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Debates in Hospital Medicine
At a hospital at which I work, every patient who presents to the emergency department with a suspected stroke or transient ischemic attack is evaluated by the stroke team. Per protocol, the team rapidly assesses each patient, orders diagnostic and therapeutic interventions and then refers each and every patient to the hospitalist service for admission and medical comanagement. At no point is any consideration given to whether the patients actually have medical comorbidities, or if a hospitalist will have anything meaningful to add to the care. The firmly set expectation is that hospitalists admit all stroke patients for the purposes of comanagement, while the neurologists consult.
Comanagement has become a mainstay of hospital medicine.1 It is predicated upon the assumption that surgical and specialty patients benefit when their medical comorbidities are managed by hospitalists. It differs conceptually from traditional medical consultation in that hospitalists collaboratively manage patients with surgeons or specialists, sharing responsibility and authority. In practice, however, comanagement varies widely, ranging from a model of care indistinguishable from traditional medical consultation to one where hospitalists admit and assume primary responsibility for surgical and specialty patients. This variability makes it difficult to study and make generalizations about the role and impact of hospitalist comanagement. Nonetheless, recent evidence suggests that hospitalist consultation and comanagement may not be as effective as originally anticipated.
In a 2008 observational cohort study of patients undergoing surgery at an academic medical center, Auerbach et al demonstrated that medical consultation (provided by hospitalists) did not improve glycemic control or increase the likelihood of perioperative beta‐blockade and venous thromboembolism prophylaxis.2 Patients who received consultation had longer adjusted lengths of stay (12.98% longer; 95% confidence interval, 1.61%‐25.61%) and higher adjusted costs (24.36% higher; 95% confidence interval, 13.54%‐36.34%). Notwithstanding the limited generalizability of this study to community hospitals, it has raised concerns that hospitalist consultation does not automatically improve quality of care or cost effectiveness.3
Several other recent trials have also helped to define where hospitalist comanagement may work well and where it may not. In 2004, Huddleston et al published the Hospitalist Orthopedic Team (HOT) trial, the first randomized prospective trial comparing hospitalist‐surgical comanagement to standard care.4 A total of 526 patients undergoing elective hip or knee replacement surgery at the Mayo Clinic were randomized to either standard orthopedic care with consultation as needed, or immediate hospitalist comanagement. The outcomes were disappointing. Hospitalist comanagement reduced minor complications (such as incidence of urinary tract infections, fever, and hyponatremia) but had no effect on moderate or major complications. The HOT intervention modestly reduced adjusted length of stay (LOS), defined as the point at which patients were deemed stable for discharge, by 0.5 days, but had no impact on actual LOS or cost per case. Not surprisingly, orthopedic surgeons and nurses preferred the HOT model of care over the standard model. One year later, Phy et al analyzed outcomes for patients admitted with hip fracture at the same institution.5 This retrospective cohort study compared patients who were admitted to either a standard orthopedic service or to a hospitalist team. In contrast to the HOT trial, hospitalist comanagement of hip fracture patients decreased time to surgery and lowered LOS by 2.2 days without compromising patient outcomes.
How did two trials that occurred roughly simultaneously at the same hospital, involving the same hospitalists and orthopedic surgeons generate such different outcomes? A likely answer is patient selection. Patients who undergo elective joint replacement are usually relatively healthy. They are almost always ambulatory and their comorbidities, when present, are generally reasonably compensated. As a rule, they fare well postoperatively, as evidenced by the 1.3% major complication rate demonstrated in the HOT trial.3 In contrast, hip fracture patients are older, have greater comorbidity and are at remarkably high risk for developing perioperative delirium.3, 4, 6 By definition, their urgent/emergent hip surgery stratifies them to a higher operative risk category than patients who undergo elective joint replacement.7 Half of hip fracture patients do not return to premorbid levels of function, and the 1‐year mortality rate has been estimated to be as high as 25%.6, 8 Given these differences, it is not surprising that hip fracture patients are more likely than elective joint replacement patients to respond favorably to hospitalist comanagement.
In 2007, Simon et al published a retrospective study of 739 pediatric spinal fusion patients at Childrens' Hospital in Denver.9 Beginning in 2004, hospitalists comanaged selected, high‐risk surgical patients (14 of 115 spinal fusion patients, or 12%). Over the course of the study, the mean LOS for low‐risk patients decreased by 21% but the mean LOS for the high‐risk, hospitalist‐comanaged patients decreased by 28%; a 33% relative reduction favoring hospitalist‐managed patients. By targeting selected high‐risk patients, pediatric hospitalists were able to improve upon LOS reductions that occurred systemically across the entire spinal fusion program. Also in 2007, Southern et al compared outcomes for 2,913 patients admitted by full‐time teaching hospitalists vs 6,124 patients admitted by nonhospitalists at Montefiore Medical Center, Bronx, New York.10 Mean LOS for patients admitted to the hospitalist service was 5.01 days vs 5.87 days for the nonhospitalists. Subgroup analysis demonstrated the greatest LOS differentials for patients requiring close clinical monitoring (heart failure, stroke, asthma, or pneumonia) or complex discharge planning.
Although these studies, performed at large academic medical centers, may have limited generalizability, they support the common‐sense notion that hospitalists most benefit patients who are sick, frail, and medically or socially complex. As a corollary, hospitalists probably offer relatively little benefit to surgical and specialty patients who are young or have compensated medical comorbidities and/or straightforward disposition plans. The enormous variability across healthcare institutions makes it difficult if not impossible to define a patient acuity or complexity cutoff below which hospitalist comanagement is unlikely to be beneficial. Nonetheless, some degree of common sense can be applied. As a case in point, a hospitalist probably adds little value to the care of a basically healthy patient with a hemodynamically stable upper gastrointestinal bleed. Despite this, in many institutions, hospitalists admit or comanage all gastroenterology patients, irrespective of their diagnosis, acuity, or complexity.11
One can even hypothesize that hospitalist comanagement may potentially inject risk into patient care. Admitting that patient with a stable upper gastrointestinal bleed to a hospitalist service may delay the gastroenterologist's involvement and initiation of the necessary endoscopy. Having assumed that the hospitalist is running the show, the gastroenterologist may pay insufficient attention to the patient. The hospitalist and gastroenterologist may give conflicting orders and reports that confuse patients, families, and hospital staff, ultimately increasing the likelihood of medical errors.
Ultimately, the risks inherent in adding complexity into patient care must be balanced against the potential benefits. For patients who are sick, frail, or complicated, the risk‐benefit ratio probably tilts in favor of comanagement. However, for generally healthy patients, it is conceivable that adding complexity negates (or worse yet, exceeds) the putative benefits of comanagement.
Given the potential limitations of hospitalist comanagement, why are hospitalists admitting or managing broad and unselected populations of surgical and specialty patients? Hospital leaders have suggested that hospitalist comanagement may protect overstretched surgeons and specialists and extend their capacity. A hospital with only one neurosurgeon on staff might reasonably ask its hospitalists to primarily manage carefully selected low‐acuity neurosurgical patients, allowing the neurosurgeon to serve as a consultant. However, in communities where specialists and surgeons are abundant, this justification is less credible. In such cases, it is difficult not to suspect that the primary reason that hospitalists admit surgical and specialty patients is to enhance the income and quality of life of the surgeons and specialists.
Expanding hospitalist comanagement services for no other reason than to keep specialists and surgeons happy might be justifiable if hospital medicine was not faced with its own critical manpower shortage. Hospital medicine is expected to grow from approximately 20,000 current practitioners to more than 40,000 within a decade.12 The growing shortage of qualified hospitalists has become a preoccupation for hospitalist employers across the country.13 At its 2006 strategic planning retreat, the Board of Directors of the Society of Hospital Medicine identified this issue as one of the greatest threats to the future health of hospital medicine.14 Demand for hospitalists will not abate for at least a decade, which will leave many hospitalist programs significantly understaffed for the foreseeable future. Understaffing forces hospitalist programs to lower hiring standards, jeopardizes patient care, accelerates physician burnout, and may ultimately destabilize hospital medicine.15 Understaffed hospitalist programs should be very circumspect about how and where they expand their clinical coverage.
Another principle underlying hospitalist comanagement is that it improves care by allowing surgeons and specialists to focus on their areas of expertise. Surgeons and specialists who do not have to manage their patients' medical issues can presumably spend more time focusing on their own disciplines. Although this argument is conceptually appealing, there is no evidence that this actually occurs. In fact, it is equally conceivable that hospitalist comanagement could jeopardize care by disengaging surgeons and specialists from their patients' progress (or lack thereof). Furthermore, evidence suggests that hospitalists are underprepared to manage diagnoses that have historically been the purview of surgeons and specialists. Practicing hospitalists who manage acute neurological and neurosurgical conditions, orthopedic trauma, and acute psychiatric illnesses have reported relative undertraining in all of these disease states.10, 16 Generally, hospitalists are expected to deliver this care in the absence of any regime to assess their competence, provide targeted training to fill knowledge gaps, and monitor their progress. At minimum, this should raise concerns about the quality and consistency of care that hospitalists provide to nonmedical patients.
Finally, working collaboratively with other specialties should be a major professional benefit of comanagement. In well‐designed comanagement arrangements, hospitalists and specialists work equitably under clearly defined and mutually agreed upon rules of engagement. They share responsibility for patients, collaborate to improve care, and teach and learn from each other. Unfortunately, in many instances, the power structure becomes lopsided, with surgeons and specialists dictating how, when, and why hospitalists manage their patients.17 Emergency departments have learned to default surgical and specialty patient admissions to hospitalists when surgeons and specialists balk. Hospital administrations may tacitly or overtly expect their financially subsidized hospitalists to cheerfully accept any and all referrals, irrespective of how inappropriate they may be. Practicing hospitalists frequently complain about their subordinate status and inability to control their working conditions, both of which are identified risk factors for career dissatisfaction and burnout.14, 16, 18 Once again, as a specialty facing a critical manpower shortage, hospitalist programs should be very attuned to defining work conditions that foster career satisfaction and physician retention.
REFRAMING COMANAGEMENT
The history of healthcare is laden with examples of new ideas that were widely and indiscriminately adopted only to subsequently fail to withstand rigorous scrutiny.19, 20 The unchecked expansion of hospitalist comanagement has the potential to become another case in point. In the absence of clear definitions of comanagement and good evidence to define best practices, hospitalists are left to use their best judgment to define the parameters of their comanagement services. At minimum, hospitalist leaders should ask some basic questions as they ponder potential comanagement relationships:
-
Why are we being asked to provide this service?
-
Do the patients have comorbidities that require our input?
-
Is there a legitimate quality or efficiency case to be made to support our participation?
-
Do we have the manpower to provide the service? If not, what will suffer as a result?
-
Will the relationship be equitable?
-
What might go wrong?
Comanagement is an appealing construct that has grown to fill many niches of healthcare delivery.10 Given compelling reasons to be skeptical about the purported benefits of comanagement, hospitalists should be circumspect about how and where they offer such services. Comanagement should be applied carefully and methodically, paying close attention to the consequences, intended and unintended. Applying comanagement in a rational, evidence‐based, and sustainable fashion will ultimately better serve patients, the healthcare community, and hospital medicine.
- Society of Hospital Medicine. The Society of Hospital Medicine 2005–2006 Survey: The Authoritative Source on the State of the Hospital Medicine Movement. Published by the, 2006. Executive summary available at http://www.hospitalmedicine.org/AM/Template.cfm?Section=Surveys2167(21):2338–2344.
- Exceed acceptable: new studies challenge hospitalists to prove our value.Hospitalist.2008;12(2):63. .
- Medical and surgical comanagement after elective hip and knee arthroplasty.Ann Intern Med.2004;141:28–38. , , , et al.
- Effects of a hospitalist model on elderly patients with hip fracture.Arch Intern Med.2005;165:796–801. , , , et al.
- Treatment and survival among elderly Americans with hip fractures: a population‐based study.Am J Public Health.1994;84:1287–1291. , , , .
- Predicting cardiac complications in patients undergoing non‐cardiac surgery.J Gen Intern Med.1986;1:211–219. , , , et al.
- Predictors of functional recovery one year following hospital discharge for hip fracture: a prospective study.J Gerontol.1990;45(3):M101–M107. , , , , .
- Pediatric hospitalist comanagement of spinal fusion surgery patients.J Hosp Med.2007;2:23–29. , , , , , .
- Hospitalist care and length of stay in patients requiring complex discharge planning and close clinical monitoring.Arch Intern Med.2007;167:1869–1874. , , , , .
- The spectrum of community‐based hospitalist practice, a call to tailor internal medicine residency training.Arch Intern Med.2007;167(7):727–728. , , , , .
- Society of Hospital Medicine. Growth of Hospital Medicine Nationwide. http://www.hospitalmedicine.org/Content/NavigationMenu/Media/GrowthofHospitalMedicineNation wide/Growth_of_Hospital_M.htm. Accessed September 2,2008.
- Rebuilding the future of the private practice of hospital medicine.The Phoenix Group, May2007. , , , et al.
- Society of Hospital Medicine Board of Directors Strategic Planning Retreat: November 28‐29,2006.
- for the SGIM Career Satisfaction Study Group.Physician stress: results from the physician worklife study.Stress Health.2001;18(1):37–42. , , , , , ,
- Hospitalist's perceptions of their residency training needs: Results of a national survey.Am J Med.2001;111:247–254. , , , et al.
- Feeling pressure to admit surgical patients? Hospitalists work to set limits on co‐management arrangements.Today's Hospitalist. January2008. .
- Society of Hospital Medicine. Career Satisfaction White Paper. http://www.hospitalmedicine.org/AM/Template.cfm?Section=Practice_Resources321:406–412.
- Pulmonary‐artery catheters—peace at last?N Engl J Med.2006;354(21):2273–2274. .
At a hospital at which I work, every patient who presents to the emergency department with a suspected stroke or transient ischemic attack is evaluated by the stroke team. Per protocol, the team rapidly assesses each patient, orders diagnostic and therapeutic interventions and then refers each and every patient to the hospitalist service for admission and medical comanagement. At no point is any consideration given to whether the patients actually have medical comorbidities, or if a hospitalist will have anything meaningful to add to the care. The firmly set expectation is that hospitalists admit all stroke patients for the purposes of comanagement, while the neurologists consult.
Comanagement has become a mainstay of hospital medicine.1 It is predicated upon the assumption that surgical and specialty patients benefit when their medical comorbidities are managed by hospitalists. It differs conceptually from traditional medical consultation in that hospitalists collaboratively manage patients with surgeons or specialists, sharing responsibility and authority. In practice, however, comanagement varies widely, ranging from a model of care indistinguishable from traditional medical consultation to one where hospitalists admit and assume primary responsibility for surgical and specialty patients. This variability makes it difficult to study and make generalizations about the role and impact of hospitalist comanagement. Nonetheless, recent evidence suggests that hospitalist consultation and comanagement may not be as effective as originally anticipated.
In a 2008 observational cohort study of patients undergoing surgery at an academic medical center, Auerbach et al demonstrated that medical consultation (provided by hospitalists) did not improve glycemic control or increase the likelihood of perioperative beta‐blockade and venous thromboembolism prophylaxis.2 Patients who received consultation had longer adjusted lengths of stay (12.98% longer; 95% confidence interval, 1.61%‐25.61%) and higher adjusted costs (24.36% higher; 95% confidence interval, 13.54%‐36.34%). Notwithstanding the limited generalizability of this study to community hospitals, it has raised concerns that hospitalist consultation does not automatically improve quality of care or cost effectiveness.3
Several other recent trials have also helped to define where hospitalist comanagement may work well and where it may not. In 2004, Huddleston et al published the Hospitalist Orthopedic Team (HOT) trial, the first randomized prospective trial comparing hospitalist‐surgical comanagement to standard care.4 A total of 526 patients undergoing elective hip or knee replacement surgery at the Mayo Clinic were randomized to either standard orthopedic care with consultation as needed, or immediate hospitalist comanagement. The outcomes were disappointing. Hospitalist comanagement reduced minor complications (such as incidence of urinary tract infections, fever, and hyponatremia) but had no effect on moderate or major complications. The HOT intervention modestly reduced adjusted length of stay (LOS), defined as the point at which patients were deemed stable for discharge, by 0.5 days, but had no impact on actual LOS or cost per case. Not surprisingly, orthopedic surgeons and nurses preferred the HOT model of care over the standard model. One year later, Phy et al analyzed outcomes for patients admitted with hip fracture at the same institution.5 This retrospective cohort study compared patients who were admitted to either a standard orthopedic service or to a hospitalist team. In contrast to the HOT trial, hospitalist comanagement of hip fracture patients decreased time to surgery and lowered LOS by 2.2 days without compromising patient outcomes.
How did two trials that occurred roughly simultaneously at the same hospital, involving the same hospitalists and orthopedic surgeons generate such different outcomes? A likely answer is patient selection. Patients who undergo elective joint replacement are usually relatively healthy. They are almost always ambulatory and their comorbidities, when present, are generally reasonably compensated. As a rule, they fare well postoperatively, as evidenced by the 1.3% major complication rate demonstrated in the HOT trial.3 In contrast, hip fracture patients are older, have greater comorbidity and are at remarkably high risk for developing perioperative delirium.3, 4, 6 By definition, their urgent/emergent hip surgery stratifies them to a higher operative risk category than patients who undergo elective joint replacement.7 Half of hip fracture patients do not return to premorbid levels of function, and the 1‐year mortality rate has been estimated to be as high as 25%.6, 8 Given these differences, it is not surprising that hip fracture patients are more likely than elective joint replacement patients to respond favorably to hospitalist comanagement.
In 2007, Simon et al published a retrospective study of 739 pediatric spinal fusion patients at Childrens' Hospital in Denver.9 Beginning in 2004, hospitalists comanaged selected, high‐risk surgical patients (14 of 115 spinal fusion patients, or 12%). Over the course of the study, the mean LOS for low‐risk patients decreased by 21% but the mean LOS for the high‐risk, hospitalist‐comanaged patients decreased by 28%; a 33% relative reduction favoring hospitalist‐managed patients. By targeting selected high‐risk patients, pediatric hospitalists were able to improve upon LOS reductions that occurred systemically across the entire spinal fusion program. Also in 2007, Southern et al compared outcomes for 2,913 patients admitted by full‐time teaching hospitalists vs 6,124 patients admitted by nonhospitalists at Montefiore Medical Center, Bronx, New York.10 Mean LOS for patients admitted to the hospitalist service was 5.01 days vs 5.87 days for the nonhospitalists. Subgroup analysis demonstrated the greatest LOS differentials for patients requiring close clinical monitoring (heart failure, stroke, asthma, or pneumonia) or complex discharge planning.
Although these studies, performed at large academic medical centers, may have limited generalizability, they support the common‐sense notion that hospitalists most benefit patients who are sick, frail, and medically or socially complex. As a corollary, hospitalists probably offer relatively little benefit to surgical and specialty patients who are young or have compensated medical comorbidities and/or straightforward disposition plans. The enormous variability across healthcare institutions makes it difficult if not impossible to define a patient acuity or complexity cutoff below which hospitalist comanagement is unlikely to be beneficial. Nonetheless, some degree of common sense can be applied. As a case in point, a hospitalist probably adds little value to the care of a basically healthy patient with a hemodynamically stable upper gastrointestinal bleed. Despite this, in many institutions, hospitalists admit or comanage all gastroenterology patients, irrespective of their diagnosis, acuity, or complexity.11
One can even hypothesize that hospitalist comanagement may potentially inject risk into patient care. Admitting that patient with a stable upper gastrointestinal bleed to a hospitalist service may delay the gastroenterologist's involvement and initiation of the necessary endoscopy. Having assumed that the hospitalist is running the show, the gastroenterologist may pay insufficient attention to the patient. The hospitalist and gastroenterologist may give conflicting orders and reports that confuse patients, families, and hospital staff, ultimately increasing the likelihood of medical errors.
Ultimately, the risks inherent in adding complexity into patient care must be balanced against the potential benefits. For patients who are sick, frail, or complicated, the risk‐benefit ratio probably tilts in favor of comanagement. However, for generally healthy patients, it is conceivable that adding complexity negates (or worse yet, exceeds) the putative benefits of comanagement.
Given the potential limitations of hospitalist comanagement, why are hospitalists admitting or managing broad and unselected populations of surgical and specialty patients? Hospital leaders have suggested that hospitalist comanagement may protect overstretched surgeons and specialists and extend their capacity. A hospital with only one neurosurgeon on staff might reasonably ask its hospitalists to primarily manage carefully selected low‐acuity neurosurgical patients, allowing the neurosurgeon to serve as a consultant. However, in communities where specialists and surgeons are abundant, this justification is less credible. In such cases, it is difficult not to suspect that the primary reason that hospitalists admit surgical and specialty patients is to enhance the income and quality of life of the surgeons and specialists.
Expanding hospitalist comanagement services for no other reason than to keep specialists and surgeons happy might be justifiable if hospital medicine was not faced with its own critical manpower shortage. Hospital medicine is expected to grow from approximately 20,000 current practitioners to more than 40,000 within a decade.12 The growing shortage of qualified hospitalists has become a preoccupation for hospitalist employers across the country.13 At its 2006 strategic planning retreat, the Board of Directors of the Society of Hospital Medicine identified this issue as one of the greatest threats to the future health of hospital medicine.14 Demand for hospitalists will not abate for at least a decade, which will leave many hospitalist programs significantly understaffed for the foreseeable future. Understaffing forces hospitalist programs to lower hiring standards, jeopardizes patient care, accelerates physician burnout, and may ultimately destabilize hospital medicine.15 Understaffed hospitalist programs should be very circumspect about how and where they expand their clinical coverage.
Another principle underlying hospitalist comanagement is that it improves care by allowing surgeons and specialists to focus on their areas of expertise. Surgeons and specialists who do not have to manage their patients' medical issues can presumably spend more time focusing on their own disciplines. Although this argument is conceptually appealing, there is no evidence that this actually occurs. In fact, it is equally conceivable that hospitalist comanagement could jeopardize care by disengaging surgeons and specialists from their patients' progress (or lack thereof). Furthermore, evidence suggests that hospitalists are underprepared to manage diagnoses that have historically been the purview of surgeons and specialists. Practicing hospitalists who manage acute neurological and neurosurgical conditions, orthopedic trauma, and acute psychiatric illnesses have reported relative undertraining in all of these disease states.10, 16 Generally, hospitalists are expected to deliver this care in the absence of any regime to assess their competence, provide targeted training to fill knowledge gaps, and monitor their progress. At minimum, this should raise concerns about the quality and consistency of care that hospitalists provide to nonmedical patients.
Finally, working collaboratively with other specialties should be a major professional benefit of comanagement. In well‐designed comanagement arrangements, hospitalists and specialists work equitably under clearly defined and mutually agreed upon rules of engagement. They share responsibility for patients, collaborate to improve care, and teach and learn from each other. Unfortunately, in many instances, the power structure becomes lopsided, with surgeons and specialists dictating how, when, and why hospitalists manage their patients.17 Emergency departments have learned to default surgical and specialty patient admissions to hospitalists when surgeons and specialists balk. Hospital administrations may tacitly or overtly expect their financially subsidized hospitalists to cheerfully accept any and all referrals, irrespective of how inappropriate they may be. Practicing hospitalists frequently complain about their subordinate status and inability to control their working conditions, both of which are identified risk factors for career dissatisfaction and burnout.14, 16, 18 Once again, as a specialty facing a critical manpower shortage, hospitalist programs should be very attuned to defining work conditions that foster career satisfaction and physician retention.
REFRAMING COMANAGEMENT
The history of healthcare is laden with examples of new ideas that were widely and indiscriminately adopted only to subsequently fail to withstand rigorous scrutiny.19, 20 The unchecked expansion of hospitalist comanagement has the potential to become another case in point. In the absence of clear definitions of comanagement and good evidence to define best practices, hospitalists are left to use their best judgment to define the parameters of their comanagement services. At minimum, hospitalist leaders should ask some basic questions as they ponder potential comanagement relationships:
-
Why are we being asked to provide this service?
-
Do the patients have comorbidities that require our input?
-
Is there a legitimate quality or efficiency case to be made to support our participation?
-
Do we have the manpower to provide the service? If not, what will suffer as a result?
-
Will the relationship be equitable?
-
What might go wrong?
Comanagement is an appealing construct that has grown to fill many niches of healthcare delivery.10 Given compelling reasons to be skeptical about the purported benefits of comanagement, hospitalists should be circumspect about how and where they offer such services. Comanagement should be applied carefully and methodically, paying close attention to the consequences, intended and unintended. Applying comanagement in a rational, evidence‐based, and sustainable fashion will ultimately better serve patients, the healthcare community, and hospital medicine.
At a hospital at which I work, every patient who presents to the emergency department with a suspected stroke or transient ischemic attack is evaluated by the stroke team. Per protocol, the team rapidly assesses each patient, orders diagnostic and therapeutic interventions and then refers each and every patient to the hospitalist service for admission and medical comanagement. At no point is any consideration given to whether the patients actually have medical comorbidities, or if a hospitalist will have anything meaningful to add to the care. The firmly set expectation is that hospitalists admit all stroke patients for the purposes of comanagement, while the neurologists consult.
Comanagement has become a mainstay of hospital medicine.1 It is predicated upon the assumption that surgical and specialty patients benefit when their medical comorbidities are managed by hospitalists. It differs conceptually from traditional medical consultation in that hospitalists collaboratively manage patients with surgeons or specialists, sharing responsibility and authority. In practice, however, comanagement varies widely, ranging from a model of care indistinguishable from traditional medical consultation to one where hospitalists admit and assume primary responsibility for surgical and specialty patients. This variability makes it difficult to study and make generalizations about the role and impact of hospitalist comanagement. Nonetheless, recent evidence suggests that hospitalist consultation and comanagement may not be as effective as originally anticipated.
In a 2008 observational cohort study of patients undergoing surgery at an academic medical center, Auerbach et al demonstrated that medical consultation (provided by hospitalists) did not improve glycemic control or increase the likelihood of perioperative beta‐blockade and venous thromboembolism prophylaxis.2 Patients who received consultation had longer adjusted lengths of stay (12.98% longer; 95% confidence interval, 1.61%‐25.61%) and higher adjusted costs (24.36% higher; 95% confidence interval, 13.54%‐36.34%). Notwithstanding the limited generalizability of this study to community hospitals, it has raised concerns that hospitalist consultation does not automatically improve quality of care or cost effectiveness.3
Several other recent trials have also helped to define where hospitalist comanagement may work well and where it may not. In 2004, Huddleston et al published the Hospitalist Orthopedic Team (HOT) trial, the first randomized prospective trial comparing hospitalist‐surgical comanagement to standard care.4 A total of 526 patients undergoing elective hip or knee replacement surgery at the Mayo Clinic were randomized to either standard orthopedic care with consultation as needed, or immediate hospitalist comanagement. The outcomes were disappointing. Hospitalist comanagement reduced minor complications (such as incidence of urinary tract infections, fever, and hyponatremia) but had no effect on moderate or major complications. The HOT intervention modestly reduced adjusted length of stay (LOS), defined as the point at which patients were deemed stable for discharge, by 0.5 days, but had no impact on actual LOS or cost per case. Not surprisingly, orthopedic surgeons and nurses preferred the HOT model of care over the standard model. One year later, Phy et al analyzed outcomes for patients admitted with hip fracture at the same institution.5 This retrospective cohort study compared patients who were admitted to either a standard orthopedic service or to a hospitalist team. In contrast to the HOT trial, hospitalist comanagement of hip fracture patients decreased time to surgery and lowered LOS by 2.2 days without compromising patient outcomes.
How did two trials that occurred roughly simultaneously at the same hospital, involving the same hospitalists and orthopedic surgeons generate such different outcomes? A likely answer is patient selection. Patients who undergo elective joint replacement are usually relatively healthy. They are almost always ambulatory and their comorbidities, when present, are generally reasonably compensated. As a rule, they fare well postoperatively, as evidenced by the 1.3% major complication rate demonstrated in the HOT trial.3 In contrast, hip fracture patients are older, have greater comorbidity and are at remarkably high risk for developing perioperative delirium.3, 4, 6 By definition, their urgent/emergent hip surgery stratifies them to a higher operative risk category than patients who undergo elective joint replacement.7 Half of hip fracture patients do not return to premorbid levels of function, and the 1‐year mortality rate has been estimated to be as high as 25%.6, 8 Given these differences, it is not surprising that hip fracture patients are more likely than elective joint replacement patients to respond favorably to hospitalist comanagement.
In 2007, Simon et al published a retrospective study of 739 pediatric spinal fusion patients at Childrens' Hospital in Denver.9 Beginning in 2004, hospitalists comanaged selected, high‐risk surgical patients (14 of 115 spinal fusion patients, or 12%). Over the course of the study, the mean LOS for low‐risk patients decreased by 21% but the mean LOS for the high‐risk, hospitalist‐comanaged patients decreased by 28%; a 33% relative reduction favoring hospitalist‐managed patients. By targeting selected high‐risk patients, pediatric hospitalists were able to improve upon LOS reductions that occurred systemically across the entire spinal fusion program. Also in 2007, Southern et al compared outcomes for 2,913 patients admitted by full‐time teaching hospitalists vs 6,124 patients admitted by nonhospitalists at Montefiore Medical Center, Bronx, New York.10 Mean LOS for patients admitted to the hospitalist service was 5.01 days vs 5.87 days for the nonhospitalists. Subgroup analysis demonstrated the greatest LOS differentials for patients requiring close clinical monitoring (heart failure, stroke, asthma, or pneumonia) or complex discharge planning.
Although these studies, performed at large academic medical centers, may have limited generalizability, they support the common‐sense notion that hospitalists most benefit patients who are sick, frail, and medically or socially complex. As a corollary, hospitalists probably offer relatively little benefit to surgical and specialty patients who are young or have compensated medical comorbidities and/or straightforward disposition plans. The enormous variability across healthcare institutions makes it difficult if not impossible to define a patient acuity or complexity cutoff below which hospitalist comanagement is unlikely to be beneficial. Nonetheless, some degree of common sense can be applied. As a case in point, a hospitalist probably adds little value to the care of a basically healthy patient with a hemodynamically stable upper gastrointestinal bleed. Despite this, in many institutions, hospitalists admit or comanage all gastroenterology patients, irrespective of their diagnosis, acuity, or complexity.11
One can even hypothesize that hospitalist comanagement may potentially inject risk into patient care. Admitting that patient with a stable upper gastrointestinal bleed to a hospitalist service may delay the gastroenterologist's involvement and initiation of the necessary endoscopy. Having assumed that the hospitalist is running the show, the gastroenterologist may pay insufficient attention to the patient. The hospitalist and gastroenterologist may give conflicting orders and reports that confuse patients, families, and hospital staff, ultimately increasing the likelihood of medical errors.
Ultimately, the risks inherent in adding complexity into patient care must be balanced against the potential benefits. For patients who are sick, frail, or complicated, the risk‐benefit ratio probably tilts in favor of comanagement. However, for generally healthy patients, it is conceivable that adding complexity negates (or worse yet, exceeds) the putative benefits of comanagement.
Given the potential limitations of hospitalist comanagement, why are hospitalists admitting or managing broad and unselected populations of surgical and specialty patients? Hospital leaders have suggested that hospitalist comanagement may protect overstretched surgeons and specialists and extend their capacity. A hospital with only one neurosurgeon on staff might reasonably ask its hospitalists to primarily manage carefully selected low‐acuity neurosurgical patients, allowing the neurosurgeon to serve as a consultant. However, in communities where specialists and surgeons are abundant, this justification is less credible. In such cases, it is difficult not to suspect that the primary reason that hospitalists admit surgical and specialty patients is to enhance the income and quality of life of the surgeons and specialists.
Expanding hospitalist comanagement services for no other reason than to keep specialists and surgeons happy might be justifiable if hospital medicine was not faced with its own critical manpower shortage. Hospital medicine is expected to grow from approximately 20,000 current practitioners to more than 40,000 within a decade.12 The growing shortage of qualified hospitalists has become a preoccupation for hospitalist employers across the country.13 At its 2006 strategic planning retreat, the Board of Directors of the Society of Hospital Medicine identified this issue as one of the greatest threats to the future health of hospital medicine.14 Demand for hospitalists will not abate for at least a decade, which will leave many hospitalist programs significantly understaffed for the foreseeable future. Understaffing forces hospitalist programs to lower hiring standards, jeopardizes patient care, accelerates physician burnout, and may ultimately destabilize hospital medicine.15 Understaffed hospitalist programs should be very circumspect about how and where they expand their clinical coverage.
Another principle underlying hospitalist comanagement is that it improves care by allowing surgeons and specialists to focus on their areas of expertise. Surgeons and specialists who do not have to manage their patients' medical issues can presumably spend more time focusing on their own disciplines. Although this argument is conceptually appealing, there is no evidence that this actually occurs. In fact, it is equally conceivable that hospitalist comanagement could jeopardize care by disengaging surgeons and specialists from their patients' progress (or lack thereof). Furthermore, evidence suggests that hospitalists are underprepared to manage diagnoses that have historically been the purview of surgeons and specialists. Practicing hospitalists who manage acute neurological and neurosurgical conditions, orthopedic trauma, and acute psychiatric illnesses have reported relative undertraining in all of these disease states.10, 16 Generally, hospitalists are expected to deliver this care in the absence of any regime to assess their competence, provide targeted training to fill knowledge gaps, and monitor their progress. At minimum, this should raise concerns about the quality and consistency of care that hospitalists provide to nonmedical patients.
Finally, working collaboratively with other specialties should be a major professional benefit of comanagement. In well‐designed comanagement arrangements, hospitalists and specialists work equitably under clearly defined and mutually agreed upon rules of engagement. They share responsibility for patients, collaborate to improve care, and teach and learn from each other. Unfortunately, in many instances, the power structure becomes lopsided, with surgeons and specialists dictating how, when, and why hospitalists manage their patients.17 Emergency departments have learned to default surgical and specialty patient admissions to hospitalists when surgeons and specialists balk. Hospital administrations may tacitly or overtly expect their financially subsidized hospitalists to cheerfully accept any and all referrals, irrespective of how inappropriate they may be. Practicing hospitalists frequently complain about their subordinate status and inability to control their working conditions, both of which are identified risk factors for career dissatisfaction and burnout.14, 16, 18 Once again, as a specialty facing a critical manpower shortage, hospitalist programs should be very attuned to defining work conditions that foster career satisfaction and physician retention.
REFRAMING COMANAGEMENT
The history of healthcare is laden with examples of new ideas that were widely and indiscriminately adopted only to subsequently fail to withstand rigorous scrutiny.19, 20 The unchecked expansion of hospitalist comanagement has the potential to become another case in point. In the absence of clear definitions of comanagement and good evidence to define best practices, hospitalists are left to use their best judgment to define the parameters of their comanagement services. At minimum, hospitalist leaders should ask some basic questions as they ponder potential comanagement relationships:
-
Why are we being asked to provide this service?
-
Do the patients have comorbidities that require our input?
-
Is there a legitimate quality or efficiency case to be made to support our participation?
-
Do we have the manpower to provide the service? If not, what will suffer as a result?
-
Will the relationship be equitable?
-
What might go wrong?
Comanagement is an appealing construct that has grown to fill many niches of healthcare delivery.10 Given compelling reasons to be skeptical about the purported benefits of comanagement, hospitalists should be circumspect about how and where they offer such services. Comanagement should be applied carefully and methodically, paying close attention to the consequences, intended and unintended. Applying comanagement in a rational, evidence‐based, and sustainable fashion will ultimately better serve patients, the healthcare community, and hospital medicine.
- Society of Hospital Medicine. The Society of Hospital Medicine 2005–2006 Survey: The Authoritative Source on the State of the Hospital Medicine Movement. Published by the, 2006. Executive summary available at http://www.hospitalmedicine.org/AM/Template.cfm?Section=Surveys2167(21):2338–2344.
- Exceed acceptable: new studies challenge hospitalists to prove our value.Hospitalist.2008;12(2):63. .
- Medical and surgical comanagement after elective hip and knee arthroplasty.Ann Intern Med.2004;141:28–38. , , , et al.
- Effects of a hospitalist model on elderly patients with hip fracture.Arch Intern Med.2005;165:796–801. , , , et al.
- Treatment and survival among elderly Americans with hip fractures: a population‐based study.Am J Public Health.1994;84:1287–1291. , , , .
- Predicting cardiac complications in patients undergoing non‐cardiac surgery.J Gen Intern Med.1986;1:211–219. , , , et al.
- Predictors of functional recovery one year following hospital discharge for hip fracture: a prospective study.J Gerontol.1990;45(3):M101–M107. , , , , .
- Pediatric hospitalist comanagement of spinal fusion surgery patients.J Hosp Med.2007;2:23–29. , , , , , .
- Hospitalist care and length of stay in patients requiring complex discharge planning and close clinical monitoring.Arch Intern Med.2007;167:1869–1874. , , , , .
- The spectrum of community‐based hospitalist practice, a call to tailor internal medicine residency training.Arch Intern Med.2007;167(7):727–728. , , , , .
- Society of Hospital Medicine. Growth of Hospital Medicine Nationwide. http://www.hospitalmedicine.org/Content/NavigationMenu/Media/GrowthofHospitalMedicineNation wide/Growth_of_Hospital_M.htm. Accessed September 2,2008.
- Rebuilding the future of the private practice of hospital medicine.The Phoenix Group, May2007. , , , et al.
- Society of Hospital Medicine Board of Directors Strategic Planning Retreat: November 28‐29,2006.
- for the SGIM Career Satisfaction Study Group.Physician stress: results from the physician worklife study.Stress Health.2001;18(1):37–42. , , , , , ,
- Hospitalist's perceptions of their residency training needs: Results of a national survey.Am J Med.2001;111:247–254. , , , et al.
- Feeling pressure to admit surgical patients? Hospitalists work to set limits on co‐management arrangements.Today's Hospitalist. January2008. .
- Society of Hospital Medicine. Career Satisfaction White Paper. http://www.hospitalmedicine.org/AM/Template.cfm?Section=Practice_Resources321:406–412.
- Pulmonary‐artery catheters—peace at last?N Engl J Med.2006;354(21):2273–2274. .
- Society of Hospital Medicine. The Society of Hospital Medicine 2005–2006 Survey: The Authoritative Source on the State of the Hospital Medicine Movement. Published by the, 2006. Executive summary available at http://www.hospitalmedicine.org/AM/Template.cfm?Section=Surveys2167(21):2338–2344.
- Exceed acceptable: new studies challenge hospitalists to prove our value.Hospitalist.2008;12(2):63. .
- Medical and surgical comanagement after elective hip and knee arthroplasty.Ann Intern Med.2004;141:28–38. , , , et al.
- Effects of a hospitalist model on elderly patients with hip fracture.Arch Intern Med.2005;165:796–801. , , , et al.
- Treatment and survival among elderly Americans with hip fractures: a population‐based study.Am J Public Health.1994;84:1287–1291. , , , .
- Predicting cardiac complications in patients undergoing non‐cardiac surgery.J Gen Intern Med.1986;1:211–219. , , , et al.
- Predictors of functional recovery one year following hospital discharge for hip fracture: a prospective study.J Gerontol.1990;45(3):M101–M107. , , , , .
- Pediatric hospitalist comanagement of spinal fusion surgery patients.J Hosp Med.2007;2:23–29. , , , , , .
- Hospitalist care and length of stay in patients requiring complex discharge planning and close clinical monitoring.Arch Intern Med.2007;167:1869–1874. , , , , .
- The spectrum of community‐based hospitalist practice, a call to tailor internal medicine residency training.Arch Intern Med.2007;167(7):727–728. , , , , .
- Society of Hospital Medicine. Growth of Hospital Medicine Nationwide. http://www.hospitalmedicine.org/Content/NavigationMenu/Media/GrowthofHospitalMedicineNation wide/Growth_of_Hospital_M.htm. Accessed September 2,2008.
- Rebuilding the future of the private practice of hospital medicine.The Phoenix Group, May2007. , , , et al.
- Society of Hospital Medicine Board of Directors Strategic Planning Retreat: November 28‐29,2006.
- for the SGIM Career Satisfaction Study Group.Physician stress: results from the physician worklife study.Stress Health.2001;18(1):37–42. , , , , , ,
- Hospitalist's perceptions of their residency training needs: Results of a national survey.Am J Med.2001;111:247–254. , , , et al.
- Feeling pressure to admit surgical patients? Hospitalists work to set limits on co‐management arrangements.Today's Hospitalist. January2008. .
- Society of Hospital Medicine. Career Satisfaction White Paper. http://www.hospitalmedicine.org/AM/Template.cfm?Section=Practice_Resources321:406–412.
- Pulmonary‐artery catheters—peace at last?N Engl J Med.2006;354(21):2273–2274. .
Purple Like a Glove
A 90‐year‐old female nursing home resident was admitted for hyponatremia and altered mental status. A Foley catheter was placed on admission. On hospital day 2, the Foley catheter was found to be draining violet urine. Urinalysis showed a pH of 9.0, numerous white cells, leukocyte esterase, and bacteria. Urine culture grew Proteus mirabilis. Purple Urine Bag Syndrome (PUBS) is a rare phenomenon associated with alkaline urine due to a urinary tract infection. The patient was treated with ciprofloxacin, and her urine returned to a pale yellow color. While alarming to patients and providers alike, PUBS is a benign herald of urinary tract infection, often in an elderly woman with constipation. In normal individuals, tryptophan is metabolized to indole by gut flora, which is in turn conjugated to indoxyl sulfate (IS) by the liver. Urine excretion of IS varies by individual. Sulfatase‐containing bacteria, notably Providencia, Klebsiella, and Proteus species, then catabolize IS to indoxyl. In an alkaline environment indoxyl isomers interact to alternately yield indigo or indirubin which jointly create the urine's characteristic violet color.0

- Enzymatic degradation of urinary indoxyl sulfate by Providencia stuartii and Klebsiella pneumonia causes the purple urine bag syndrome.J Clin Microbiol.1988;26(10):2152–2156. , , .
A 90‐year‐old female nursing home resident was admitted for hyponatremia and altered mental status. A Foley catheter was placed on admission. On hospital day 2, the Foley catheter was found to be draining violet urine. Urinalysis showed a pH of 9.0, numerous white cells, leukocyte esterase, and bacteria. Urine culture grew Proteus mirabilis. Purple Urine Bag Syndrome (PUBS) is a rare phenomenon associated with alkaline urine due to a urinary tract infection. The patient was treated with ciprofloxacin, and her urine returned to a pale yellow color. While alarming to patients and providers alike, PUBS is a benign herald of urinary tract infection, often in an elderly woman with constipation. In normal individuals, tryptophan is metabolized to indole by gut flora, which is in turn conjugated to indoxyl sulfate (IS) by the liver. Urine excretion of IS varies by individual. Sulfatase‐containing bacteria, notably Providencia, Klebsiella, and Proteus species, then catabolize IS to indoxyl. In an alkaline environment indoxyl isomers interact to alternately yield indigo or indirubin which jointly create the urine's characteristic violet color.0

A 90‐year‐old female nursing home resident was admitted for hyponatremia and altered mental status. A Foley catheter was placed on admission. On hospital day 2, the Foley catheter was found to be draining violet urine. Urinalysis showed a pH of 9.0, numerous white cells, leukocyte esterase, and bacteria. Urine culture grew Proteus mirabilis. Purple Urine Bag Syndrome (PUBS) is a rare phenomenon associated with alkaline urine due to a urinary tract infection. The patient was treated with ciprofloxacin, and her urine returned to a pale yellow color. While alarming to patients and providers alike, PUBS is a benign herald of urinary tract infection, often in an elderly woman with constipation. In normal individuals, tryptophan is metabolized to indole by gut flora, which is in turn conjugated to indoxyl sulfate (IS) by the liver. Urine excretion of IS varies by individual. Sulfatase‐containing bacteria, notably Providencia, Klebsiella, and Proteus species, then catabolize IS to indoxyl. In an alkaline environment indoxyl isomers interact to alternately yield indigo or indirubin which jointly create the urine's characteristic violet color.0

- Enzymatic degradation of urinary indoxyl sulfate by Providencia stuartii and Klebsiella pneumonia causes the purple urine bag syndrome.J Clin Microbiol.1988;26(10):2152–2156. , , .
- Enzymatic degradation of urinary indoxyl sulfate by Providencia stuartii and Klebsiella pneumonia causes the purple urine bag syndrome.J Clin Microbiol.1988;26(10):2152–2156. , , .
Ethics of Discharge Against Medical Advice
BACKGROUND
Discharges against medical advice (AMA) account for approximately 1% of discharges for general medical patients and up to 10% and 30% for patients afflicted with HIV disease and psychiatric disorders, respectively.17 Patients discharged AMA have higher rates of readmission, longer subsequent hospital stays, and worse health outcomes.3, 5, 811 Not unexpectedly, discharges AMA are associated with overall health costs of up to 50% greater than usual discharges.2
Patients who leave AMA are more likely to have poorer social supports, to abuse alcohol, heroin, and other substances, and often have weighty psychosocial or financial concerns.1218 They are also less likely to have an established relationship with a primary care physician.19 Although studies have found that rates of discharge AMA are higher among some ethnic minorities, one recent study suggests that other patient variables, such as level of income and type of insurance, may be more closely related.7, 20 Unfortunately, many patients who leave AMA have dual sources of distress: compelling personal concerns that fuel one's wish to leave and the illness that initially caused the patient to seek care.
Physicians are often distressed by the clinical and ethical challenges of discharges AMA. How should physicians manage their conflicted obligations to respect patients' choices and to prevent harms from befalling their patients? What are physicians' obligations to their patients who leave accepting only partial or inadequate treatment plans or no treatment at all? When should physicians call into question the decision‐making capacity of patients' who make seemingly unwise or clearly dangerous judgments to leave the hospital? In addition to these sorts of concerns, physicians who discharge patients AMA enjoy no definitive legal protection from the consequences of their patients' choices.2123 In fact, good clinical judgement and careful documentation provide the best liability protection.24
Clearly, discharges AMA are problematic for patients, stressful for physicians, and resource intensive for health facilities. Therefore, efforts to understand, better manage, and ultimately decrease discharges AMA will benefit all parties. Whereas the literature on discharge AMA tends to focus on psychiatric and substance abuse patients, this review examines the professional and ethical implications of discharge AMA more generally.
Does Discharge AMA Differ from Treatment Nonadherence Elsewhere in Health Care?
Patients' nonadherence to recommended treatment is often influenced by treatment side effects, costs, inconvenience, psychosocial burden, and the quality of the patient‐physician relationship. Not surprisingly, these same factors are often associated with discharge AMA.2528 In fact, nonadherence in discharge AMA and nonadherence elsewhere are fundamentally similar. Differences, where they exist, are often in the degree or imminency of health risk and in the ability of physicians to monitor the patient.
Discharges AMA tend to involve health risks that are more acute and more severe compared to general nonadherence. To illustrate, Patient A is diagnosed with the metabolic syndrome during an office visit. His physician recommends medical therapy, and the patient declines, thereby incurring a high risk of a cardiovascular event within the next 10 years. Patient B presents to the hospital with an acute coronary syndrome. He declines to remain in the hospital for an evaluation of ischemic burden despite a high risk of a myocardial infarction in the next few days. Patient A is motivated by the cost of medication and chooses to purchase his wife's medications, foregoing his own. Patient B is motivated by distress over leaving his frail wife alone at home and concerns of medical bills that he can not afford to pay. The patient in each of these cases is motivated by social and financial concerns. The consequence of each patient's choice is a higher risk of a cardiovascular event. A major difference is the temporal relationship between the decision to not accept treatment and the ensuing adverse event.
Of course, high‐risk situations are not exclusive to the inpatient setting. For example, a patient presents to a physician's office after having experienced substernal chest pain during the previous evening. The physician recommends hospitalization but the patient declines. Conversely, a hospitalized patient may pursue discharge AMA because the patient disagrees with the physician's stipulations for safe discharge plan including assistance at home. Yet, these concerns about custodial needs, if identified by the physician in an office setting, may not necessarily compel the physician to hospitalize the patient.
Another difference between discharge AMA and general nonadherence is that adherence is more readily and closely measured in the inpatient setting. Hospital‐based occurrences of nonadherence are immediately identified and addressed. To contrast, in the outpatient setting, adherence is far poorer with a 20% nonadherence rate considered to be good compliance.2931 Regardless of the setting for nonadherence, the variance between recommended and accepted treatments often stems from the fact that patients tend to make decisions based on values and broader interests whereas physicians tend to emphasize more circumscribed medical goals.32, 33
Informed and Voluntary Refusal of Treatment
A patient's intention to leave AMA may trigger physicians and other hospital staff to question the patient's decision‐making capacity.34 One's capacity to make decisions is specific to the decision at hand. For example, a patient with early dementia and an infected arterial insufficiency ulcer may not be able to fully appreciate all the consequences of premature discharge on her health, but may be able to reliably indicate her preferred health agent.
Clinicians commonly make implicit capacity determinations, and do so each time a patient's general consent for treatment is accepted. These assessments tend to be made more explicitly when the patient's decision appears to be grossly contrary to his or her welfare. Capacity to make decisions includes the ability to understand information germane to the decision, to deliberate, and to appreciate the consequences of choices.35 As with consent to treatment, a physician who accepts a patient's refusal for treatment has determined that the patient has adequate decision‐making capacity. However, physicians do not regularly document assessments of capacity in discharge AMA.3638
Writers on the subject suggest that patients who refuse low‐risk but high‐benefit treatments should be held to a higher standard of capacity.22 This notion could expose patients to incapacity determinations based on a physician's subjective assessment of net benefit or net harm. Rather, I contend that the standard itself should not vary. It should always require that the patient's level of cognitive function, insight, and deliberative abilities be appropriate to the decision at hand and sufficient for the patient to render an autonomous decision. The relative benefit of a treatment, in and of itself, is not relevant to the level of capacity required. Rather, net benefit is relevant to physicians' obligations to more carefully verify patients' understanding of the pertinent information and their perceptions of the consequences of their choices when declining high benefit/low harm treatments.
A capacitated patient's decision to leave AMA, however well informed, may nevertheless not be entirely voluntary. Voluntary decisions are those that are made with substantially free choice.39 Various controlling influences may impact a patient's decision to leave AMA, including social or emotional challenges such as a desperate concern about losing employment.9, 1315 Health professionals may view a patient's action under some controlling influences as meritorious, for example, leaving AMA to fulfill one's obligation to care for a demented spouse, whereas professionals may view acting on other controlling influences as contemptible, such as a leaving to satisfy a drug addiction. Physicians should view controlling influences, regardless of its moral valence, as affecting the voluntariness of a patient's decision. Moreover, physicians are positioned, through either support or coercion, to influence the degree to which a patient's decision about treatment is voluntary. To illustrate, physicians who support their substance abuse patients by providing adequate treatment of their withdrawal symptoms see lower rates of discharge AMA among these addicted patients.3, 5, 7 Regarding coercion, physicians of hospitalized patients may state their refusal to prescribe a beneficial but inferior outpatient treatment in order to compel their patients to accept standard inpatient treatment.
Physicians' Obligations in Discharge AMA
Broadly stated, physicians' obligations are to promote their patients' welfare and to respect their autonomy which is understood as serving the patient's self‐defined best interests including maintaining dignity.40 When discharging a patient AMA, physicians are sometimes limited in the ways in which they can fulfill these obligations. Physicians should attempt to promote informed decision‐making by discussing the likely harms of premature discharge, the likely harms and benefits of inpatient treatment, and alternatives to inpatient treatment, including medically inferior options where these exist.
Within this obligation to promote patients' welfare, physicians should render only objective and conservative assessments of harm and benefit. These assessments may directly reflect well‐established medical evidence (eg, use of statins in acute coronary syndromes), but may also be partly or even wholly dependent on clinical judgment (eg, interpreting and applying criteria for inpatient versus outpatient treatment of pneumonia). The process though which these clinical judgments are made is critical because it forms the basis of the medical advice that defines whether a patient's discharge is routine or AMA. Physicians, in addition to their obligation to objectively assess options for treatment, should be mindful of their fiduciary responsibilities in their position to influence patients' choices by the content, emphasis, and manner with which they communicate treatment options.4144
In addition to supporting patient autonomy through information and education, physicians can promote authenticity of choice by identifying patients' compelling reasons to leave AMA. Does the patient have a demented spouse alone at home? Does the patient have a cultural or religious requirement that they perceive cannot be met while hospitalized? Is the patient concerned about loss of employment? Does the patient have an important family obligation (eg, wedding, funeral) to fulfill? Ways in which these concerns can be mitigated should be explored, often through a multidisciplinary approach that may include social work and pastoral care.45
What are physicians' obligations to patients who are willing to accept only partial or inadequate treatment plans upon discharge AMA? Should physicians be complicit in treatments that are substandard, such as the writing of a prescription for an oral antibiotic for a patient whose clinical condition meets criteria for inpatient treatment of pneumonia? Should physicians be complicit in treatments that are somewhat effective, but clearly inadequate and potentially dangerous? An example of this is the providing of a prescription for an oral anti‐arrhythmic medication for a patient diagnosed in the emergency department (ED) with syncope from a tachyarrhythmia.
In considering these scenarios, physicians may need to focus primarily on their ethical obligations to not cause harms, because discharge AMA limits physicians' ability to actively promote patients' health.46 To illustrate, Patient C, a frequent abuser of alcohol, presents to the ED and is diagnosed with a pulmonary embolus. She wants only analgesic medication for her chest pain and states that she plans no outpatient follow up. What options should the ED physician consider? The physician should not discharge the patient with a prescription for warfarin, the use of which requires close and careful monitoring especially in the setting of alcohol consumption, because this treatment, along with this patient's social practices and disinclination for follow up, introduces risks similar in seriousness to her medical condition.47 Should the ED physician give her an injection of low molecular weight heparin before the patient exits? Although a single injection of heparin is not likely to meaningfully affect her disease course, there is little direct harm in providing it. However, one must also consider possible indirect harms. For example, the offer of heparin may harm Patient C if she construes it as a bona fide treatment alternative, thereby influencing her decision to leave AMA. In another scenario, Patient D presents to the ED with an upper gastrointestinal hemorrhage and orthostatic hypotension that responds quickly to intravenous fluids. The patient unconditionally refuses to undergo an endoscopy or to accept admission into the hospital. Should the ED physician administer a dose of intravenous proton pump inhibitor (PPI), and write a prescription for high‐dose oral PPI? Because the harms of PPIs are low and it may prevent rebleeding, providing such care does not violate the obligation to not cause disproportionate harms, and attends to the obligation to promote the patient's health. To summarize, physicians' obligations to provide treatment upon discharge AMA is determined by a complex evaluation of the likelihood and magnitude of each the harms and benefits associated with the outpatient treatment and the disease‐associated risks of morbidity and mortality. This assessment is outlined in Table 1.
Disease Risk | Treatment Efficacy | Treatment Risk | Ethical Obligation |
---|---|---|---|
High | High | Low | Clear obligation to treat |
High | Low | Low | Weak obligation to treat |
Low | High | Low | Weak obligation to treat |
High | High | High | No clear obligation to treat |
High | Low | High | No clear obligation to treat |
Low | High | High | No clear obligation to treat |
Low | Low | Low | No clear obligation to treat |
Low | Low | High | Clear obligation not to treat |
Do physicians have obligations for facilitating after‐care when discharging a patient AMA? The policy of some hospitals is that there are no such obligations.48 Arguably, providing resources for after‐care to these patients may benefit these patients with no additional medical risk, with the caveat that offering after‐care does not influence the patient's decision to leave AMA. Therefore, physicians are ethically obligated to offer this care. In fact, this is the practice of many physicians and consistent with a number of authorities in medicine and ethics.24, 36, 49, 50 There is little evidence to support the concern that providing patients with after‐care resources exposes physicians or institutions to greater legal liability. In fact the opposite may be true.51 For patients who habitually leave AMA and who repeatedly have not sought recommended after‐care, it should not be ethically obligatory for hospital staff to expend efforts to secure after‐care.
A corollary to physicians' obligations is the obligations of patients as users of health resources. There is an enormous literature on patients' rights, yet a relative dearth of discourse, let alone consensus, on patients' duties and responsibilities.52, 53 At a minimum, patients are obligated to honor commitments and to disclose relevant information in the interest of their personal health.54 Do patients discharged AMA have moral obligations to their fellow patients or to society in terms of responsible use of often costly and sometimes limited health resources? If so, what do these obligations require and which patients should be so obligated? These are important questions to consider, yet are beyond the scope of this discussion.
Summary and Conclusions
Clinicians caring for patients who seek discharge AMA are often faced with emotionally charged and time‐pressured treatment situations. These clinicians must weigh multiple considerations for the benefit of their patients, and maintain professional standards of clinical care. Clinicians presented with these situations should (1) evaluate patients' decision‐making capacity, (2) assess the degree to which their choices are influenced by controlling external influences and mitigate these factors where possible, and (3) encourage and facilitate after‐care (Table 2).
1. | Capacity | Assess patient's factual understanding, reasoning, and insight into consequences of decision |
2. | Voluntariness | Assess for controlling influences; physical, social, emotional, psychiatric, cultural |
3. | Mitigation | Multidisciplinary efforts to mitigate controlling influences |
4. | Treatment alternatives | Assess for medically appropriate outpatient treatment alternatives. (See table 1) |
5. | Aftercare | Encourage and facilitate after care |
Although discharge AMA accounts for only a small percentage of hospital discharges, its medical, emotional, and resource utilization consequences for patients as well as for physicians and hospitals is disproportionate. The clinical impacts of discharge AMA should be further investigated and specific strategies and interventions to mitigate its health effects should be validated.
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- Leaving hospital against medical advice among HIV‐positive patients.CMAJ.2002;167(6):633–637. , , , , , .
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- Discharges against medical advice: are race/ethnicity predictors?J Gen Intern Med.2006;21(9):955–960. , , .
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- Hospitalized patients with asthma who leave against medical advice: characteristics, reasons, and outcomes.J Allergy Clin Immunol.2007;19(4):924–929. , , , , .
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- HIV‐positive injection drug users who leave the hospital against medical advice: the mitigating role of methadone and social support.J Acquir Immune Defic Syndr.2004;35(1):56–59. , , , et al.
- Risk fctors for AMA discharge from VA inpatient alcoholism treatment programs.J Subst Abuse Treat.1994;11(3):239–245. , , , , .
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- Patients' rights and psychiatrists' duties: discharging patients against medical advice.Harv Rev Psychiatry.2003;11(6):333–343. , .
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- American College of Emergency Physicians Scientific Meeting. http://meetings.acep.org/NR/rdonlyres/3389C314–2395‐4FCE‐BD9A‐FAABFFC0DFB6/0/WE184.pdf. Accessed November 30,2007.
- Posttraumatic stress, nonadherence, and adverse outcome in survivors of a myocardial infarction.Psychosom Med.2004;66(4):521–526. , , , et al.
- The role of patient‐physician trust in moderating medication nonadherence due to cost pressures.Arch Intern Med.2005;165(15):1749–1755. , , , .
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- Compliance with antihypertensive therapy among elderly medicaid enrollees: the roles of age, gender, and race.Am J Public Health.1996;86(12):1805–1808. , , , , , .
- How well do patients report noncompliance with antihypertensive medications?: a comparison of self‐report versus filled prescriptions.Pharmacoepidemiol Drug Saf.2004;13(1):11–19. , , , , , .
- Variations in patients' adherence to medical recommendations: a quantitative review of 50 years of research.Med Care.2004;42(3):200–209. .
- Physicians' evaluations of patients' decisions to refuse oncological treatment.J Med Ethics.2005;31(3):131–136. , .
- Patient non‐compliance: deviance or reasoned decision‐making?Soc Sci Med.1992;34(5):507–513. , .
- Ten myths about decision‐making capacity.J Am Med Dir Assoc.2005;6(3 Suppl):S100–S104. , , , , .
- The MacCAT‐T: a clinical tool to assess patients' capacities to make treatment decisions.Psychiatr Serv.1997;48(11):1415–1419. , , .
- Emergency department discharges against medical advice.J Emerg Med.1992;10(4):513–516. , , .
- Discharges against medical advice: a community hospital's experience.Can J Rural Med.2004;9(3):148–153. , .
- Patient self discharge from the emergency department: who is at Risk?Emergency Med J.2005;22(7):499–501. , .
- Respect for Autonomy.Principles of Biomedical Ethics.Fifth ed.New York:Oxford University Press;2001. p.57–112. , .
- Ethics Manual: fifth edition.Ann Intern Med.2005;142(7):560–582. , .
- The effect of physician's explanations on patients' treatment preferences: five‐year survival data.Med Decis Making.1994;14(3):255–258. , .
- How the manner of presentation of data influences older patients in determining their treatment preferences.J Am Geriatr Soc.1993;41(3):223–228. , .
- The role of doctor's opinion in shared decision making: what does shared decision making really mean when considering invasive medical procedures?Health Expect.2005;8(2):97–102. , , , .
- The influence of treatment descriptions on advance medical directive decisions.J Am Geriatr Soc.1992;40(12):1255–1260. , , , .
- Patients who leave the hospital against medical advice: the role of the psychiatric consultant.Psychosomatics.1989;30(4):396–404. , , , .
- Nonmaleficence.Principles of Biomedical Ethics.Fifth ed.New York:Oxford University Press;2001:113–164. , .
- Untreated patients with pulmonary embolism. Outcome, clinical, and laboratory assessment.Chest.1995;107(4):931–935. , , .
- Memorial Hospital Pembroke, Pembroke Pines, Florida. Medical Staff Rules and Regulations. http://www.mhs.net/AboutUs/Physician_Bylaws/pdfs/mhp/MHP_Rules_and%20_Regs_2004.pdf. Accessed August 29,2008.
- Nonabandonment: a central obligation for physicians.Ann Intern Med.1995;122(5):368–374. , .
- Changing policy to reflect a concern for patients who sign out against medical advice.Am J Bioethic.2007;7(3):32–34. .
- Reducing risk with telephone follow‐up of patients who leave against medical advice of fail to complete an ED visit.J Emerg Nurs.2000;26(3):223–232. , , , , , .
- Moral obligations of patients: a clinical view.J Med Philos.2005;30(2):139–152. .
- Patients' responsibilities in medical ethics.Bioethics.2002;16(4):335–352. , .
- Patients' Responsibilities. In:Post SG, ed.Encyclopedia of Bioethics.Third ed.New York:Thompson Gale;2004. p.1990–1992. .
BACKGROUND
Discharges against medical advice (AMA) account for approximately 1% of discharges for general medical patients and up to 10% and 30% for patients afflicted with HIV disease and psychiatric disorders, respectively.17 Patients discharged AMA have higher rates of readmission, longer subsequent hospital stays, and worse health outcomes.3, 5, 811 Not unexpectedly, discharges AMA are associated with overall health costs of up to 50% greater than usual discharges.2
Patients who leave AMA are more likely to have poorer social supports, to abuse alcohol, heroin, and other substances, and often have weighty psychosocial or financial concerns.1218 They are also less likely to have an established relationship with a primary care physician.19 Although studies have found that rates of discharge AMA are higher among some ethnic minorities, one recent study suggests that other patient variables, such as level of income and type of insurance, may be more closely related.7, 20 Unfortunately, many patients who leave AMA have dual sources of distress: compelling personal concerns that fuel one's wish to leave and the illness that initially caused the patient to seek care.
Physicians are often distressed by the clinical and ethical challenges of discharges AMA. How should physicians manage their conflicted obligations to respect patients' choices and to prevent harms from befalling their patients? What are physicians' obligations to their patients who leave accepting only partial or inadequate treatment plans or no treatment at all? When should physicians call into question the decision‐making capacity of patients' who make seemingly unwise or clearly dangerous judgments to leave the hospital? In addition to these sorts of concerns, physicians who discharge patients AMA enjoy no definitive legal protection from the consequences of their patients' choices.2123 In fact, good clinical judgement and careful documentation provide the best liability protection.24
Clearly, discharges AMA are problematic for patients, stressful for physicians, and resource intensive for health facilities. Therefore, efforts to understand, better manage, and ultimately decrease discharges AMA will benefit all parties. Whereas the literature on discharge AMA tends to focus on psychiatric and substance abuse patients, this review examines the professional and ethical implications of discharge AMA more generally.
Does Discharge AMA Differ from Treatment Nonadherence Elsewhere in Health Care?
Patients' nonadherence to recommended treatment is often influenced by treatment side effects, costs, inconvenience, psychosocial burden, and the quality of the patient‐physician relationship. Not surprisingly, these same factors are often associated with discharge AMA.2528 In fact, nonadherence in discharge AMA and nonadherence elsewhere are fundamentally similar. Differences, where they exist, are often in the degree or imminency of health risk and in the ability of physicians to monitor the patient.
Discharges AMA tend to involve health risks that are more acute and more severe compared to general nonadherence. To illustrate, Patient A is diagnosed with the metabolic syndrome during an office visit. His physician recommends medical therapy, and the patient declines, thereby incurring a high risk of a cardiovascular event within the next 10 years. Patient B presents to the hospital with an acute coronary syndrome. He declines to remain in the hospital for an evaluation of ischemic burden despite a high risk of a myocardial infarction in the next few days. Patient A is motivated by the cost of medication and chooses to purchase his wife's medications, foregoing his own. Patient B is motivated by distress over leaving his frail wife alone at home and concerns of medical bills that he can not afford to pay. The patient in each of these cases is motivated by social and financial concerns. The consequence of each patient's choice is a higher risk of a cardiovascular event. A major difference is the temporal relationship between the decision to not accept treatment and the ensuing adverse event.
Of course, high‐risk situations are not exclusive to the inpatient setting. For example, a patient presents to a physician's office after having experienced substernal chest pain during the previous evening. The physician recommends hospitalization but the patient declines. Conversely, a hospitalized patient may pursue discharge AMA because the patient disagrees with the physician's stipulations for safe discharge plan including assistance at home. Yet, these concerns about custodial needs, if identified by the physician in an office setting, may not necessarily compel the physician to hospitalize the patient.
Another difference between discharge AMA and general nonadherence is that adherence is more readily and closely measured in the inpatient setting. Hospital‐based occurrences of nonadherence are immediately identified and addressed. To contrast, in the outpatient setting, adherence is far poorer with a 20% nonadherence rate considered to be good compliance.2931 Regardless of the setting for nonadherence, the variance between recommended and accepted treatments often stems from the fact that patients tend to make decisions based on values and broader interests whereas physicians tend to emphasize more circumscribed medical goals.32, 33
Informed and Voluntary Refusal of Treatment
A patient's intention to leave AMA may trigger physicians and other hospital staff to question the patient's decision‐making capacity.34 One's capacity to make decisions is specific to the decision at hand. For example, a patient with early dementia and an infected arterial insufficiency ulcer may not be able to fully appreciate all the consequences of premature discharge on her health, but may be able to reliably indicate her preferred health agent.
Clinicians commonly make implicit capacity determinations, and do so each time a patient's general consent for treatment is accepted. These assessments tend to be made more explicitly when the patient's decision appears to be grossly contrary to his or her welfare. Capacity to make decisions includes the ability to understand information germane to the decision, to deliberate, and to appreciate the consequences of choices.35 As with consent to treatment, a physician who accepts a patient's refusal for treatment has determined that the patient has adequate decision‐making capacity. However, physicians do not regularly document assessments of capacity in discharge AMA.3638
Writers on the subject suggest that patients who refuse low‐risk but high‐benefit treatments should be held to a higher standard of capacity.22 This notion could expose patients to incapacity determinations based on a physician's subjective assessment of net benefit or net harm. Rather, I contend that the standard itself should not vary. It should always require that the patient's level of cognitive function, insight, and deliberative abilities be appropriate to the decision at hand and sufficient for the patient to render an autonomous decision. The relative benefit of a treatment, in and of itself, is not relevant to the level of capacity required. Rather, net benefit is relevant to physicians' obligations to more carefully verify patients' understanding of the pertinent information and their perceptions of the consequences of their choices when declining high benefit/low harm treatments.
A capacitated patient's decision to leave AMA, however well informed, may nevertheless not be entirely voluntary. Voluntary decisions are those that are made with substantially free choice.39 Various controlling influences may impact a patient's decision to leave AMA, including social or emotional challenges such as a desperate concern about losing employment.9, 1315 Health professionals may view a patient's action under some controlling influences as meritorious, for example, leaving AMA to fulfill one's obligation to care for a demented spouse, whereas professionals may view acting on other controlling influences as contemptible, such as a leaving to satisfy a drug addiction. Physicians should view controlling influences, regardless of its moral valence, as affecting the voluntariness of a patient's decision. Moreover, physicians are positioned, through either support or coercion, to influence the degree to which a patient's decision about treatment is voluntary. To illustrate, physicians who support their substance abuse patients by providing adequate treatment of their withdrawal symptoms see lower rates of discharge AMA among these addicted patients.3, 5, 7 Regarding coercion, physicians of hospitalized patients may state their refusal to prescribe a beneficial but inferior outpatient treatment in order to compel their patients to accept standard inpatient treatment.
Physicians' Obligations in Discharge AMA
Broadly stated, physicians' obligations are to promote their patients' welfare and to respect their autonomy which is understood as serving the patient's self‐defined best interests including maintaining dignity.40 When discharging a patient AMA, physicians are sometimes limited in the ways in which they can fulfill these obligations. Physicians should attempt to promote informed decision‐making by discussing the likely harms of premature discharge, the likely harms and benefits of inpatient treatment, and alternatives to inpatient treatment, including medically inferior options where these exist.
Within this obligation to promote patients' welfare, physicians should render only objective and conservative assessments of harm and benefit. These assessments may directly reflect well‐established medical evidence (eg, use of statins in acute coronary syndromes), but may also be partly or even wholly dependent on clinical judgment (eg, interpreting and applying criteria for inpatient versus outpatient treatment of pneumonia). The process though which these clinical judgments are made is critical because it forms the basis of the medical advice that defines whether a patient's discharge is routine or AMA. Physicians, in addition to their obligation to objectively assess options for treatment, should be mindful of their fiduciary responsibilities in their position to influence patients' choices by the content, emphasis, and manner with which they communicate treatment options.4144
In addition to supporting patient autonomy through information and education, physicians can promote authenticity of choice by identifying patients' compelling reasons to leave AMA. Does the patient have a demented spouse alone at home? Does the patient have a cultural or religious requirement that they perceive cannot be met while hospitalized? Is the patient concerned about loss of employment? Does the patient have an important family obligation (eg, wedding, funeral) to fulfill? Ways in which these concerns can be mitigated should be explored, often through a multidisciplinary approach that may include social work and pastoral care.45
What are physicians' obligations to patients who are willing to accept only partial or inadequate treatment plans upon discharge AMA? Should physicians be complicit in treatments that are substandard, such as the writing of a prescription for an oral antibiotic for a patient whose clinical condition meets criteria for inpatient treatment of pneumonia? Should physicians be complicit in treatments that are somewhat effective, but clearly inadequate and potentially dangerous? An example of this is the providing of a prescription for an oral anti‐arrhythmic medication for a patient diagnosed in the emergency department (ED) with syncope from a tachyarrhythmia.
In considering these scenarios, physicians may need to focus primarily on their ethical obligations to not cause harms, because discharge AMA limits physicians' ability to actively promote patients' health.46 To illustrate, Patient C, a frequent abuser of alcohol, presents to the ED and is diagnosed with a pulmonary embolus. She wants only analgesic medication for her chest pain and states that she plans no outpatient follow up. What options should the ED physician consider? The physician should not discharge the patient with a prescription for warfarin, the use of which requires close and careful monitoring especially in the setting of alcohol consumption, because this treatment, along with this patient's social practices and disinclination for follow up, introduces risks similar in seriousness to her medical condition.47 Should the ED physician give her an injection of low molecular weight heparin before the patient exits? Although a single injection of heparin is not likely to meaningfully affect her disease course, there is little direct harm in providing it. However, one must also consider possible indirect harms. For example, the offer of heparin may harm Patient C if she construes it as a bona fide treatment alternative, thereby influencing her decision to leave AMA. In another scenario, Patient D presents to the ED with an upper gastrointestinal hemorrhage and orthostatic hypotension that responds quickly to intravenous fluids. The patient unconditionally refuses to undergo an endoscopy or to accept admission into the hospital. Should the ED physician administer a dose of intravenous proton pump inhibitor (PPI), and write a prescription for high‐dose oral PPI? Because the harms of PPIs are low and it may prevent rebleeding, providing such care does not violate the obligation to not cause disproportionate harms, and attends to the obligation to promote the patient's health. To summarize, physicians' obligations to provide treatment upon discharge AMA is determined by a complex evaluation of the likelihood and magnitude of each the harms and benefits associated with the outpatient treatment and the disease‐associated risks of morbidity and mortality. This assessment is outlined in Table 1.
Disease Risk | Treatment Efficacy | Treatment Risk | Ethical Obligation |
---|---|---|---|
High | High | Low | Clear obligation to treat |
High | Low | Low | Weak obligation to treat |
Low | High | Low | Weak obligation to treat |
High | High | High | No clear obligation to treat |
High | Low | High | No clear obligation to treat |
Low | High | High | No clear obligation to treat |
Low | Low | Low | No clear obligation to treat |
Low | Low | High | Clear obligation not to treat |
Do physicians have obligations for facilitating after‐care when discharging a patient AMA? The policy of some hospitals is that there are no such obligations.48 Arguably, providing resources for after‐care to these patients may benefit these patients with no additional medical risk, with the caveat that offering after‐care does not influence the patient's decision to leave AMA. Therefore, physicians are ethically obligated to offer this care. In fact, this is the practice of many physicians and consistent with a number of authorities in medicine and ethics.24, 36, 49, 50 There is little evidence to support the concern that providing patients with after‐care resources exposes physicians or institutions to greater legal liability. In fact the opposite may be true.51 For patients who habitually leave AMA and who repeatedly have not sought recommended after‐care, it should not be ethically obligatory for hospital staff to expend efforts to secure after‐care.
A corollary to physicians' obligations is the obligations of patients as users of health resources. There is an enormous literature on patients' rights, yet a relative dearth of discourse, let alone consensus, on patients' duties and responsibilities.52, 53 At a minimum, patients are obligated to honor commitments and to disclose relevant information in the interest of their personal health.54 Do patients discharged AMA have moral obligations to their fellow patients or to society in terms of responsible use of often costly and sometimes limited health resources? If so, what do these obligations require and which patients should be so obligated? These are important questions to consider, yet are beyond the scope of this discussion.
Summary and Conclusions
Clinicians caring for patients who seek discharge AMA are often faced with emotionally charged and time‐pressured treatment situations. These clinicians must weigh multiple considerations for the benefit of their patients, and maintain professional standards of clinical care. Clinicians presented with these situations should (1) evaluate patients' decision‐making capacity, (2) assess the degree to which their choices are influenced by controlling external influences and mitigate these factors where possible, and (3) encourage and facilitate after‐care (Table 2).
1. | Capacity | Assess patient's factual understanding, reasoning, and insight into consequences of decision |
2. | Voluntariness | Assess for controlling influences; physical, social, emotional, psychiatric, cultural |
3. | Mitigation | Multidisciplinary efforts to mitigate controlling influences |
4. | Treatment alternatives | Assess for medically appropriate outpatient treatment alternatives. (See table 1) |
5. | Aftercare | Encourage and facilitate after care |
Although discharge AMA accounts for only a small percentage of hospital discharges, its medical, emotional, and resource utilization consequences for patients as well as for physicians and hospitals is disproportionate. The clinical impacts of discharge AMA should be further investigated and specific strategies and interventions to mitigate its health effects should be validated.
BACKGROUND
Discharges against medical advice (AMA) account for approximately 1% of discharges for general medical patients and up to 10% and 30% for patients afflicted with HIV disease and psychiatric disorders, respectively.17 Patients discharged AMA have higher rates of readmission, longer subsequent hospital stays, and worse health outcomes.3, 5, 811 Not unexpectedly, discharges AMA are associated with overall health costs of up to 50% greater than usual discharges.2
Patients who leave AMA are more likely to have poorer social supports, to abuse alcohol, heroin, and other substances, and often have weighty psychosocial or financial concerns.1218 They are also less likely to have an established relationship with a primary care physician.19 Although studies have found that rates of discharge AMA are higher among some ethnic minorities, one recent study suggests that other patient variables, such as level of income and type of insurance, may be more closely related.7, 20 Unfortunately, many patients who leave AMA have dual sources of distress: compelling personal concerns that fuel one's wish to leave and the illness that initially caused the patient to seek care.
Physicians are often distressed by the clinical and ethical challenges of discharges AMA. How should physicians manage their conflicted obligations to respect patients' choices and to prevent harms from befalling their patients? What are physicians' obligations to their patients who leave accepting only partial or inadequate treatment plans or no treatment at all? When should physicians call into question the decision‐making capacity of patients' who make seemingly unwise or clearly dangerous judgments to leave the hospital? In addition to these sorts of concerns, physicians who discharge patients AMA enjoy no definitive legal protection from the consequences of their patients' choices.2123 In fact, good clinical judgement and careful documentation provide the best liability protection.24
Clearly, discharges AMA are problematic for patients, stressful for physicians, and resource intensive for health facilities. Therefore, efforts to understand, better manage, and ultimately decrease discharges AMA will benefit all parties. Whereas the literature on discharge AMA tends to focus on psychiatric and substance abuse patients, this review examines the professional and ethical implications of discharge AMA more generally.
Does Discharge AMA Differ from Treatment Nonadherence Elsewhere in Health Care?
Patients' nonadherence to recommended treatment is often influenced by treatment side effects, costs, inconvenience, psychosocial burden, and the quality of the patient‐physician relationship. Not surprisingly, these same factors are often associated with discharge AMA.2528 In fact, nonadherence in discharge AMA and nonadherence elsewhere are fundamentally similar. Differences, where they exist, are often in the degree or imminency of health risk and in the ability of physicians to monitor the patient.
Discharges AMA tend to involve health risks that are more acute and more severe compared to general nonadherence. To illustrate, Patient A is diagnosed with the metabolic syndrome during an office visit. His physician recommends medical therapy, and the patient declines, thereby incurring a high risk of a cardiovascular event within the next 10 years. Patient B presents to the hospital with an acute coronary syndrome. He declines to remain in the hospital for an evaluation of ischemic burden despite a high risk of a myocardial infarction in the next few days. Patient A is motivated by the cost of medication and chooses to purchase his wife's medications, foregoing his own. Patient B is motivated by distress over leaving his frail wife alone at home and concerns of medical bills that he can not afford to pay. The patient in each of these cases is motivated by social and financial concerns. The consequence of each patient's choice is a higher risk of a cardiovascular event. A major difference is the temporal relationship between the decision to not accept treatment and the ensuing adverse event.
Of course, high‐risk situations are not exclusive to the inpatient setting. For example, a patient presents to a physician's office after having experienced substernal chest pain during the previous evening. The physician recommends hospitalization but the patient declines. Conversely, a hospitalized patient may pursue discharge AMA because the patient disagrees with the physician's stipulations for safe discharge plan including assistance at home. Yet, these concerns about custodial needs, if identified by the physician in an office setting, may not necessarily compel the physician to hospitalize the patient.
Another difference between discharge AMA and general nonadherence is that adherence is more readily and closely measured in the inpatient setting. Hospital‐based occurrences of nonadherence are immediately identified and addressed. To contrast, in the outpatient setting, adherence is far poorer with a 20% nonadherence rate considered to be good compliance.2931 Regardless of the setting for nonadherence, the variance between recommended and accepted treatments often stems from the fact that patients tend to make decisions based on values and broader interests whereas physicians tend to emphasize more circumscribed medical goals.32, 33
Informed and Voluntary Refusal of Treatment
A patient's intention to leave AMA may trigger physicians and other hospital staff to question the patient's decision‐making capacity.34 One's capacity to make decisions is specific to the decision at hand. For example, a patient with early dementia and an infected arterial insufficiency ulcer may not be able to fully appreciate all the consequences of premature discharge on her health, but may be able to reliably indicate her preferred health agent.
Clinicians commonly make implicit capacity determinations, and do so each time a patient's general consent for treatment is accepted. These assessments tend to be made more explicitly when the patient's decision appears to be grossly contrary to his or her welfare. Capacity to make decisions includes the ability to understand information germane to the decision, to deliberate, and to appreciate the consequences of choices.35 As with consent to treatment, a physician who accepts a patient's refusal for treatment has determined that the patient has adequate decision‐making capacity. However, physicians do not regularly document assessments of capacity in discharge AMA.3638
Writers on the subject suggest that patients who refuse low‐risk but high‐benefit treatments should be held to a higher standard of capacity.22 This notion could expose patients to incapacity determinations based on a physician's subjective assessment of net benefit or net harm. Rather, I contend that the standard itself should not vary. It should always require that the patient's level of cognitive function, insight, and deliberative abilities be appropriate to the decision at hand and sufficient for the patient to render an autonomous decision. The relative benefit of a treatment, in and of itself, is not relevant to the level of capacity required. Rather, net benefit is relevant to physicians' obligations to more carefully verify patients' understanding of the pertinent information and their perceptions of the consequences of their choices when declining high benefit/low harm treatments.
A capacitated patient's decision to leave AMA, however well informed, may nevertheless not be entirely voluntary. Voluntary decisions are those that are made with substantially free choice.39 Various controlling influences may impact a patient's decision to leave AMA, including social or emotional challenges such as a desperate concern about losing employment.9, 1315 Health professionals may view a patient's action under some controlling influences as meritorious, for example, leaving AMA to fulfill one's obligation to care for a demented spouse, whereas professionals may view acting on other controlling influences as contemptible, such as a leaving to satisfy a drug addiction. Physicians should view controlling influences, regardless of its moral valence, as affecting the voluntariness of a patient's decision. Moreover, physicians are positioned, through either support or coercion, to influence the degree to which a patient's decision about treatment is voluntary. To illustrate, physicians who support their substance abuse patients by providing adequate treatment of their withdrawal symptoms see lower rates of discharge AMA among these addicted patients.3, 5, 7 Regarding coercion, physicians of hospitalized patients may state their refusal to prescribe a beneficial but inferior outpatient treatment in order to compel their patients to accept standard inpatient treatment.
Physicians' Obligations in Discharge AMA
Broadly stated, physicians' obligations are to promote their patients' welfare and to respect their autonomy which is understood as serving the patient's self‐defined best interests including maintaining dignity.40 When discharging a patient AMA, physicians are sometimes limited in the ways in which they can fulfill these obligations. Physicians should attempt to promote informed decision‐making by discussing the likely harms of premature discharge, the likely harms and benefits of inpatient treatment, and alternatives to inpatient treatment, including medically inferior options where these exist.
Within this obligation to promote patients' welfare, physicians should render only objective and conservative assessments of harm and benefit. These assessments may directly reflect well‐established medical evidence (eg, use of statins in acute coronary syndromes), but may also be partly or even wholly dependent on clinical judgment (eg, interpreting and applying criteria for inpatient versus outpatient treatment of pneumonia). The process though which these clinical judgments are made is critical because it forms the basis of the medical advice that defines whether a patient's discharge is routine or AMA. Physicians, in addition to their obligation to objectively assess options for treatment, should be mindful of their fiduciary responsibilities in their position to influence patients' choices by the content, emphasis, and manner with which they communicate treatment options.4144
In addition to supporting patient autonomy through information and education, physicians can promote authenticity of choice by identifying patients' compelling reasons to leave AMA. Does the patient have a demented spouse alone at home? Does the patient have a cultural or religious requirement that they perceive cannot be met while hospitalized? Is the patient concerned about loss of employment? Does the patient have an important family obligation (eg, wedding, funeral) to fulfill? Ways in which these concerns can be mitigated should be explored, often through a multidisciplinary approach that may include social work and pastoral care.45
What are physicians' obligations to patients who are willing to accept only partial or inadequate treatment plans upon discharge AMA? Should physicians be complicit in treatments that are substandard, such as the writing of a prescription for an oral antibiotic for a patient whose clinical condition meets criteria for inpatient treatment of pneumonia? Should physicians be complicit in treatments that are somewhat effective, but clearly inadequate and potentially dangerous? An example of this is the providing of a prescription for an oral anti‐arrhythmic medication for a patient diagnosed in the emergency department (ED) with syncope from a tachyarrhythmia.
In considering these scenarios, physicians may need to focus primarily on their ethical obligations to not cause harms, because discharge AMA limits physicians' ability to actively promote patients' health.46 To illustrate, Patient C, a frequent abuser of alcohol, presents to the ED and is diagnosed with a pulmonary embolus. She wants only analgesic medication for her chest pain and states that she plans no outpatient follow up. What options should the ED physician consider? The physician should not discharge the patient with a prescription for warfarin, the use of which requires close and careful monitoring especially in the setting of alcohol consumption, because this treatment, along with this patient's social practices and disinclination for follow up, introduces risks similar in seriousness to her medical condition.47 Should the ED physician give her an injection of low molecular weight heparin before the patient exits? Although a single injection of heparin is not likely to meaningfully affect her disease course, there is little direct harm in providing it. However, one must also consider possible indirect harms. For example, the offer of heparin may harm Patient C if she construes it as a bona fide treatment alternative, thereby influencing her decision to leave AMA. In another scenario, Patient D presents to the ED with an upper gastrointestinal hemorrhage and orthostatic hypotension that responds quickly to intravenous fluids. The patient unconditionally refuses to undergo an endoscopy or to accept admission into the hospital. Should the ED physician administer a dose of intravenous proton pump inhibitor (PPI), and write a prescription for high‐dose oral PPI? Because the harms of PPIs are low and it may prevent rebleeding, providing such care does not violate the obligation to not cause disproportionate harms, and attends to the obligation to promote the patient's health. To summarize, physicians' obligations to provide treatment upon discharge AMA is determined by a complex evaluation of the likelihood and magnitude of each the harms and benefits associated with the outpatient treatment and the disease‐associated risks of morbidity and mortality. This assessment is outlined in Table 1.
Disease Risk | Treatment Efficacy | Treatment Risk | Ethical Obligation |
---|---|---|---|
High | High | Low | Clear obligation to treat |
High | Low | Low | Weak obligation to treat |
Low | High | Low | Weak obligation to treat |
High | High | High | No clear obligation to treat |
High | Low | High | No clear obligation to treat |
Low | High | High | No clear obligation to treat |
Low | Low | Low | No clear obligation to treat |
Low | Low | High | Clear obligation not to treat |
Do physicians have obligations for facilitating after‐care when discharging a patient AMA? The policy of some hospitals is that there are no such obligations.48 Arguably, providing resources for after‐care to these patients may benefit these patients with no additional medical risk, with the caveat that offering after‐care does not influence the patient's decision to leave AMA. Therefore, physicians are ethically obligated to offer this care. In fact, this is the practice of many physicians and consistent with a number of authorities in medicine and ethics.24, 36, 49, 50 There is little evidence to support the concern that providing patients with after‐care resources exposes physicians or institutions to greater legal liability. In fact the opposite may be true.51 For patients who habitually leave AMA and who repeatedly have not sought recommended after‐care, it should not be ethically obligatory for hospital staff to expend efforts to secure after‐care.
A corollary to physicians' obligations is the obligations of patients as users of health resources. There is an enormous literature on patients' rights, yet a relative dearth of discourse, let alone consensus, on patients' duties and responsibilities.52, 53 At a minimum, patients are obligated to honor commitments and to disclose relevant information in the interest of their personal health.54 Do patients discharged AMA have moral obligations to their fellow patients or to society in terms of responsible use of often costly and sometimes limited health resources? If so, what do these obligations require and which patients should be so obligated? These are important questions to consider, yet are beyond the scope of this discussion.
Summary and Conclusions
Clinicians caring for patients who seek discharge AMA are often faced with emotionally charged and time‐pressured treatment situations. These clinicians must weigh multiple considerations for the benefit of their patients, and maintain professional standards of clinical care. Clinicians presented with these situations should (1) evaluate patients' decision‐making capacity, (2) assess the degree to which their choices are influenced by controlling external influences and mitigate these factors where possible, and (3) encourage and facilitate after‐care (Table 2).
1. | Capacity | Assess patient's factual understanding, reasoning, and insight into consequences of decision |
2. | Voluntariness | Assess for controlling influences; physical, social, emotional, psychiatric, cultural |
3. | Mitigation | Multidisciplinary efforts to mitigate controlling influences |
4. | Treatment alternatives | Assess for medically appropriate outpatient treatment alternatives. (See table 1) |
5. | Aftercare | Encourage and facilitate after care |
Although discharge AMA accounts for only a small percentage of hospital discharges, its medical, emotional, and resource utilization consequences for patients as well as for physicians and hospitals is disproportionate. The clinical impacts of discharge AMA should be further investigated and specific strategies and interventions to mitigate its health effects should be validated.
- Factors associated with patients who leave acute‐care hospitals against medical advice.Am J Public Health.2007;97(12):2204–2208. , , .
- Discharge against medical advice: sociodemographic, clinical and financial perspectives.Int J Clin Pract.2002;56(5):325–327. .
- Leaving hospital against medical advice among HIV‐positive patients.CMAJ.2002;167(6):633–637. , , , , , .
- Leaving hospital against medical advice.J Qual Clin Pract.1996;16(3):157–164. , , .
- Predictors and outcome of discharge against medical advice from the psychiatric units of a general hospital.Psychiatr Serv.1998;49(9):1187–1192. , , , , , .
- Discharges against medical advice at regional acute care hospitals.Am J Public Health.1991;81(2):212–215. , .
- Discharges against medical advice: are race/ethnicity predictors?J Gen Intern Med.2006;21(9):955–960. , , .
- What happens to patients who leave hospital against medical advice?CMAJ.2003;168(4):417–420. , , , , .
- Hospitalized patients with asthma who leave against medical advice: characteristics, reasons, and outcomes.J Allergy Clin Immunol.2007;19(4):924–929. , , , , .
- Post partum discharge against medical advice: who leaves and does it matter?Matern Child Health J.2007;11(5):431–436. , , .
- Uncompleted emergency department care: patients who leave against medical advice.Acad Emerg Med.2007;14(10):870–876. , , , , .
- HIV‐positive injection drug users who leave the hospital against medical advice: the mitigating role of methadone and social support.J Acquir Immune Defic Syndr.2004;35(1):56–59. , , , et al.
- Risk fctors for AMA discharge from VA inpatient alcoholism treatment programs.J Subst Abuse Treat.1994;11(3):239–245. , , , , .
- Interventions to improve the AMA‐discharge rate for opiate‐addicted patients.J Psychosoc Nurs Ment Health Serv.1994;32(8):36–40. , .
- Why patients sign out against medical advice (AMA): factors motivating patients to sign out AMA.Am J Drug Alcohol Abuse.2004;30(2):489–493. , , , .
- Diagnostic correlates of discharge against medical advice.Arch Gen Psychiatry.1977;34(2):153–155. , .
- Who leaves against medical advice?J Gen Intern Med.1995;10(7):403–405. , , .
- Hospital discharge against medical advice after myocardial infarction: deaths and readmissions.Am J Med.2007;120(12):104–153. , , .
- Patients discharged against medical advice from a general medicine service.J Gen Intern Med.1998;13(8):568–571. , , .
- Race and hospital discharge against medical advice.J Natl Med Assoc.1996;88(10):658–660. , .
- An examination of whether discharging patients against medical advice protects physicians from malpractice charges.Psychiatr Serv.2000;51(7):899–902. , , .
- Patients' rights and psychiatrists' duties: discharging patients against medical advice.Harv Rev Psychiatry.2003;11(6):333–343. , .
- Does identifying a discharge as “against medical advice” confer legal protection?J Fam Pract.2000;49(3):224–227. , , .
- American College of Emergency Physicians Scientific Meeting. http://meetings.acep.org/NR/rdonlyres/3389C314–2395‐4FCE‐BD9A‐FAABFFC0DFB6/0/WE184.pdf. Accessed November 30,2007.
- Posttraumatic stress, nonadherence, and adverse outcome in survivors of a myocardial infarction.Psychosom Med.2004;66(4):521–526. , , , et al.
- The role of patient‐physician trust in moderating medication nonadherence due to cost pressures.Arch Intern Med.2005;165(15):1749–1755. , , , .
- Factors associated with medication nonadherence in patients with COPD.Chest.2005;128(5):3198–3204. , , , .
- Medication nonadherence and substance abuse in psychotic disorders: impact of depressive symptoms and social stability.J Nerv Ment Dis.2005;193(10):673–679. , , , .
- Compliance with antihypertensive therapy among elderly medicaid enrollees: the roles of age, gender, and race.Am J Public Health.1996;86(12):1805–1808. , , , , , .
- How well do patients report noncompliance with antihypertensive medications?: a comparison of self‐report versus filled prescriptions.Pharmacoepidemiol Drug Saf.2004;13(1):11–19. , , , , , .
- Variations in patients' adherence to medical recommendations: a quantitative review of 50 years of research.Med Care.2004;42(3):200–209. .
- Physicians' evaluations of patients' decisions to refuse oncological treatment.J Med Ethics.2005;31(3):131–136. , .
- Patient non‐compliance: deviance or reasoned decision‐making?Soc Sci Med.1992;34(5):507–513. , .
- Ten myths about decision‐making capacity.J Am Med Dir Assoc.2005;6(3 Suppl):S100–S104. , , , , .
- The MacCAT‐T: a clinical tool to assess patients' capacities to make treatment decisions.Psychiatr Serv.1997;48(11):1415–1419. , , .
- Emergency department discharges against medical advice.J Emerg Med.1992;10(4):513–516. , , .
- Discharges against medical advice: a community hospital's experience.Can J Rural Med.2004;9(3):148–153. , .
- Patient self discharge from the emergency department: who is at Risk?Emergency Med J.2005;22(7):499–501. , .
- Respect for Autonomy.Principles of Biomedical Ethics.Fifth ed.New York:Oxford University Press;2001. p.57–112. , .
- Ethics Manual: fifth edition.Ann Intern Med.2005;142(7):560–582. , .
- The effect of physician's explanations on patients' treatment preferences: five‐year survival data.Med Decis Making.1994;14(3):255–258. , .
- How the manner of presentation of data influences older patients in determining their treatment preferences.J Am Geriatr Soc.1993;41(3):223–228. , .
- The role of doctor's opinion in shared decision making: what does shared decision making really mean when considering invasive medical procedures?Health Expect.2005;8(2):97–102. , , , .
- The influence of treatment descriptions on advance medical directive decisions.J Am Geriatr Soc.1992;40(12):1255–1260. , , , .
- Patients who leave the hospital against medical advice: the role of the psychiatric consultant.Psychosomatics.1989;30(4):396–404. , , , .
- Nonmaleficence.Principles of Biomedical Ethics.Fifth ed.New York:Oxford University Press;2001:113–164. , .
- Untreated patients with pulmonary embolism. Outcome, clinical, and laboratory assessment.Chest.1995;107(4):931–935. , , .
- Memorial Hospital Pembroke, Pembroke Pines, Florida. Medical Staff Rules and Regulations. http://www.mhs.net/AboutUs/Physician_Bylaws/pdfs/mhp/MHP_Rules_and%20_Regs_2004.pdf. Accessed August 29,2008.
- Nonabandonment: a central obligation for physicians.Ann Intern Med.1995;122(5):368–374. , .
- Changing policy to reflect a concern for patients who sign out against medical advice.Am J Bioethic.2007;7(3):32–34. .
- Reducing risk with telephone follow‐up of patients who leave against medical advice of fail to complete an ED visit.J Emerg Nurs.2000;26(3):223–232. , , , , , .
- Moral obligations of patients: a clinical view.J Med Philos.2005;30(2):139–152. .
- Patients' responsibilities in medical ethics.Bioethics.2002;16(4):335–352. , .
- Patients' Responsibilities. In:Post SG, ed.Encyclopedia of Bioethics.Third ed.New York:Thompson Gale;2004. p.1990–1992. .
- Factors associated with patients who leave acute‐care hospitals against medical advice.Am J Public Health.2007;97(12):2204–2208. , , .
- Discharge against medical advice: sociodemographic, clinical and financial perspectives.Int J Clin Pract.2002;56(5):325–327. .
- Leaving hospital against medical advice among HIV‐positive patients.CMAJ.2002;167(6):633–637. , , , , , .
- Leaving hospital against medical advice.J Qual Clin Pract.1996;16(3):157–164. , , .
- Predictors and outcome of discharge against medical advice from the psychiatric units of a general hospital.Psychiatr Serv.1998;49(9):1187–1192. , , , , , .
- Discharges against medical advice at regional acute care hospitals.Am J Public Health.1991;81(2):212–215. , .
- Discharges against medical advice: are race/ethnicity predictors?J Gen Intern Med.2006;21(9):955–960. , , .
- What happens to patients who leave hospital against medical advice?CMAJ.2003;168(4):417–420. , , , , .
- Hospitalized patients with asthma who leave against medical advice: characteristics, reasons, and outcomes.J Allergy Clin Immunol.2007;19(4):924–929. , , , , .
- Post partum discharge against medical advice: who leaves and does it matter?Matern Child Health J.2007;11(5):431–436. , , .
- Uncompleted emergency department care: patients who leave against medical advice.Acad Emerg Med.2007;14(10):870–876. , , , , .
- HIV‐positive injection drug users who leave the hospital against medical advice: the mitigating role of methadone and social support.J Acquir Immune Defic Syndr.2004;35(1):56–59. , , , et al.
- Risk fctors for AMA discharge from VA inpatient alcoholism treatment programs.J Subst Abuse Treat.1994;11(3):239–245. , , , , .
- Interventions to improve the AMA‐discharge rate for opiate‐addicted patients.J Psychosoc Nurs Ment Health Serv.1994;32(8):36–40. , .
- Why patients sign out against medical advice (AMA): factors motivating patients to sign out AMA.Am J Drug Alcohol Abuse.2004;30(2):489–493. , , , .
- Diagnostic correlates of discharge against medical advice.Arch Gen Psychiatry.1977;34(2):153–155. , .
- Who leaves against medical advice?J Gen Intern Med.1995;10(7):403–405. , , .
- Hospital discharge against medical advice after myocardial infarction: deaths and readmissions.Am J Med.2007;120(12):104–153. , , .
- Patients discharged against medical advice from a general medicine service.J Gen Intern Med.1998;13(8):568–571. , , .
- Race and hospital discharge against medical advice.J Natl Med Assoc.1996;88(10):658–660. , .
- An examination of whether discharging patients against medical advice protects physicians from malpractice charges.Psychiatr Serv.2000;51(7):899–902. , , .
- Patients' rights and psychiatrists' duties: discharging patients against medical advice.Harv Rev Psychiatry.2003;11(6):333–343. , .
- Does identifying a discharge as “against medical advice” confer legal protection?J Fam Pract.2000;49(3):224–227. , , .
- American College of Emergency Physicians Scientific Meeting. http://meetings.acep.org/NR/rdonlyres/3389C314–2395‐4FCE‐BD9A‐FAABFFC0DFB6/0/WE184.pdf. Accessed November 30,2007.
- Posttraumatic stress, nonadherence, and adverse outcome in survivors of a myocardial infarction.Psychosom Med.2004;66(4):521–526. , , , et al.
- The role of patient‐physician trust in moderating medication nonadherence due to cost pressures.Arch Intern Med.2005;165(15):1749–1755. , , , .
- Factors associated with medication nonadherence in patients with COPD.Chest.2005;128(5):3198–3204. , , , .
- Medication nonadherence and substance abuse in psychotic disorders: impact of depressive symptoms and social stability.J Nerv Ment Dis.2005;193(10):673–679. , , , .
- Compliance with antihypertensive therapy among elderly medicaid enrollees: the roles of age, gender, and race.Am J Public Health.1996;86(12):1805–1808. , , , , , .
- How well do patients report noncompliance with antihypertensive medications?: a comparison of self‐report versus filled prescriptions.Pharmacoepidemiol Drug Saf.2004;13(1):11–19. , , , , , .
- Variations in patients' adherence to medical recommendations: a quantitative review of 50 years of research.Med Care.2004;42(3):200–209. .
- Physicians' evaluations of patients' decisions to refuse oncological treatment.J Med Ethics.2005;31(3):131–136. , .
- Patient non‐compliance: deviance or reasoned decision‐making?Soc Sci Med.1992;34(5):507–513. , .
- Ten myths about decision‐making capacity.J Am Med Dir Assoc.2005;6(3 Suppl):S100–S104. , , , , .
- The MacCAT‐T: a clinical tool to assess patients' capacities to make treatment decisions.Psychiatr Serv.1997;48(11):1415–1419. , , .
- Emergency department discharges against medical advice.J Emerg Med.1992;10(4):513–516. , , .
- Discharges against medical advice: a community hospital's experience.Can J Rural Med.2004;9(3):148–153. , .
- Patient self discharge from the emergency department: who is at Risk?Emergency Med J.2005;22(7):499–501. , .
- Respect for Autonomy.Principles of Biomedical Ethics.Fifth ed.New York:Oxford University Press;2001. p.57–112. , .
- Ethics Manual: fifth edition.Ann Intern Med.2005;142(7):560–582. , .
- The effect of physician's explanations on patients' treatment preferences: five‐year survival data.Med Decis Making.1994;14(3):255–258. , .
- How the manner of presentation of data influences older patients in determining their treatment preferences.J Am Geriatr Soc.1993;41(3):223–228. , .
- The role of doctor's opinion in shared decision making: what does shared decision making really mean when considering invasive medical procedures?Health Expect.2005;8(2):97–102. , , , .
- The influence of treatment descriptions on advance medical directive decisions.J Am Geriatr Soc.1992;40(12):1255–1260. , , , .
- Patients who leave the hospital against medical advice: the role of the psychiatric consultant.Psychosomatics.1989;30(4):396–404. , , , .
- Nonmaleficence.Principles of Biomedical Ethics.Fifth ed.New York:Oxford University Press;2001:113–164. , .
- Untreated patients with pulmonary embolism. Outcome, clinical, and laboratory assessment.Chest.1995;107(4):931–935. , , .
- Memorial Hospital Pembroke, Pembroke Pines, Florida. Medical Staff Rules and Regulations. http://www.mhs.net/AboutUs/Physician_Bylaws/pdfs/mhp/MHP_Rules_and%20_Regs_2004.pdf. Accessed August 29,2008.
- Nonabandonment: a central obligation for physicians.Ann Intern Med.1995;122(5):368–374. , .
- Changing policy to reflect a concern for patients who sign out against medical advice.Am J Bioethic.2007;7(3):32–34. .
- Reducing risk with telephone follow‐up of patients who leave against medical advice of fail to complete an ED visit.J Emerg Nurs.2000;26(3):223–232. , , , , , .
- Moral obligations of patients: a clinical view.J Med Philos.2005;30(2):139–152. .
- Patients' responsibilities in medical ethics.Bioethics.2002;16(4):335–352. , .
- Patients' Responsibilities. In:Post SG, ed.Encyclopedia of Bioethics.Third ed.New York:Thompson Gale;2004. p.1990–1992. .
ITP and Hyperthyroidism
The connection between idiopathic thrombocytopenic purpura (ITP) and Grave's disease is not well known in the Western hemisphere. The immunologic relationship between these 2 conditions is well reported15 but poorly defined in the literature. New‐onset hyperthyroidism in the setting of preexisting ITP can be overlooked and, if untreated, lead to worsening of the ITP, rendering it refractory to standard therapy. Early recognition and treatment of the hyperthyroid state with antithyroid medications can lead to significant improvement in the platelet count.1, 8 We report this rare but critical clinical relationship.
CASE REPORT
A 35‐year‐old Asian woman with a known history of stable ITP for 12 years (baseline platelet count of 40,000/mL) presented to her outpatient provider with a diffuse petechial rash, easy bruisability, and heavy menorrhagia for 2 weeks. Her new platelet count was 7000/mL. She was immediately started on prednisone at a dose of 1 mg/kg without any improvement in her platelet count. At the end of 4 weeks on prednisone, she developed fever, intractable nausea and vomiting, severe headache, hypotension, and tachycardia. She was subsequently hospitalized with the presumptive diagnosis of meningitis and sepsis syndrome. Her clinical syndrome was consistent with systemic inflammatory response syndrome. She was treated aggressively with intravenous fluids and a broad‐spectrum empirical antimicrobial regimen consisting of ceftriaxone, vancomycin, and acyclovir. Lumbar puncture was deferred because of her low platelet count. The sepsis workup, which included viral, fungal, and bacterial blood cultures, remained negative. Her peripheral smear did not show evidence of microangiopathic hemolytic anemia, therefore ruling out thrombotic thrombocytopenic purpura and disseminated intravascular coagulation. HIV and tuberculosis were also ruled out. After the initial sepsis workup turned out negative, she was started on solumedrol 125 mg IV every 6 hours. Over the next 2 weeks, she received an average of 4‐6 units of platelets per day and multiple blood transfusions to maintain her hemoglobin and platelet counts. The latter remained in the 1000‐5000 platelets/mL range throughout her hospitalization without any significant improvement. Her clinical course was further complicated by multiple small intracranial hemorrhages without major focal neurological deficits. A bone marrow biopsy was eventually done. It showed early dysplastic cells but no definite features of myelodysplasia and few large megakaryocytes. She received 1 dose of vincristine without response in the bone marrow after 2 weeks, and consideration was given to treatment with rituximab for refractory ITP. At that point, she informed her hematologist that 10 years ago, she had been treated for hyperthyroidism with antithyroid medications for 6 months, without further follow‐up. A thyroid panel was then ordered, and she was found to be hyperthyroid, with thyroid‐stimulating hormone (TSH) < 0.01 mU/mL and free T4 of 3.1 ng/dL. She was subsequently started on propylthiouracil at 300 mg per day. Her platelet count dramatically improved and went up to the 50,000/mm3 range without further intervention over the next few months. After her discharge, an outpatient thyroid scan showed diffuse, homogeneous uptake of iodine, thereby confirming the diagnosis of Grave's disease. Retrospectively, her initial clinical syndrome of fever, hypotension, and tachycardia may have been the result of thyrotoxicosis or worsened by it.
DISCUSSION
The association between ITP and Grave's disease is poorly understood. Many hypotheses from observational data have been given in the literature. The leading theory to explain the coexistence of these 2 disorders is the presence of a common autoimmune pathway with production of 2 kinds of antibodies against platelets and TSH receptors. Indeed, autoimmune disorders tend to occur concurrently in individuals or families. Bizzaro et al. reported the coexistence of ITP and Grave's in 4 members of the same family.6 Hymes et al. found elevated levels of platelet‐bound IgG in 44% of 25 study patients with Grave's thyrotoxicosis.7 Most of these patients had easy bruising and/or bleeding, and 12% were thrombocytopenic. Panzer et al. reported the presence of antiplatelet IgG in patients with Grave's as well as improved platelet counts and increased mean platelet volume after successful antithyroid therapy.8
In addition to the coexistence of thyroid‐stimulatingimmunoglobulins (TSIs) and antiplatelet antibodies as a potential mechanism for Grave's‐associated thrombocytopenia, some have postulated that in Grave's patients, TSIs and other thyroid antibodies might actually bind to the platelets themselves. The postulated site for binding would be a truncated actin‐binding protein on the platelets that would link the high‐affinity Fc receptor of immunoglobulin G to the platelets' cytoskeleton, thereby accelerating their destruction.9
Another plausible mechanism is activation of the reticuloendothelial system by thyroid hormones, with increased clearance of platelets by the spleen in thyrotoxic states. This may explain the restoration of the platelet count when euthyroidism is reached.
Finally, thyrotoxicosis seems to alter platelet aggregation, partially by inhibition of myosin light‐chain kinase, and that also improves with restoration of euthyroidism.10
The coexistence of severe hyperthyroidism and thrombocytopenia can mimic severe sepsis in critically ill patients, and the hyperthyroid state in itself can worsen the thrombocytopenia of ITP. We suspect this patient's severe sepsis may actually have been an unrecognized severe thyrotoxicosis, with bone marrow dysfunction secondary to the hyperthyroidism, which might partially explain her lack of response to standard therapy.
CONCLUSIONS
This case underscores the importance of screening for and treating hyperthyroidism in patients with ITP, especially those resistant to steroid therapy, because the literature seems to indicate that treatment of the hyperthyroid state improves platelet count. This might help to prevent devastating clinical complications. Further research is necessary to define this empirical finding.
- Improvement of idiopathic thrombocytopenic purpura by antithyroid therapy.Eur J Haematol.74:73–74. , , , , , .
- Graves disease associated with autoimmune thrombocytopenic purpura.Arch Intern Med.1997;157:1033–1036. , , , .
- The thyrotoxicosis/thrombocytopenia connection.Surgery.1983;94:966–968. .
- Idiopathic thrombocytopenic purpura and Graves disease.Am J Hematol.1982;12:69–72. , , , .
- Autoimmune thrombocytopenic purpura associated with hyperthyroidism in a single individual.South Med J.1997;90:933–936. , .
- Familial association of autoimmune thrombocytopenia and hyperthyroidism.Am J Hematol.1992;39:294–298. .
- Easy bruising, thrombocytopenia, and elevated platelet immunoglobulin G in Graves' disease and Hashimoto's thyroiditis.Ann Intern Med.1981;94:27–30. , , , et al.
- Platelets in hyperthyroidism: studies on platelet counts, mean platelet volume.111‐indium‐labeled platelet kinetics, and platelet associated immunoglobulins G and M.J Clin Endocrinol Metab.1990;70:491–496. , , .
- Coagulation disorders in thyroid diseases.Eur J Endocrinol.1997;136:1. , .
- Alteration of platelet aggregation in patients with thyroid disorders.Metabolism.1997;46:1128. , , .
The connection between idiopathic thrombocytopenic purpura (ITP) and Grave's disease is not well known in the Western hemisphere. The immunologic relationship between these 2 conditions is well reported15 but poorly defined in the literature. New‐onset hyperthyroidism in the setting of preexisting ITP can be overlooked and, if untreated, lead to worsening of the ITP, rendering it refractory to standard therapy. Early recognition and treatment of the hyperthyroid state with antithyroid medications can lead to significant improvement in the platelet count.1, 8 We report this rare but critical clinical relationship.
CASE REPORT
A 35‐year‐old Asian woman with a known history of stable ITP for 12 years (baseline platelet count of 40,000/mL) presented to her outpatient provider with a diffuse petechial rash, easy bruisability, and heavy menorrhagia for 2 weeks. Her new platelet count was 7000/mL. She was immediately started on prednisone at a dose of 1 mg/kg without any improvement in her platelet count. At the end of 4 weeks on prednisone, she developed fever, intractable nausea and vomiting, severe headache, hypotension, and tachycardia. She was subsequently hospitalized with the presumptive diagnosis of meningitis and sepsis syndrome. Her clinical syndrome was consistent with systemic inflammatory response syndrome. She was treated aggressively with intravenous fluids and a broad‐spectrum empirical antimicrobial regimen consisting of ceftriaxone, vancomycin, and acyclovir. Lumbar puncture was deferred because of her low platelet count. The sepsis workup, which included viral, fungal, and bacterial blood cultures, remained negative. Her peripheral smear did not show evidence of microangiopathic hemolytic anemia, therefore ruling out thrombotic thrombocytopenic purpura and disseminated intravascular coagulation. HIV and tuberculosis were also ruled out. After the initial sepsis workup turned out negative, she was started on solumedrol 125 mg IV every 6 hours. Over the next 2 weeks, she received an average of 4‐6 units of platelets per day and multiple blood transfusions to maintain her hemoglobin and platelet counts. The latter remained in the 1000‐5000 platelets/mL range throughout her hospitalization without any significant improvement. Her clinical course was further complicated by multiple small intracranial hemorrhages without major focal neurological deficits. A bone marrow biopsy was eventually done. It showed early dysplastic cells but no definite features of myelodysplasia and few large megakaryocytes. She received 1 dose of vincristine without response in the bone marrow after 2 weeks, and consideration was given to treatment with rituximab for refractory ITP. At that point, she informed her hematologist that 10 years ago, she had been treated for hyperthyroidism with antithyroid medications for 6 months, without further follow‐up. A thyroid panel was then ordered, and she was found to be hyperthyroid, with thyroid‐stimulating hormone (TSH) < 0.01 mU/mL and free T4 of 3.1 ng/dL. She was subsequently started on propylthiouracil at 300 mg per day. Her platelet count dramatically improved and went up to the 50,000/mm3 range without further intervention over the next few months. After her discharge, an outpatient thyroid scan showed diffuse, homogeneous uptake of iodine, thereby confirming the diagnosis of Grave's disease. Retrospectively, her initial clinical syndrome of fever, hypotension, and tachycardia may have been the result of thyrotoxicosis or worsened by it.
DISCUSSION
The association between ITP and Grave's disease is poorly understood. Many hypotheses from observational data have been given in the literature. The leading theory to explain the coexistence of these 2 disorders is the presence of a common autoimmune pathway with production of 2 kinds of antibodies against platelets and TSH receptors. Indeed, autoimmune disorders tend to occur concurrently in individuals or families. Bizzaro et al. reported the coexistence of ITP and Grave's in 4 members of the same family.6 Hymes et al. found elevated levels of platelet‐bound IgG in 44% of 25 study patients with Grave's thyrotoxicosis.7 Most of these patients had easy bruising and/or bleeding, and 12% were thrombocytopenic. Panzer et al. reported the presence of antiplatelet IgG in patients with Grave's as well as improved platelet counts and increased mean platelet volume after successful antithyroid therapy.8
In addition to the coexistence of thyroid‐stimulatingimmunoglobulins (TSIs) and antiplatelet antibodies as a potential mechanism for Grave's‐associated thrombocytopenia, some have postulated that in Grave's patients, TSIs and other thyroid antibodies might actually bind to the platelets themselves. The postulated site for binding would be a truncated actin‐binding protein on the platelets that would link the high‐affinity Fc receptor of immunoglobulin G to the platelets' cytoskeleton, thereby accelerating their destruction.9
Another plausible mechanism is activation of the reticuloendothelial system by thyroid hormones, with increased clearance of platelets by the spleen in thyrotoxic states. This may explain the restoration of the platelet count when euthyroidism is reached.
Finally, thyrotoxicosis seems to alter platelet aggregation, partially by inhibition of myosin light‐chain kinase, and that also improves with restoration of euthyroidism.10
The coexistence of severe hyperthyroidism and thrombocytopenia can mimic severe sepsis in critically ill patients, and the hyperthyroid state in itself can worsen the thrombocytopenia of ITP. We suspect this patient's severe sepsis may actually have been an unrecognized severe thyrotoxicosis, with bone marrow dysfunction secondary to the hyperthyroidism, which might partially explain her lack of response to standard therapy.
CONCLUSIONS
This case underscores the importance of screening for and treating hyperthyroidism in patients with ITP, especially those resistant to steroid therapy, because the literature seems to indicate that treatment of the hyperthyroid state improves platelet count. This might help to prevent devastating clinical complications. Further research is necessary to define this empirical finding.
The connection between idiopathic thrombocytopenic purpura (ITP) and Grave's disease is not well known in the Western hemisphere. The immunologic relationship between these 2 conditions is well reported15 but poorly defined in the literature. New‐onset hyperthyroidism in the setting of preexisting ITP can be overlooked and, if untreated, lead to worsening of the ITP, rendering it refractory to standard therapy. Early recognition and treatment of the hyperthyroid state with antithyroid medications can lead to significant improvement in the platelet count.1, 8 We report this rare but critical clinical relationship.
CASE REPORT
A 35‐year‐old Asian woman with a known history of stable ITP for 12 years (baseline platelet count of 40,000/mL) presented to her outpatient provider with a diffuse petechial rash, easy bruisability, and heavy menorrhagia for 2 weeks. Her new platelet count was 7000/mL. She was immediately started on prednisone at a dose of 1 mg/kg without any improvement in her platelet count. At the end of 4 weeks on prednisone, she developed fever, intractable nausea and vomiting, severe headache, hypotension, and tachycardia. She was subsequently hospitalized with the presumptive diagnosis of meningitis and sepsis syndrome. Her clinical syndrome was consistent with systemic inflammatory response syndrome. She was treated aggressively with intravenous fluids and a broad‐spectrum empirical antimicrobial regimen consisting of ceftriaxone, vancomycin, and acyclovir. Lumbar puncture was deferred because of her low platelet count. The sepsis workup, which included viral, fungal, and bacterial blood cultures, remained negative. Her peripheral smear did not show evidence of microangiopathic hemolytic anemia, therefore ruling out thrombotic thrombocytopenic purpura and disseminated intravascular coagulation. HIV and tuberculosis were also ruled out. After the initial sepsis workup turned out negative, she was started on solumedrol 125 mg IV every 6 hours. Over the next 2 weeks, she received an average of 4‐6 units of platelets per day and multiple blood transfusions to maintain her hemoglobin and platelet counts. The latter remained in the 1000‐5000 platelets/mL range throughout her hospitalization without any significant improvement. Her clinical course was further complicated by multiple small intracranial hemorrhages without major focal neurological deficits. A bone marrow biopsy was eventually done. It showed early dysplastic cells but no definite features of myelodysplasia and few large megakaryocytes. She received 1 dose of vincristine without response in the bone marrow after 2 weeks, and consideration was given to treatment with rituximab for refractory ITP. At that point, she informed her hematologist that 10 years ago, she had been treated for hyperthyroidism with antithyroid medications for 6 months, without further follow‐up. A thyroid panel was then ordered, and she was found to be hyperthyroid, with thyroid‐stimulating hormone (TSH) < 0.01 mU/mL and free T4 of 3.1 ng/dL. She was subsequently started on propylthiouracil at 300 mg per day. Her platelet count dramatically improved and went up to the 50,000/mm3 range without further intervention over the next few months. After her discharge, an outpatient thyroid scan showed diffuse, homogeneous uptake of iodine, thereby confirming the diagnosis of Grave's disease. Retrospectively, her initial clinical syndrome of fever, hypotension, and tachycardia may have been the result of thyrotoxicosis or worsened by it.
DISCUSSION
The association between ITP and Grave's disease is poorly understood. Many hypotheses from observational data have been given in the literature. The leading theory to explain the coexistence of these 2 disorders is the presence of a common autoimmune pathway with production of 2 kinds of antibodies against platelets and TSH receptors. Indeed, autoimmune disorders tend to occur concurrently in individuals or families. Bizzaro et al. reported the coexistence of ITP and Grave's in 4 members of the same family.6 Hymes et al. found elevated levels of platelet‐bound IgG in 44% of 25 study patients with Grave's thyrotoxicosis.7 Most of these patients had easy bruising and/or bleeding, and 12% were thrombocytopenic. Panzer et al. reported the presence of antiplatelet IgG in patients with Grave's as well as improved platelet counts and increased mean platelet volume after successful antithyroid therapy.8
In addition to the coexistence of thyroid‐stimulatingimmunoglobulins (TSIs) and antiplatelet antibodies as a potential mechanism for Grave's‐associated thrombocytopenia, some have postulated that in Grave's patients, TSIs and other thyroid antibodies might actually bind to the platelets themselves. The postulated site for binding would be a truncated actin‐binding protein on the platelets that would link the high‐affinity Fc receptor of immunoglobulin G to the platelets' cytoskeleton, thereby accelerating their destruction.9
Another plausible mechanism is activation of the reticuloendothelial system by thyroid hormones, with increased clearance of platelets by the spleen in thyrotoxic states. This may explain the restoration of the platelet count when euthyroidism is reached.
Finally, thyrotoxicosis seems to alter platelet aggregation, partially by inhibition of myosin light‐chain kinase, and that also improves with restoration of euthyroidism.10
The coexistence of severe hyperthyroidism and thrombocytopenia can mimic severe sepsis in critically ill patients, and the hyperthyroid state in itself can worsen the thrombocytopenia of ITP. We suspect this patient's severe sepsis may actually have been an unrecognized severe thyrotoxicosis, with bone marrow dysfunction secondary to the hyperthyroidism, which might partially explain her lack of response to standard therapy.
CONCLUSIONS
This case underscores the importance of screening for and treating hyperthyroidism in patients with ITP, especially those resistant to steroid therapy, because the literature seems to indicate that treatment of the hyperthyroid state improves platelet count. This might help to prevent devastating clinical complications. Further research is necessary to define this empirical finding.
- Improvement of idiopathic thrombocytopenic purpura by antithyroid therapy.Eur J Haematol.74:73–74. , , , , , .
- Graves disease associated with autoimmune thrombocytopenic purpura.Arch Intern Med.1997;157:1033–1036. , , , .
- The thyrotoxicosis/thrombocytopenia connection.Surgery.1983;94:966–968. .
- Idiopathic thrombocytopenic purpura and Graves disease.Am J Hematol.1982;12:69–72. , , , .
- Autoimmune thrombocytopenic purpura associated with hyperthyroidism in a single individual.South Med J.1997;90:933–936. , .
- Familial association of autoimmune thrombocytopenia and hyperthyroidism.Am J Hematol.1992;39:294–298. .
- Easy bruising, thrombocytopenia, and elevated platelet immunoglobulin G in Graves' disease and Hashimoto's thyroiditis.Ann Intern Med.1981;94:27–30. , , , et al.
- Platelets in hyperthyroidism: studies on platelet counts, mean platelet volume.111‐indium‐labeled platelet kinetics, and platelet associated immunoglobulins G and M.J Clin Endocrinol Metab.1990;70:491–496. , , .
- Coagulation disorders in thyroid diseases.Eur J Endocrinol.1997;136:1. , .
- Alteration of platelet aggregation in patients with thyroid disorders.Metabolism.1997;46:1128. , , .
- Improvement of idiopathic thrombocytopenic purpura by antithyroid therapy.Eur J Haematol.74:73–74. , , , , , .
- Graves disease associated with autoimmune thrombocytopenic purpura.Arch Intern Med.1997;157:1033–1036. , , , .
- The thyrotoxicosis/thrombocytopenia connection.Surgery.1983;94:966–968. .
- Idiopathic thrombocytopenic purpura and Graves disease.Am J Hematol.1982;12:69–72. , , , .
- Autoimmune thrombocytopenic purpura associated with hyperthyroidism in a single individual.South Med J.1997;90:933–936. , .
- Familial association of autoimmune thrombocytopenia and hyperthyroidism.Am J Hematol.1992;39:294–298. .
- Easy bruising, thrombocytopenia, and elevated platelet immunoglobulin G in Graves' disease and Hashimoto's thyroiditis.Ann Intern Med.1981;94:27–30. , , , et al.
- Platelets in hyperthyroidism: studies on platelet counts, mean platelet volume.111‐indium‐labeled platelet kinetics, and platelet associated immunoglobulins G and M.J Clin Endocrinol Metab.1990;70:491–496. , , .
- Coagulation disorders in thyroid diseases.Eur J Endocrinol.1997;136:1. , .
- Alteration of platelet aggregation in patients with thyroid disorders.Metabolism.1997;46:1128. , , .
Editorial
Older Americans comprise approximately half the patients on inpatient medical wards. There are too few geriatricians to care for these patients, and few geriatricians practice hospital medicine. Hospitalists often provide the majority of inpatient geriatric care, and at teaching hospitals, hospitalists also play a pivotal role in educating residents and students to provide high‐quality care for hospitalized geriatric patients. Thus, hospitalists will be the primary clinicians educating many trainees to care for older patients, and the hospitalists must be skilled in addressing the clinical syndromes that are common in these patients, including delirium, dementia, falls, and infection.1 Generalists and geriatricians have anticipated a shortfall in clinicians prepared to educate trainees about geriatrics and called for faculty development for generalists in geriatrics.2, 3
In this issue of the Journal of Hospital Medicine, Podrazik and colleagues present initial results from a major initiative to enhance the quality and quantity of geriatric inpatient education for residents and students.4 The Curriculum for the Hospitalized Aging Medical Patient (CHAMP) at the University of Chicago represents a multifaceted faculty development effort funded in part by the Donald W. Reynolds and John A. Hartford Foundations. In 12 half‐day sessions offered weekly, hospitalist and general internist faculty members learned about four thematic areasthe frail older person, hazards of hospitalization, end‐of‐life issues, and transitions of carewhile also receiving training in engaging and effective teaching strategies. At each session, participants drew on their own experiences attending on the wards to generate clinical examples and test new teaching strategies. CHAMP incorporates the attributes of best practices for integrating geriatrics education into internal medicine residency training: it promotes model care for older hospital patients, uses a train‐the‐trainer model, addresses care transitions, and promotes interdisciplinary teamwork.5
CHAMP achieved its initial goals. Faculty participants were satisfied and CHAMP substantially increased participants' confidence in practicing and teaching geriatric care. Faculty participants also gained confidence in their teaching abilities and presumably learned teaching strategies that could be applied to other topics in inpatient medicine. Faculty participants demonstrated modest improvements in their knowledge of geriatric issues and more positive attitudes about geriatrics at the end of the course than at the beginning. It is worth noting that the hospitalist and general internist ward attending physicians who participated in CHAMP were volunteers and may have started the process with greater interest in learning geriatric care than other attendings. Thus, it is unknown whether CHAMP might have greater or lesser effect on other faculty.
The CHAMP train‐the‐trainer model offers the potential to impact future practitioners. Findings of the CHAMP investigators are consistent with the literature on faculty development programs for educators, which shows that faculty development on teaching yields high participant satisfaction, knowledge gains, and improved self‐assessment of the ability to implement changes in teaching practice.6 The use in CHAMP of a diverse menu of teaching strategies and active learning techniques such as case‐based discussions and the Objective Structured Teaching Exercise in a small group of colleagues should promote learning and retention.
Is the CHAMP curriculum worth the cost? The program requires resources to pay for 48 hours for each faculty participant and for instructors with expertise in geriatrics and teaching skills. We estimate that the cost for 12 faculty participants would be roughly $72,000. We believe this investment will likely pay off in terms of enhancing faculty skills, improving faculty job satisfaction, promoting faculty retention in academic or other teaching positions, and improving care provided by trainees. For example, if CHAMP were to lead to the retention and promotion of even 2 faculty for just 1 year, it would save recruitment costs that would exceed the direct program costs, and other benefits of CHAMP would only further add value. However, analysis of the benefits of CHAMP will require more in‐depth evaluation data of its impact. The program leaders currently contact former participants around the time of ward attending to reinforce teaching concepts and encourage implementation of CHAMP materials, through a Commitment to Change contract. The ultimate downstream educational goal would be that these faculty learners retain and apply this newly acquired knowledge and skills in their clinical practice and teaching activities. Ideally, evidence would confirm that these benefits improve patient care. The long‐term evaluation plan for CHAMP incorporates important additional outcome measures including resident and student geriatric knowledge as well as patient satisfaction and clinical outcomes. We commend the authors for aiming to expand their evaluation plan over time and aspiring for sustained changes in teaching practice. The literature on the impact of hospitalists has similarly evolved from early descriptions of hospitalists and the logistics of developing a hospitalist program to sophisticated analyses of the impact of hospitalists on clinical outcomes such as length of stay and mortality.7, 8
The feasibility of disseminating CHAMP is an open question. The University of Chicago model employs a time‐intensive curriculum that engages participants in part by releasing them from clinical duties for a half day per week. Release time was funded through combined support from external funding sources and the Department of Medicine. This model addresses the major barrier to faculty development in geriatrics for general internists: lack of time.2, 9 The investment in intensive, longitudinal faculty development may generate higher returns than periodic short faculty workshop sessions that do not build in the time for role‐playing, practice, and reinforcement of key concepts. This type of intervention may also be more feasible when done in conjunction with one of the approximately 50 Health Resources and Services Administration (HRSA)supported Geriatrics Education Centers, which can fund teachers and infrastructure for faculty development.
How is this article useful for hospitalist educators? Many hospitalists at academic centers serve important teaching functions, and some will aspire to advance their educational efforts through more scholarly activities such as curriculum design. The CHAMP curriculum represents a successful model for hospitalists aiming to follow a rigorous approach to curriculum design relevant to inpatient medicine, and the extensive CHAMP materials are available online.10 It serves as a practical model that could be applied to other clinical topics related to hospital medicine. Hospitalists are effective and respected teachers for residents and students, and they develop unique expertise in the content and process of inpatient medicine.11 The authors followed the 6 steps of effective curriculum design: problem identification, targeted needs assessment, goals and objectives, education methods, implementation, and evaluation.12
The CHAMP curriculum typifies a set of materials that aligns well with the Society of Hospital Medicine (SHM) Core Competencies.13 As part of their needs assessment, the authors also surveyed hospitalists at a regional SHM meeting to determine the geriatrics topics for which they perceived greatest educational need. The Core Competencies chapters on the care of the elderly patient, delirium and dementia, hospital‐acquired infections, and palliative care highlight the common learning goals shared by hospital medicine and geriatrics. Both disciplines also emphasize the team‐based, multidisciplinary approach to care, particularly during care transitions, that is highlighted in the CHAMP curriculum.
More generally, the CHAMP curriculum can be used to teach and assess the Accreditation Council for Graduate Medical Education (ACGME) competencies, which must be assessed in all ACGME‐accredited residency programs.14 In an initial session on Teaching on Today's Wards, CHAMP participants brainstorm about how to incorporate both geriatrics content and the ACGME competencies into their post‐call rounds. The emphasis in CHAMP on the health care system and interdisciplinary care is evident in topics such as end‐of‐life care and transitions in care, and provides opportunity for assessment of residents' performance in the ACGME competency of systems‐based practice. The organization of the curriculum by ACGME competency makes it more applicable today than some prior geriatric curricula that emphasized similar themes but without the emphasis on demonstrating competency as an outcome.15
Hospitalists partnering with the Donald W. Reynolds and John A. Hartford Foundations and other external organizations may find funding opportunities for educational projects. For example, the Hartford Foundation has partnered with SHM since 2002 to support hospitalists' efforts to improve care for older adults. Products of this collaboration include a Geriatric Toolbox that contains assessment tools designed for use with geriatric patients.16 The tools assess a range of parameters including nutritional, functional, and mental status, and the website supplies guidelines on the advantages and disadvantages and appropriate use of each assessment tool. With support from the Hartford Foundation, hospitalists have also conducted several workshops at SHM meetings on improving assessment and care of geriatric patients and developed a discharge‐planning checklist for older adults.
As hospitalist programs gain traction in academic centers, hospitalists will increasingly serve as key geriatric content educators for trainees. The CHAMP curriculum offers a model of intensive faculty development for hospitalists and general internists that clinician educators find engaging and empowering. The partnerships of geriatricians and hospitalists, and of the SHM with national geriatrics organizations, have the potential for widespread benefits for both learners and elderly patients.
Older Americans comprise approximately half the patients on inpatient medical wards. There are too few geriatricians to care for these patients, and few geriatricians practice hospital medicine. Hospitalists often provide the majority of inpatient geriatric care, and at teaching hospitals, hospitalists also play a pivotal role in educating residents and students to provide high‐quality care for hospitalized geriatric patients. Thus, hospitalists will be the primary clinicians educating many trainees to care for older patients, and the hospitalists must be skilled in addressing the clinical syndromes that are common in these patients, including delirium, dementia, falls, and infection.1 Generalists and geriatricians have anticipated a shortfall in clinicians prepared to educate trainees about geriatrics and called for faculty development for generalists in geriatrics.2, 3
In this issue of the Journal of Hospital Medicine, Podrazik and colleagues present initial results from a major initiative to enhance the quality and quantity of geriatric inpatient education for residents and students.4 The Curriculum for the Hospitalized Aging Medical Patient (CHAMP) at the University of Chicago represents a multifaceted faculty development effort funded in part by the Donald W. Reynolds and John A. Hartford Foundations. In 12 half‐day sessions offered weekly, hospitalist and general internist faculty members learned about four thematic areasthe frail older person, hazards of hospitalization, end‐of‐life issues, and transitions of carewhile also receiving training in engaging and effective teaching strategies. At each session, participants drew on their own experiences attending on the wards to generate clinical examples and test new teaching strategies. CHAMP incorporates the attributes of best practices for integrating geriatrics education into internal medicine residency training: it promotes model care for older hospital patients, uses a train‐the‐trainer model, addresses care transitions, and promotes interdisciplinary teamwork.5
CHAMP achieved its initial goals. Faculty participants were satisfied and CHAMP substantially increased participants' confidence in practicing and teaching geriatric care. Faculty participants also gained confidence in their teaching abilities and presumably learned teaching strategies that could be applied to other topics in inpatient medicine. Faculty participants demonstrated modest improvements in their knowledge of geriatric issues and more positive attitudes about geriatrics at the end of the course than at the beginning. It is worth noting that the hospitalist and general internist ward attending physicians who participated in CHAMP were volunteers and may have started the process with greater interest in learning geriatric care than other attendings. Thus, it is unknown whether CHAMP might have greater or lesser effect on other faculty.
The CHAMP train‐the‐trainer model offers the potential to impact future practitioners. Findings of the CHAMP investigators are consistent with the literature on faculty development programs for educators, which shows that faculty development on teaching yields high participant satisfaction, knowledge gains, and improved self‐assessment of the ability to implement changes in teaching practice.6 The use in CHAMP of a diverse menu of teaching strategies and active learning techniques such as case‐based discussions and the Objective Structured Teaching Exercise in a small group of colleagues should promote learning and retention.
Is the CHAMP curriculum worth the cost? The program requires resources to pay for 48 hours for each faculty participant and for instructors with expertise in geriatrics and teaching skills. We estimate that the cost for 12 faculty participants would be roughly $72,000. We believe this investment will likely pay off in terms of enhancing faculty skills, improving faculty job satisfaction, promoting faculty retention in academic or other teaching positions, and improving care provided by trainees. For example, if CHAMP were to lead to the retention and promotion of even 2 faculty for just 1 year, it would save recruitment costs that would exceed the direct program costs, and other benefits of CHAMP would only further add value. However, analysis of the benefits of CHAMP will require more in‐depth evaluation data of its impact. The program leaders currently contact former participants around the time of ward attending to reinforce teaching concepts and encourage implementation of CHAMP materials, through a Commitment to Change contract. The ultimate downstream educational goal would be that these faculty learners retain and apply this newly acquired knowledge and skills in their clinical practice and teaching activities. Ideally, evidence would confirm that these benefits improve patient care. The long‐term evaluation plan for CHAMP incorporates important additional outcome measures including resident and student geriatric knowledge as well as patient satisfaction and clinical outcomes. We commend the authors for aiming to expand their evaluation plan over time and aspiring for sustained changes in teaching practice. The literature on the impact of hospitalists has similarly evolved from early descriptions of hospitalists and the logistics of developing a hospitalist program to sophisticated analyses of the impact of hospitalists on clinical outcomes such as length of stay and mortality.7, 8
The feasibility of disseminating CHAMP is an open question. The University of Chicago model employs a time‐intensive curriculum that engages participants in part by releasing them from clinical duties for a half day per week. Release time was funded through combined support from external funding sources and the Department of Medicine. This model addresses the major barrier to faculty development in geriatrics for general internists: lack of time.2, 9 The investment in intensive, longitudinal faculty development may generate higher returns than periodic short faculty workshop sessions that do not build in the time for role‐playing, practice, and reinforcement of key concepts. This type of intervention may also be more feasible when done in conjunction with one of the approximately 50 Health Resources and Services Administration (HRSA)supported Geriatrics Education Centers, which can fund teachers and infrastructure for faculty development.
How is this article useful for hospitalist educators? Many hospitalists at academic centers serve important teaching functions, and some will aspire to advance their educational efforts through more scholarly activities such as curriculum design. The CHAMP curriculum represents a successful model for hospitalists aiming to follow a rigorous approach to curriculum design relevant to inpatient medicine, and the extensive CHAMP materials are available online.10 It serves as a practical model that could be applied to other clinical topics related to hospital medicine. Hospitalists are effective and respected teachers for residents and students, and they develop unique expertise in the content and process of inpatient medicine.11 The authors followed the 6 steps of effective curriculum design: problem identification, targeted needs assessment, goals and objectives, education methods, implementation, and evaluation.12
The CHAMP curriculum typifies a set of materials that aligns well with the Society of Hospital Medicine (SHM) Core Competencies.13 As part of their needs assessment, the authors also surveyed hospitalists at a regional SHM meeting to determine the geriatrics topics for which they perceived greatest educational need. The Core Competencies chapters on the care of the elderly patient, delirium and dementia, hospital‐acquired infections, and palliative care highlight the common learning goals shared by hospital medicine and geriatrics. Both disciplines also emphasize the team‐based, multidisciplinary approach to care, particularly during care transitions, that is highlighted in the CHAMP curriculum.
More generally, the CHAMP curriculum can be used to teach and assess the Accreditation Council for Graduate Medical Education (ACGME) competencies, which must be assessed in all ACGME‐accredited residency programs.14 In an initial session on Teaching on Today's Wards, CHAMP participants brainstorm about how to incorporate both geriatrics content and the ACGME competencies into their post‐call rounds. The emphasis in CHAMP on the health care system and interdisciplinary care is evident in topics such as end‐of‐life care and transitions in care, and provides opportunity for assessment of residents' performance in the ACGME competency of systems‐based practice. The organization of the curriculum by ACGME competency makes it more applicable today than some prior geriatric curricula that emphasized similar themes but without the emphasis on demonstrating competency as an outcome.15
Hospitalists partnering with the Donald W. Reynolds and John A. Hartford Foundations and other external organizations may find funding opportunities for educational projects. For example, the Hartford Foundation has partnered with SHM since 2002 to support hospitalists' efforts to improve care for older adults. Products of this collaboration include a Geriatric Toolbox that contains assessment tools designed for use with geriatric patients.16 The tools assess a range of parameters including nutritional, functional, and mental status, and the website supplies guidelines on the advantages and disadvantages and appropriate use of each assessment tool. With support from the Hartford Foundation, hospitalists have also conducted several workshops at SHM meetings on improving assessment and care of geriatric patients and developed a discharge‐planning checklist for older adults.
As hospitalist programs gain traction in academic centers, hospitalists will increasingly serve as key geriatric content educators for trainees. The CHAMP curriculum offers a model of intensive faculty development for hospitalists and general internists that clinician educators find engaging and empowering. The partnerships of geriatricians and hospitalists, and of the SHM with national geriatrics organizations, have the potential for widespread benefits for both learners and elderly patients.
Older Americans comprise approximately half the patients on inpatient medical wards. There are too few geriatricians to care for these patients, and few geriatricians practice hospital medicine. Hospitalists often provide the majority of inpatient geriatric care, and at teaching hospitals, hospitalists also play a pivotal role in educating residents and students to provide high‐quality care for hospitalized geriatric patients. Thus, hospitalists will be the primary clinicians educating many trainees to care for older patients, and the hospitalists must be skilled in addressing the clinical syndromes that are common in these patients, including delirium, dementia, falls, and infection.1 Generalists and geriatricians have anticipated a shortfall in clinicians prepared to educate trainees about geriatrics and called for faculty development for generalists in geriatrics.2, 3
In this issue of the Journal of Hospital Medicine, Podrazik and colleagues present initial results from a major initiative to enhance the quality and quantity of geriatric inpatient education for residents and students.4 The Curriculum for the Hospitalized Aging Medical Patient (CHAMP) at the University of Chicago represents a multifaceted faculty development effort funded in part by the Donald W. Reynolds and John A. Hartford Foundations. In 12 half‐day sessions offered weekly, hospitalist and general internist faculty members learned about four thematic areasthe frail older person, hazards of hospitalization, end‐of‐life issues, and transitions of carewhile also receiving training in engaging and effective teaching strategies. At each session, participants drew on their own experiences attending on the wards to generate clinical examples and test new teaching strategies. CHAMP incorporates the attributes of best practices for integrating geriatrics education into internal medicine residency training: it promotes model care for older hospital patients, uses a train‐the‐trainer model, addresses care transitions, and promotes interdisciplinary teamwork.5
CHAMP achieved its initial goals. Faculty participants were satisfied and CHAMP substantially increased participants' confidence in practicing and teaching geriatric care. Faculty participants also gained confidence in their teaching abilities and presumably learned teaching strategies that could be applied to other topics in inpatient medicine. Faculty participants demonstrated modest improvements in their knowledge of geriatric issues and more positive attitudes about geriatrics at the end of the course than at the beginning. It is worth noting that the hospitalist and general internist ward attending physicians who participated in CHAMP were volunteers and may have started the process with greater interest in learning geriatric care than other attendings. Thus, it is unknown whether CHAMP might have greater or lesser effect on other faculty.
The CHAMP train‐the‐trainer model offers the potential to impact future practitioners. Findings of the CHAMP investigators are consistent with the literature on faculty development programs for educators, which shows that faculty development on teaching yields high participant satisfaction, knowledge gains, and improved self‐assessment of the ability to implement changes in teaching practice.6 The use in CHAMP of a diverse menu of teaching strategies and active learning techniques such as case‐based discussions and the Objective Structured Teaching Exercise in a small group of colleagues should promote learning and retention.
Is the CHAMP curriculum worth the cost? The program requires resources to pay for 48 hours for each faculty participant and for instructors with expertise in geriatrics and teaching skills. We estimate that the cost for 12 faculty participants would be roughly $72,000. We believe this investment will likely pay off in terms of enhancing faculty skills, improving faculty job satisfaction, promoting faculty retention in academic or other teaching positions, and improving care provided by trainees. For example, if CHAMP were to lead to the retention and promotion of even 2 faculty for just 1 year, it would save recruitment costs that would exceed the direct program costs, and other benefits of CHAMP would only further add value. However, analysis of the benefits of CHAMP will require more in‐depth evaluation data of its impact. The program leaders currently contact former participants around the time of ward attending to reinforce teaching concepts and encourage implementation of CHAMP materials, through a Commitment to Change contract. The ultimate downstream educational goal would be that these faculty learners retain and apply this newly acquired knowledge and skills in their clinical practice and teaching activities. Ideally, evidence would confirm that these benefits improve patient care. The long‐term evaluation plan for CHAMP incorporates important additional outcome measures including resident and student geriatric knowledge as well as patient satisfaction and clinical outcomes. We commend the authors for aiming to expand their evaluation plan over time and aspiring for sustained changes in teaching practice. The literature on the impact of hospitalists has similarly evolved from early descriptions of hospitalists and the logistics of developing a hospitalist program to sophisticated analyses of the impact of hospitalists on clinical outcomes such as length of stay and mortality.7, 8
The feasibility of disseminating CHAMP is an open question. The University of Chicago model employs a time‐intensive curriculum that engages participants in part by releasing them from clinical duties for a half day per week. Release time was funded through combined support from external funding sources and the Department of Medicine. This model addresses the major barrier to faculty development in geriatrics for general internists: lack of time.2, 9 The investment in intensive, longitudinal faculty development may generate higher returns than periodic short faculty workshop sessions that do not build in the time for role‐playing, practice, and reinforcement of key concepts. This type of intervention may also be more feasible when done in conjunction with one of the approximately 50 Health Resources and Services Administration (HRSA)supported Geriatrics Education Centers, which can fund teachers and infrastructure for faculty development.
How is this article useful for hospitalist educators? Many hospitalists at academic centers serve important teaching functions, and some will aspire to advance their educational efforts through more scholarly activities such as curriculum design. The CHAMP curriculum represents a successful model for hospitalists aiming to follow a rigorous approach to curriculum design relevant to inpatient medicine, and the extensive CHAMP materials are available online.10 It serves as a practical model that could be applied to other clinical topics related to hospital medicine. Hospitalists are effective and respected teachers for residents and students, and they develop unique expertise in the content and process of inpatient medicine.11 The authors followed the 6 steps of effective curriculum design: problem identification, targeted needs assessment, goals and objectives, education methods, implementation, and evaluation.12
The CHAMP curriculum typifies a set of materials that aligns well with the Society of Hospital Medicine (SHM) Core Competencies.13 As part of their needs assessment, the authors also surveyed hospitalists at a regional SHM meeting to determine the geriatrics topics for which they perceived greatest educational need. The Core Competencies chapters on the care of the elderly patient, delirium and dementia, hospital‐acquired infections, and palliative care highlight the common learning goals shared by hospital medicine and geriatrics. Both disciplines also emphasize the team‐based, multidisciplinary approach to care, particularly during care transitions, that is highlighted in the CHAMP curriculum.
More generally, the CHAMP curriculum can be used to teach and assess the Accreditation Council for Graduate Medical Education (ACGME) competencies, which must be assessed in all ACGME‐accredited residency programs.14 In an initial session on Teaching on Today's Wards, CHAMP participants brainstorm about how to incorporate both geriatrics content and the ACGME competencies into their post‐call rounds. The emphasis in CHAMP on the health care system and interdisciplinary care is evident in topics such as end‐of‐life care and transitions in care, and provides opportunity for assessment of residents' performance in the ACGME competency of systems‐based practice. The organization of the curriculum by ACGME competency makes it more applicable today than some prior geriatric curricula that emphasized similar themes but without the emphasis on demonstrating competency as an outcome.15
Hospitalists partnering with the Donald W. Reynolds and John A. Hartford Foundations and other external organizations may find funding opportunities for educational projects. For example, the Hartford Foundation has partnered with SHM since 2002 to support hospitalists' efforts to improve care for older adults. Products of this collaboration include a Geriatric Toolbox that contains assessment tools designed for use with geriatric patients.16 The tools assess a range of parameters including nutritional, functional, and mental status, and the website supplies guidelines on the advantages and disadvantages and appropriate use of each assessment tool. With support from the Hartford Foundation, hospitalists have also conducted several workshops at SHM meetings on improving assessment and care of geriatric patients and developed a discharge‐planning checklist for older adults.
As hospitalist programs gain traction in academic centers, hospitalists will increasingly serve as key geriatric content educators for trainees. The CHAMP curriculum offers a model of intensive faculty development for hospitalists and general internists that clinician educators find engaging and empowering. The partnerships of geriatricians and hospitalists, and of the SHM with national geriatrics organizations, have the potential for widespread benefits for both learners and elderly patients.
An Unconventional Living Will
Her name was Mrs. Carberry, but her readers knew her as Mary Margaret. Two months earlier, she suffered a debilitating stroke that took away her vibrant life. Previously a prolific writer of advice columns and opinion pieces, the blockage of blood to her brain dammed the steady flow of wisdom to her innumerable fans. They never again would benefit from the words of this intelligent, feisty, and self‐proclaimed Cranky Catholic. Unfortunately, I would not know Mary Margaret for her words, but only her numbers: her vital signs, her urine output, her tube feed residuals.
Not able to communicate with us, we wondered did Mrs. Carberry want this tracheostomy that was placed? Did she want this peg tube that fed her continuously? And even if she would have initially agreed to them, would she still want them now? Especially given she was not improving and had little hope for a meaningful recovery.
We posed these difficult questions to her two sons. One son believed that his mother would want an end to these aggressive measures. The other son disagreed; he said his mother would want to make every effort to stay alive.
In the end, Mary Margaret's voice found its way to us and provided us with the answer. She did not tell us in the conventional manner via a lawyer or a living will. Her friends did not come forth and let us know about serious conversations during their afternoon lunches. Instead, Mary Margaret penned it to her audience of devoted readers in a newspaper column written 14 years earlier. Mary Margaret's poignant words were revealed to her doctors by her son who understood its undeniable significance.
Mary Margaret was an essayist in Chicago whose pieces filled many major newspapers and magazines. She had strong opinions on matters large and small, writing articles addressing topics ranging from her Catholic beliefs to gender‐based inequities in the workplace. One article in particular addressed sickness and death and provided her sons the answer they sought. Having witnessed illness strike two loved ones, it was only natural for Mary Margaret to write about it. Her very personal essay was entitled Tough Questions on Life, Death and a Dog Named Bamboo. The words, resurfacing years later, and now having direct meaning to her own life and death, may have been some of the most profound and prophetic words of her career:
Tough Questions on Life, Death and a Dog Named Bamboo
I sat with her that evening while she was dyingrubbing her back, smoothing her head, whispering that I loved her, trying to be of some small comfort as she snuggled closer, looking up with her mysteriously accepting, somehow understanding brown eyes.
Adjusting herself once more, she half rose, then toppled sideways and simply stopped breathing. She died as a lady ought to be able to diequietly, as easily as possible, in her own bed. In my bed actually. She was Bamboo, my Shar‐pei, and it is difficult to write this even several months later without tears starting to roll.
It was not just that last day, of course. For a bit more than a week, Bamboo had been giving signs of a serious problema heavy doggie cough indicating severe congestion and a firm, stubborn decision not to eat. The kitchen offered a parade of small bowls of her favorite people foods with which I hoped to restore her appetite when she determinedly ignored her regular dog food. She had her choice of cottage cheese, scrambled eggs, ground sirloin, cheddar chunks, ice cream, buttered rice and morea virtual buffet for ants.
After I set each dish out, she would go over to look and sniff admiringly, even wag her tail, but then rather reluctantly return to her favorite resting place, a small rug at the top of the stairs to the front door.
She would only drink a lot of water, bowl after bowl, in which she did also get her medicine, mashed and melted. Late on that last afternoon, however she stopped the drinking, too. I couldn't get her to sip even when I brought the water dish to her or offered the ice cubes she once loved to lick. In her own way, she was saying No.
Lately I have been reflecting again on the experience as a result of having heard some discussion about the death of a woman with whom I once shared friendly commuter chitchat as we trained together into the Loop.
Following a stroke, she had been unconscious, vegetative, tragically for almost as long as I had enjoyed the eight years of Bamboo's delightful companionship. Her husband, I learned, had ultimately gone to court and had been granted permission to remove the feeding tube and let nature take its course. A counteraction to prevent this was filed by some well‐intentioned people; but what I believe as good human and legal sense prevailed. So without the tube feeding, this nice long‐suffering woman finally slipped away to God.
People who oppose the dying being released this way argue that they are being starved to death without the feeding tubes. But I don't buy that, especially after having watched Bamboo decide by some deep natural instinct that it was time for her, first, to stop eating even the treats she loved and, finally, to stop drinking while she waited patiently for what was to come, what was inevitable.
There used to be an advertising slogan: It's not nice to fool Mother Nature. If you believe in God and the promise of eternity, perhaps it is equally not nice to fool dying human bodies into a semblance of living when nature is poised to move them beyond the rim of this life. Nature or God, I mean, and absolutely never, of course, a manipulative Dr. Death.
I don't think my puppy was starving those last few days so much as simply stopping. Simply letting herself be folded into an immutable process. At least this is something to ponder in terms of the will of God overwhelming the hopes of man. I am awed and rather apprehensive and yet somehow comfortable with this conclusion.
A couple of months tops with the tubes and no other reasonable hope, I think I'll tell my kids.
Mary Margaret's words struck a cord with both her sons. Her wishes, neatly laid out in a dusty newspaper, were respected. Mary Margaret entered hospice and died peacefully 2 weeks later.
(Tough Questions on Life, Death and a Dog Named Bamboo originally appeared in the The Catholic New World on July 16, 1993. The article was reprinted with their permission.)
Postscript: The author of the essay (my mother) passed away after a week in hospice care and 7 weeks in hospitals following a stroke. She was a published writer for more than 60 years. For her 61st birthday, my brother and I decided to buy her a wrinkly little puppy to keep her company and bark at anyone who came to her house. It ended up being a terrific watchdog as well as my mom's best friend. The last days with her puppy were translated into the essay, which also helped guide me during my mother's final days. My hope is that she and Bamboo are enjoying the promise of eternity in each other's company.
Patrick Carberry
Her name was Mrs. Carberry, but her readers knew her as Mary Margaret. Two months earlier, she suffered a debilitating stroke that took away her vibrant life. Previously a prolific writer of advice columns and opinion pieces, the blockage of blood to her brain dammed the steady flow of wisdom to her innumerable fans. They never again would benefit from the words of this intelligent, feisty, and self‐proclaimed Cranky Catholic. Unfortunately, I would not know Mary Margaret for her words, but only her numbers: her vital signs, her urine output, her tube feed residuals.
Not able to communicate with us, we wondered did Mrs. Carberry want this tracheostomy that was placed? Did she want this peg tube that fed her continuously? And even if she would have initially agreed to them, would she still want them now? Especially given she was not improving and had little hope for a meaningful recovery.
We posed these difficult questions to her two sons. One son believed that his mother would want an end to these aggressive measures. The other son disagreed; he said his mother would want to make every effort to stay alive.
In the end, Mary Margaret's voice found its way to us and provided us with the answer. She did not tell us in the conventional manner via a lawyer or a living will. Her friends did not come forth and let us know about serious conversations during their afternoon lunches. Instead, Mary Margaret penned it to her audience of devoted readers in a newspaper column written 14 years earlier. Mary Margaret's poignant words were revealed to her doctors by her son who understood its undeniable significance.
Mary Margaret was an essayist in Chicago whose pieces filled many major newspapers and magazines. She had strong opinions on matters large and small, writing articles addressing topics ranging from her Catholic beliefs to gender‐based inequities in the workplace. One article in particular addressed sickness and death and provided her sons the answer they sought. Having witnessed illness strike two loved ones, it was only natural for Mary Margaret to write about it. Her very personal essay was entitled Tough Questions on Life, Death and a Dog Named Bamboo. The words, resurfacing years later, and now having direct meaning to her own life and death, may have been some of the most profound and prophetic words of her career:
Tough Questions on Life, Death and a Dog Named Bamboo
I sat with her that evening while she was dyingrubbing her back, smoothing her head, whispering that I loved her, trying to be of some small comfort as she snuggled closer, looking up with her mysteriously accepting, somehow understanding brown eyes.
Adjusting herself once more, she half rose, then toppled sideways and simply stopped breathing. She died as a lady ought to be able to diequietly, as easily as possible, in her own bed. In my bed actually. She was Bamboo, my Shar‐pei, and it is difficult to write this even several months later without tears starting to roll.
It was not just that last day, of course. For a bit more than a week, Bamboo had been giving signs of a serious problema heavy doggie cough indicating severe congestion and a firm, stubborn decision not to eat. The kitchen offered a parade of small bowls of her favorite people foods with which I hoped to restore her appetite when she determinedly ignored her regular dog food. She had her choice of cottage cheese, scrambled eggs, ground sirloin, cheddar chunks, ice cream, buttered rice and morea virtual buffet for ants.
After I set each dish out, she would go over to look and sniff admiringly, even wag her tail, but then rather reluctantly return to her favorite resting place, a small rug at the top of the stairs to the front door.
She would only drink a lot of water, bowl after bowl, in which she did also get her medicine, mashed and melted. Late on that last afternoon, however she stopped the drinking, too. I couldn't get her to sip even when I brought the water dish to her or offered the ice cubes she once loved to lick. In her own way, she was saying No.
Lately I have been reflecting again on the experience as a result of having heard some discussion about the death of a woman with whom I once shared friendly commuter chitchat as we trained together into the Loop.
Following a stroke, she had been unconscious, vegetative, tragically for almost as long as I had enjoyed the eight years of Bamboo's delightful companionship. Her husband, I learned, had ultimately gone to court and had been granted permission to remove the feeding tube and let nature take its course. A counteraction to prevent this was filed by some well‐intentioned people; but what I believe as good human and legal sense prevailed. So without the tube feeding, this nice long‐suffering woman finally slipped away to God.
People who oppose the dying being released this way argue that they are being starved to death without the feeding tubes. But I don't buy that, especially after having watched Bamboo decide by some deep natural instinct that it was time for her, first, to stop eating even the treats she loved and, finally, to stop drinking while she waited patiently for what was to come, what was inevitable.
There used to be an advertising slogan: It's not nice to fool Mother Nature. If you believe in God and the promise of eternity, perhaps it is equally not nice to fool dying human bodies into a semblance of living when nature is poised to move them beyond the rim of this life. Nature or God, I mean, and absolutely never, of course, a manipulative Dr. Death.
I don't think my puppy was starving those last few days so much as simply stopping. Simply letting herself be folded into an immutable process. At least this is something to ponder in terms of the will of God overwhelming the hopes of man. I am awed and rather apprehensive and yet somehow comfortable with this conclusion.
A couple of months tops with the tubes and no other reasonable hope, I think I'll tell my kids.
Mary Margaret's words struck a cord with both her sons. Her wishes, neatly laid out in a dusty newspaper, were respected. Mary Margaret entered hospice and died peacefully 2 weeks later.
(Tough Questions on Life, Death and a Dog Named Bamboo originally appeared in the The Catholic New World on July 16, 1993. The article was reprinted with their permission.)
Postscript: The author of the essay (my mother) passed away after a week in hospice care and 7 weeks in hospitals following a stroke. She was a published writer for more than 60 years. For her 61st birthday, my brother and I decided to buy her a wrinkly little puppy to keep her company and bark at anyone who came to her house. It ended up being a terrific watchdog as well as my mom's best friend. The last days with her puppy were translated into the essay, which also helped guide me during my mother's final days. My hope is that she and Bamboo are enjoying the promise of eternity in each other's company.
Patrick Carberry
Her name was Mrs. Carberry, but her readers knew her as Mary Margaret. Two months earlier, she suffered a debilitating stroke that took away her vibrant life. Previously a prolific writer of advice columns and opinion pieces, the blockage of blood to her brain dammed the steady flow of wisdom to her innumerable fans. They never again would benefit from the words of this intelligent, feisty, and self‐proclaimed Cranky Catholic. Unfortunately, I would not know Mary Margaret for her words, but only her numbers: her vital signs, her urine output, her tube feed residuals.
Not able to communicate with us, we wondered did Mrs. Carberry want this tracheostomy that was placed? Did she want this peg tube that fed her continuously? And even if she would have initially agreed to them, would she still want them now? Especially given she was not improving and had little hope for a meaningful recovery.
We posed these difficult questions to her two sons. One son believed that his mother would want an end to these aggressive measures. The other son disagreed; he said his mother would want to make every effort to stay alive.
In the end, Mary Margaret's voice found its way to us and provided us with the answer. She did not tell us in the conventional manner via a lawyer or a living will. Her friends did not come forth and let us know about serious conversations during their afternoon lunches. Instead, Mary Margaret penned it to her audience of devoted readers in a newspaper column written 14 years earlier. Mary Margaret's poignant words were revealed to her doctors by her son who understood its undeniable significance.
Mary Margaret was an essayist in Chicago whose pieces filled many major newspapers and magazines. She had strong opinions on matters large and small, writing articles addressing topics ranging from her Catholic beliefs to gender‐based inequities in the workplace. One article in particular addressed sickness and death and provided her sons the answer they sought. Having witnessed illness strike two loved ones, it was only natural for Mary Margaret to write about it. Her very personal essay was entitled Tough Questions on Life, Death and a Dog Named Bamboo. The words, resurfacing years later, and now having direct meaning to her own life and death, may have been some of the most profound and prophetic words of her career:
Tough Questions on Life, Death and a Dog Named Bamboo
I sat with her that evening while she was dyingrubbing her back, smoothing her head, whispering that I loved her, trying to be of some small comfort as she snuggled closer, looking up with her mysteriously accepting, somehow understanding brown eyes.
Adjusting herself once more, she half rose, then toppled sideways and simply stopped breathing. She died as a lady ought to be able to diequietly, as easily as possible, in her own bed. In my bed actually. She was Bamboo, my Shar‐pei, and it is difficult to write this even several months later without tears starting to roll.
It was not just that last day, of course. For a bit more than a week, Bamboo had been giving signs of a serious problema heavy doggie cough indicating severe congestion and a firm, stubborn decision not to eat. The kitchen offered a parade of small bowls of her favorite people foods with which I hoped to restore her appetite when she determinedly ignored her regular dog food. She had her choice of cottage cheese, scrambled eggs, ground sirloin, cheddar chunks, ice cream, buttered rice and morea virtual buffet for ants.
After I set each dish out, she would go over to look and sniff admiringly, even wag her tail, but then rather reluctantly return to her favorite resting place, a small rug at the top of the stairs to the front door.
She would only drink a lot of water, bowl after bowl, in which she did also get her medicine, mashed and melted. Late on that last afternoon, however she stopped the drinking, too. I couldn't get her to sip even when I brought the water dish to her or offered the ice cubes she once loved to lick. In her own way, she was saying No.
Lately I have been reflecting again on the experience as a result of having heard some discussion about the death of a woman with whom I once shared friendly commuter chitchat as we trained together into the Loop.
Following a stroke, she had been unconscious, vegetative, tragically for almost as long as I had enjoyed the eight years of Bamboo's delightful companionship. Her husband, I learned, had ultimately gone to court and had been granted permission to remove the feeding tube and let nature take its course. A counteraction to prevent this was filed by some well‐intentioned people; but what I believe as good human and legal sense prevailed. So without the tube feeding, this nice long‐suffering woman finally slipped away to God.
People who oppose the dying being released this way argue that they are being starved to death without the feeding tubes. But I don't buy that, especially after having watched Bamboo decide by some deep natural instinct that it was time for her, first, to stop eating even the treats she loved and, finally, to stop drinking while she waited patiently for what was to come, what was inevitable.
There used to be an advertising slogan: It's not nice to fool Mother Nature. If you believe in God and the promise of eternity, perhaps it is equally not nice to fool dying human bodies into a semblance of living when nature is poised to move them beyond the rim of this life. Nature or God, I mean, and absolutely never, of course, a manipulative Dr. Death.
I don't think my puppy was starving those last few days so much as simply stopping. Simply letting herself be folded into an immutable process. At least this is something to ponder in terms of the will of God overwhelming the hopes of man. I am awed and rather apprehensive and yet somehow comfortable with this conclusion.
A couple of months tops with the tubes and no other reasonable hope, I think I'll tell my kids.
Mary Margaret's words struck a cord with both her sons. Her wishes, neatly laid out in a dusty newspaper, were respected. Mary Margaret entered hospice and died peacefully 2 weeks later.
(Tough Questions on Life, Death and a Dog Named Bamboo originally appeared in the The Catholic New World on July 16, 1993. The article was reprinted with their permission.)
Postscript: The author of the essay (my mother) passed away after a week in hospice care and 7 weeks in hospitals following a stroke. She was a published writer for more than 60 years. For her 61st birthday, my brother and I decided to buy her a wrinkly little puppy to keep her company and bark at anyone who came to her house. It ended up being a terrific watchdog as well as my mom's best friend. The last days with her puppy were translated into the essay, which also helped guide me during my mother's final days. My hope is that she and Bamboo are enjoying the promise of eternity in each other's company.
Patrick Carberry
Differences in End‐of‐Life Hospital Care for Children
More than 53,000 children 19 years of age or younger died in 2004,1 and more than 40% of these children died while hospitalized.25 Recently, pediatric end‐of‐life (EOL) issues have gained clinical and research attention, primarily focused on children with chronic conditions, ethical dilemmas surrounding childhood death and dying, and the need for interdisciplinary palliative care efforts for dying children and their families.2, 3, 69
Much remains unknown about patterns of EOL hospital care at the national level for all children, both with and without complex chronic conditions. Because a large proportion of childhood mortality occurs during hospitalization, the inpatient setting is a crucial arena for patients and families facing EOL issues. However, little is known about how insurance status and interhospital transfer are associated with patterns of hospitalization and mortality for children while hospitalized, or about hospital charges and lengths of stay for children who die as inpatients versus those who survive to discharge. In addition, although spending on EOL health care in the United States has attracted considerable attention in recent years, the published literature focuses almost exclusively on adult populations.1012
Illuminating the patterns of childhood mortality in hospital settings may inform expanding institutional efforts to address death and dying for children and their families. We conducted an analysis of national patterns of hospitalization over a span of a decade (19922002), in order to characterize sociodemographic and health care factors associated with inpatient mortality, and to examine patterns of hospital resource use related to EOL care. We hypothesized that resource use would be higher for children who died versus those who survived, and would be higher for uninsured versus insured children.13 We also hypothesized that children admitted upon transfer from another hospital would have higher risk of mortality.14
METHODS
Our data source was the National Inpatient Sample (NIS), which is a component of the Healthcare Cost and Utilization Project (HCUP) sponsored by the Agency for Healthcare Research and Quality. The HCUP is a set of databases developed through partnership among health care institutions and federal and state governments.15 The NIS is the largest publicly available all‐payer inpatient database in the United States, and contains de‐identified, patient‐level clinical data included in a typical discharge abstract. For each year, these data reflect hospital stays from between 800 and 1000 institutions sampled to approximate a 20% stratified sample of nonfederal community hospitals, including public hospitals, children's hospitals, and academic medical centers but excluding long‐term hospitals, psychiatric hospitals, and chemical dependency treatment facilities.
We chose the NIS for this analysis because we were interested in the most common diagnoses for hospitalized children. An alternative database, such as the KID (Kids Inpatient Database), is optimal for less commonly seen discharge diagnoses and did not permit a full decade of retrospective analysis.
In order to characterize changes in mortality and health resource utilization related to our research questions, we conducted a comparative cross‐sectional analysis of 3 years of the NIS over the years 1992, 1997, and 2002. For each year of NIS data, discharge‐level weights were provided to permit calculation of national estimates of hospitalization rates standardized to the concurrent national population.15 All inpatient hospital stays of children aged 17 years and younger were selected.
Discharge data were analyzed based on age, sex, payer status, and transfer status on admission. Although transfer status is not often considered in studies of mortality, we expected that it would be associated with mortality, as a potential indicator of disease severity.14 We included only interhospital transfers, and excluded patients transferred from other locations such as long‐term care facilities. We categorized discharges into 5 age groups: newborns, whose hospitalization began at birth; infants up to 1 year of age who were not born during hospitalization; 15 years; 610 years; and 1117 years. This stratification allowed us to separate infants who were admitted from home or from another hospital versus those who were born during hospitalization. Payer groups included Medicaid, private insurance, and uninsured. Medicare and other payers were analyzed, but were present in very small numbers and are not reported.
Outcomes included weighted inpatient mortality rate, weighted mean of length of stay (in days), and weighted mean total hospital charges. For nationally weighted data, lengths of stay and hospital charges are typically reported as means because weighted medians cannot be estimated.16 We compared mortality patterns for patients who were transferred between hospitals versus those who were not, using multivariable logistic regression to identify factors associated with in‐hospital mortality. Of note, transfer status was evaluated from the standpoint of the receiving hospital as children who were admitted upon transfer from another hospital. Thus, our estimates likely underestimate the effects attributed to interhospital transfer, because this evaluation is unilateral and does not include the transferring hospital. The 5 most common principal Diagnosis‐Related Groups (DRGs) upon discharge were compiled for each of the study years for both survivors and decedents. In order to interpret the analyses of discharge‐related hospital charges in constant dollars, we standardized all hospital charges to 2002 US dollars using the Consumer Price Index.17
Statistical analyses included bivariate comparisons of sociodemographic characteristics and the study outcomes, for each of the study years. We also conducted multivariable regression analyses of mortality, comparing effects of sociodemographic variables and transfer status. We conducted all analyses using Stata, version 8 (Stata Corp., College Station, TX), with which we incorporated sample weights to account for the complex stratified sampling of hospitals that comprise the NIS, and to generate variance estimates with which we derived 95% confidence intervals (95% CI). NIS samples included weighted data for 6.2 million discharges in 1992, 7.1 million discharges in 1997, and 7.9 million discharges in 2002. All results are presented using weighted values. The study was funded internally and all analyses were conducted by the authors. The authors had no financial interest in the outcome. The study was exempt from human subjects review as an analysis of de‐identified secondary data.
RESULTS
Study Sample
NIS samples represented between 35 million and 37.8 million discharges nationally in each of the study years. Distributions of discharges across age group, gender, and payer group were similar across the study years (Table 1).
Characteristic | 1992 N = 6,722,647 | 1997 N = 6,365,886 | 2002 N = 6,456,077 |
---|---|---|---|
| |||
Age (%) | |||
Newborn | 60.0 | 63.0 | 65.0 |
Admitted as transfer* | 1.3 | 1.1 | 1.2 |
0‐<1 year | 8.7 | 8.0 | 8.6 |
Admitted as transfer* | 7.6 | 7.2 | 8.8 |
1‐5 years | 11.9 | 11.0 | 9.2 |
Admitted as transfer* | 5.1 | 4.5 | 5.6 |
6‐10 years | 5.5 | 5.0 | 5.0 |
Admitted as transfer* | 4.9 | 4.7 | 5.3 |
11‐17 years | 13.9 | 13.0 | 12.2 |
Admitted as transfer* | 3.1 | 4.2 | 4.8 |
Gender (%) | |||
Female | 49.0 | 49.0 | 49.0 |
Payer (%) | |||
Medicaid | 37.0 | 36.0 | 39.0 |
Admitted as transfer* | 3.3 | 3.0 | 3.4 |
Private | 52.0 | 55.0 | 53.0 |
Admitted as transfer* | 2.3 | 2.3 | 2.4 |
Uninsured | 7.0 | 5.0 | 5.0 |
Admitted as transfer* | 2.4 | 2.4 | 2.4 |
The proportions of patients admitted as transfers between hospitals are shown for each age group, as well as by payer. Non‐newborn infants had the highest rate of transfer for each year studied, compared with the other age groups. Across the study years, transfer status was fairly uniform across payers.
Patterns of Inpatient Mortality
During the study period, overall pediatric inpatient mortality decreased from 32,941 children (0.49% of all child discharges) in 1992 to 25,824 children (0.40%) in 2002, although this was not a statistically significant change. The inpatient mortality rate across all years studied was significantly higher for the non‐newborn infants (<1 years) than for all other age groups in all study years (P <.005) (Table 2). The newborn age group had the second highest mortality rate in all years, and the remaining 3 groups had similar mortality rates.
Age Groups* | Annual Inpatient Mortality Rate | ||
---|---|---|---|
1992 N = 6,722,647 | 1997 N = 6,365,886 | 2002 N = 6,456,077 | |
| |||
Overall | 0.49% | 0.41% | 0.40% |
Newborn | 0.50% | 0.41% | 0.40% |
0‐<1 year | 0.77% | 0.64% | 0.52% |
1‐5 years | 0.43% | 0.34% | 0.33% |
6‐10 years | 0.41% | 0.34% | 0.34% |
11‐17 years | 0.35% | 0.34% | 0.36% |
Payer groups | |||
Medicaid | 0.51% | 0.44% | 0.45% |
Private | 0.38% | 0.34% | 0.33% |
Uninsured | 0.69% | 0.69% | 0.58% |
However, because the majority of child hospitalizations are for newborns, the overall burden of mortality was greatest for newborns in all years studied. In 2002, 68.6% of pediatric inpatient deaths were newborns, 8.2% were non‐newborn infants, 7.7% were 15 years old, 4.2% were 610 years old, and 11.3% were 1117 years old. These findings were similarly distributed across age groups in 1992 and 1997 as well (data not shown).
Inpatient mortality rates also differed significantly by payer in all study years (Table 2). In each year, uninsured children had the highest mortality rates followed by children with Medicaid coverage and children with private health plans. Given the proportions of discharges with coverage by Medicaid versus private plans and the differences in mortality rates, the overall burden of mortality was greatest for children with private coverage in 1992 and 1997, and was equivalent to that of Medicaid (11,292 versus 11,330, respectively) in 2002.
Table 3 presents inpatient mortality rate by age and transfer status. Patients who were admitted on transfer from another acute care hospital had a significantly greater mortality rate for all age groups, compared with patients admitted not on transfer, within the same age group. The strong association of mortality with transfer status remained in multivariable regression analyses, adjusted for age and payer status (data not shown).
Mortality Rate (% of Discharges) | |||
---|---|---|---|
Age Group and Transfer Status | 1992 (95% CI) | 1997 (95% CI) | 2002 (95% CI) |
Newborn | |||
Admitted as transfer | 4.57 (3.56, 5.59) | 4.22 (3.44, 5.00) | 4.75 (3.80, 5.93) |
Admitted not on transfer | 0.45 (0.40, 0.51) | 0.37 (0.33, 0.40) | 0.36 (0.32, 0.40) |
0‐<1 year | |||
Admitted as transfer | 5.05 (3.83, 6.28) | 4.38 (3.59, 5.17) | 2.86 (2.32, 3.53) |
Admitted not on transfer | 0.43 (0.34, 0.50) | 0.35 (0.28, 0.43) | 0.30 (0.23, 0.40) |
1‐5 years | |||
Admitted as transfer | 2.26 (1.61, 2.19) | 1.59 (1.20, 1.98) | 1.33 (0.97, 1.83) |
Admitted not on transfer | 0.33 (0.25, 0.40) | 0.27 (0.22, 0.33) | 0.27 (0.22, 0.33) |
6‐10 years | |||
Admitted as transfer | 2.01 (1.23, 2.96) | 1.48 (0.92, 2.03) | 1.11 (0.83, 1.49) |
Admitted not on transfer | 0.32 (0.26, 0.39) | 0.28 (0.22, 0.34) | 0.29 (0.24, 0.36) |
11‐17 years | |||
Admitted as transfer | 1.87 (1.42, 2.33) | 1.09 (0.81, 1.38) | 1.33 (1.02, 1.73) |
Admitted not on transfer | 0.30 (0.25, 0.35) | 0.30 (0.25, 0.34) | 0.32 (0.27, 0.37) |
DRGs were evaluated based on transfer status, mortality, and study year. The most common DRGs for survivors were generally consistent across years and transfer status: neonate, bronchitis and asthma, pneumonia, esophagitis/gastroenteritis, nutritional and metabolic disturbances, and vaginal delivery. Among decedents, the primary diagnoses also included neonate, but in contrast with survivors were more likely to include traumatic injury, cardiothoracic surgery/medical care (ie, for congenital cardiac/valve disease), respiratory diagnosis with ventilatory support, and craniotomy. DRGs for decedents were consistent across years and transfer status (data available upon request to the authors).
DRGs were also evaluated based by payer status across all 3 study years (data not shown). The most common DRGs showed no meaningful differences in the types of conditions for children who were transferred versus not, across all payer types (including uninsured children).
Length of Stay and Hospital Charges, by Survival, Payer, and Transfer Status
Table 4 illustrates the national patterns of mean length of stay by age, survival, and transfer status. Data for 2002 are shown; the other study years had very similar findings and are available from the authors.
Admitted on Transfer (95% CI) | Admitted Not on Transfer (95% CI) | |||
---|---|---|---|---|
Alive | Died | Alive | Died | |
Age | ||||
Newborn | 16.9 (14.7‐19.0) | 19.6 (15.1‐24.0) | 3.2 (3.0‐3.3) | 8.3 (6.9‐9.7) |
0‐<1year | 11.3 (9.1‐13.0) | 24.8 (18.8‐30.8) | 3.5 (3.2‐3.8) | 20.1 (12.8‐27.5) |
1‐5 years | 4.8 (4.2‐5.6) | 16.0 (8.5‐23.4) | 3.0 (3.4‐4.0) | 12.7 (7.2‐18.2) |
6‐10 years | 6.4 (4.7‐8.2) | 12.9 (4.9‐20.8) | 3.7 (3.4‐4.0) | 13.8 (9.7‐17.8) |
11‐17 years | 8.0 (6.0‐10.0) | 8.8 (5.8‐11.7) | 4.0 (3.7‐4.3) | 10.2 (6.4‐14.0) |
Payer | ||||
Medicaid | 11.4 (9.7‐13.1) | 21.8 (16.2‐27.4) | 3.5 (3.4‐3.7) | 11.2 (9.2‐13.3) |
Private | 9.7 (8.6‐10.7) | 17.1 (13.5‐20.7) | 3.1 (3.0‐3.2) | 9.3 (7.4‐11.1) |
Uninsured | 7.0 (4.8‐9.2) | 5.3 (1.1‐9.5) | 2.8 (2.6‐3.1) | 3.1 (1.2‐5.0) |
Length of stay differed significantly by transfer and survival status, and also varied significantly by insurance coverage. In 2002, among children who were admitted not on transfer, those who died had significantly longer mean length stay than those who survived. Among children admitted as a transfer, for all but non‐newborn infants and those 15 years of age, length of stay did not differ significantly by survival status.
For children covered by Medicaid and private insurance, decedents had significantly longer length of stay compared to survivors, regardless of transfer status. However, this was not the case for uninsured children, for whom those who died and those who survived had statistically indistinguishable lengths of stay, within the transfer/non‐ transfer groups. Findings for 1997 and 1992 were similar (data not shown).
Mean hospital charges are presented in Table 5. For children covered by Medicaid and private insurance, among patients who were admitted not on transfer, those who died had more than 8‐fold greater charges than those who survived. A similar trend was seen for patients admitted on transfer who were covered by Medicaid and private insurance, with more than 3‐fold greater charges for those who died versus those who survived. In contrast, for uninsured children, those who were admitted not on transfer and died had only 3.5‐fold greater charges compared to survivors, and those who were admitted on transfer and died had only 2‐fold greater charges compared to survivors.
Admitted on Transfer (95% CI) | Admitted Not on Transfer (95% CI) | |||
---|---|---|---|---|
Alive | Died | Alive | Died | |
Payer | ||||
Medicaid | 43,123 (34,570‐51,675) | 141,280 (104,881‐177,679) | 8,456 (7,3489‐9,564) | 73,798 (59,71‐87,884) |
Private | 41,037 (33,420‐48,653) | 142,739 (110,122‐175,355) | 7,519 (6,597‐8,441) | 62,195 (50,722‐73,667) |
Uninsured | 21,228 (15,389‐27,068) | 48,036 (28,974‐67,099) | 5,591 (4,372‐6,810) | 19,910 (13,342‐26,479) |
DISCUSSION
Children's Inpatient Mortality
This is the first study of which we are aware that examines EOL hospitalization patterns for children in a national sample, spanning a decade. Our data revealed that the pediatric inpatient mortality rate is consistently highest among children in the non‐newborn infant age group over this time period, and that the burden of mortality is persistently greatest among newborns. These age‐specific findings are consistent with vital statistics published separately for each of the study years regarding overall childhood mortality.1820
This study highlights what many health care providers may not recognize: to meet the needs of the greatest numbers of families with gravely ill children, EOL care efforts must focus on the very youngest. Many of these children may not have chronic conditions, which have been a central focus of many pediatric EOL efforts to date. In fact, the parents of most gravely ill children in the hospital may have had just a few days or hours to prepare to face the loss of their children.
In addition, children admitted on interhospital transfer are significantly more likely to die while hospitalized. This pattern likely represents referral of severely ill children to medical centers that offer tertiary and quaternary specialty care, rather than risks associated with the transfer event itself. Some parents and their children may be far away from home and their closest networks of social support.7 Overall, these findings strongly indicate that EOL efforts will meet the needs of greater proportions of parents if they actively incorporate considerations of age and transfer status as institutions reach out to families in need of support.
Of note, this analysis does not capture children who were discharged into hospice, or long‐term care facilities, or who may have been discharged to home and may have died thereafter. Discharge disposition is known to vary by age, with older children with chronic conditions being more likely to use hospice services compared with infants.8 A recent study suggests that deaths outside the hospital have become increasingly common for older children over time, with the expansion of EOL supportive services in communities to meet the needs of families with gravely ill children.8
Length of Stay, Hospital Charges, and Mortality Related to Insurance Status
In this study, insured children who were admitted and died had significantly longer hospital stays compared to uninsured children who were admitted and died. DRG diagnoses by payer were very similar among children who died, although it is possible that differences in length of stay by payer status may reflect differences in severity of illness at admission and/or processes of care during hospitalization, which could not be fully accounted for using diagnostic codes. Hospitalizations that ended in death were significantly more expensive than hospitalizations in which children survived to discharge, regardless of age, payer status, or transfer status. However, incremental differences in spending for those who died versus those who survived were much greater for children with health insurance than for children without, suggesting greater resource utilization for children with coverage. Resource utilization is reflected largely in length of stay, which explains why our findings for differences in length of stay were echoed so strongly in our findings regarding differences in hospital charges.
Several studies of EOL care for adults have indicated that uninsured patients sustained higher inpatient mortality and lower hospital resource use versus insured adults, across similar diagnoses.13, 2123 Among children, Braveman and colleagues found differences in hospital resource allocation among sick newborns according to insurance coverage that are echoed in the findings of our study.24 Sick newborns without insurance received fewer inpatient services, with statistically significant shorter length of stay and total charges compared to insured newborns. In our study, disparities related to insurance coverage were consistent over the decade considered, and likely indicate ongoing challenges of broad disparities in access to care for children related to insurance coverage in the US health care system. Perhaps the greatest disparity was in mortality itself, which was highest among the uninsured, although the gap in mortality rates by insurance status appeared narrower in 2002 than in the prior study years.
Mortality Rates by Transfer Status
Mortality rates stratified by transfer status revealed that children transferred between hospitals had a significantly higher mortality rate, compared to children admitted not on transfer. Literature evaluating adult intensive care units found that transferred patients have more comorbid conditions, greater severity of illness, and 1.4‐fold to 2.5‐fold higher hospital mortality rates compared to direct admissions.25 Similar challenges face pediatric patients who are transferred to intensive care settings, where children at higher clinical risk have a higher morality rate and utilize greater resources compared with less critically ill children.14 Hospital EOL support personnel must be cognizant of the high mortality rate for transferred patients, and services may need to be adjusted to address the needs of these families. Additionally, further research is needed to better understand and remedy these potential disparities in care for children based on insurance status.
Limitations
This study is potentially limited by the accuracy of hospital discharge data, which may have influenced our outcomes. Further, not all states participate in the NIS; 11 states participated in 1992, 22 states participated in 1997, and 35 states participated in 2002. Although NIS data are weighted to be nationally representative in each year, it is possible that the participating states may have differed in systematic ways from nonparticipating states. However, the external validity of our data with regard to patterns of mortality by age and diagnoses, and the stability of patterns across a span of several years, suggest strongly that our findings are likely robust to these potential biases in this dataset.
As with any hospital resource use data, we are mindful that the distribution of data regarding length of stay and charges are typically right‐skewed, and therefore mean values should be interpreted with caution. In using mean values to test our hypotheses, we have followed the standard method of comparison for nationally weighted data.16
CONCLUSION
This national study of inpatient mortality patterns among US children over the span of a decade presents a new framework of challenges to clinicians and investigators regarding EOL care for children. As health care providers and institutions expand their efforts to meet the needs of severely ill children and their families, such efforts must be cognizant of the high burden of mortality among the youngest children, as well as those who are transferred between hospitals, and children without insurance coverage. These children and their families may require expanded EOL care and support services, beyond those typically available in most hospitals and communities.
APPENDIX
DIAGNOSIS‐RELATED GROUPS BY TRANSFER AND SURVIVAL STATUS
1992 | % | 1997 | % | 2002 | % |
---|---|---|---|---|---|
| |||||
Transferred ‐ Survived | |||||
Neonate* | 26.2 | Neonate* | 23.2 | Neonate* | 24.6 |
Bronchitis and Asthma | 6.4 | Bronchitis and Asthma | 7.4 | Bronchitis and Asthma | 8.0 |
Seizure and Headache | 3.7 | Simple Pneumonia | 3.3 | Seizure and Headache | 4.2 |
Simple Pneumonia | 3.4 | Seizure and Headache | 3.2 | Simple Pneumonia | 3.7 |
Esophagitis and Gastroenteritis | 3.0 | Psychoses | 3.2 | Esophagitis and Gastroenteritis | 3.0 |
Transferred ‐ Died | |||||
Neonate | 35.1 | Neonate | 38.2 | Neonate | 40.5 |
Cardiac Disease and/or Cardiothoracic surgery | 9.6 | Cardiac Disease and/or Cardiothoracic surgery | 12.2 | Cardiac Disease and/or Cardiothoracic surgery | 10.9 |
Respiratory diagnosis with ventilatory support | 6.8 | Respiratory diagnosis with ventilatory support | 7.7 | Respiratory diagnosis with ventilatory support | 7.0 |
Craniotomy | 3.5 | Septicemia | 2.8 | Injury, Poisoning | 2.4 |
Injury, Poisoning | 3.3 | Tracheostomy with ventilatory support | 2.8 | Craniotomy | 2.2 |
Not Transferred ‐ Survived | |||||
Neonate* | 60.6 | Neonate* | 63 | Neonate* | 66.4 |
Bronchitis and Asthma | 4.9 | Bronchitis and Asthma | 5.3 | Bronchitis and Asthma | 4.7 |
Esophagitis and Gastroenteritis | 3.1 | Simple Pneumonia | 2.9 | Simple Pneumonia | 2.5 |
Simple Pneumonia | 2.7 | Esophagitis and Gastroenteritis | 2.6 | Esophagitis and Gastroenteritis | 2.0 |
Vaginal Delivery | 2.2 | Vaginal Delivery | 2.3 | Nutritional and Metabolic Disorder | 1.8 |
Not Transferred ‐ Died | |||||
Neonate | 61.5 | Neonate | 66.2 | Neonate | 69.0 |
Traumatic Coma or Operative Procedure for Traumatic Injury | 3.3 | Traumatic Coma or Operative Procedure for Traumatic Injury | 4.8 | Traumatic Coma or Operative Procedure for Traumatic Injury | 4.7 |
Cardiac Disease and/or Cardiothoracic surgery | 2.9 | Cardiac Disease and/or Cardiothoracic surgery | 2.7 | Respiratory diagnosis with ventilatory support | 2.7 |
Craniotomy | 2.3 | Respiratory diagnosis with ventilatory support | 2.5 | Craniotomy | 2.4 |
Respiratory diagnosis with ventilatory support | 2.0 | Septicemia | 1.4 | Septicemia | 1.2 |
- Annual summary of vital statistics: 2005.Pediatrics.2007;119(2):345–360. , , , , , .
- Circumstances surrounding the deaths of hospitalized children: opportunities for pediatric palliative care.Pediatrics.2004;114(3):e361–e366. , , , , , .
- Characteristics of deaths occurring in children's hospitals: implications for supportive care services.Pediatrics.2002;109(5):887–893. , , , , , .
- Declining severity adjusted mortality: evidence of improving neonatal intensive care.Pediatrics.1998;102(4):893–899. , , , , , .
- Use of intensive care at the end of life in the United States: an epidemiologic study.Crit Care Med.2004;32(3):638–643. , , , et al.
- Cancer‐related deaths in children and adolescents.J Palliat Med.2005;8(1):86–95. , , , , .
- Where do children with complex chronic conditions die? Patterns in Washington State, 1980‐1998.Pediatrics.2002;109(4):656–660. , , .
- Deaths attributed to pediatric complex chronic conditions: national trends and implications for supportive care services.Pediatrics.2001;107(6):e99. , , , , , .
- Medical end‐of‐life decisions for children in the Netherlands.Arch Pediatr Adolescent Med.005;159(9):802–809. , , , et al.
- Medicare beneficiaries' costs of care in the last year of life.Health Affairs.2001;20(4):188–195. , , , .
- Medicare Beneficiaries' Costs and Use of Care in the Last Year of Life.Washington, DC:MedPAC;2000. , , , , .
- Trends in Medicare payments in the last year of life.N Engl J Med.1993;328(15):1092–1096. , .
- Comparing uninsured and privately insured hospital patients: admission severity, health outcomes and resource use.Health Serv Manage Res.2001;14(3):203–210. , , .
- Characteristics and outcomes of interhospital transfers from level II to level I pediatric intensive care units.Pediatr Crit Care Med.2006;7(6):536–540. , , , et al.
- Agency for Healthcare Research and Quality. National Inpatient Sample (NIS). Healthcare Cost and Utilization Project (HCUP). http://www.hcup‐us.ahrq.gov/nisoverview.jsp. Accessed August 26,2008.
- Agency for Healthcare Research and Quality, . Healthcare Cost and Utilization Project H CUP. Care of Children and Adolescents in U.S. Hospitals. HCUP Fact Book No. 4, Publication No. 04‐0004. http://www.ahrq.gov/data/hcup/factbk4/. Accessed August 26,2008.
- U.S. Department of Labor, Bureau of Labor Statistics. Consumer Price Index.ftp://ftp.bls.gov/pub/special.requests/cpi/cpiai.txt. Accessed August 26,2008.
- Annual summary of vital statistics‐‐2002.Pediatrics.2003;112(6):1215–1230. , , , .
- Annual summary of vital statistics‐‐1996.Pediatrics.1997;100(6):905–918. , , , , .
- Annual summary of vital statistics‐‐1992.Pediatrics.1993;92(6):743–754. .
- Acutely injured patients with trauma in Massachusetts: differences in care and mortality, by insurance status.Am J Publ Health.1994;84(10):1605–1608. , .
- Comparison of uninsured and privately insured hospital patients. Condition on admission, resource use, and outcome.JAMA.1991;265(3):374–379. , , .
- Inequities in hospital care, the Massachusetts experience.Inquiry.1991;28(3):255–262. , .
- Differences in hospital resource allocation among sick newborns according to insurance coverage.JAMA.1991;266(23):3300–3308. , , , .
- Accepting critically ill transfer patients: adverse effect on a referral center's outcome and benchmark measures. [summary for patients in Ann Intern Med. 2003;138(11):I42; PMID: 12779311].Ann Intern Med.2003;138(11):882–890. , , , , .
More than 53,000 children 19 years of age or younger died in 2004,1 and more than 40% of these children died while hospitalized.25 Recently, pediatric end‐of‐life (EOL) issues have gained clinical and research attention, primarily focused on children with chronic conditions, ethical dilemmas surrounding childhood death and dying, and the need for interdisciplinary palliative care efforts for dying children and their families.2, 3, 69
Much remains unknown about patterns of EOL hospital care at the national level for all children, both with and without complex chronic conditions. Because a large proportion of childhood mortality occurs during hospitalization, the inpatient setting is a crucial arena for patients and families facing EOL issues. However, little is known about how insurance status and interhospital transfer are associated with patterns of hospitalization and mortality for children while hospitalized, or about hospital charges and lengths of stay for children who die as inpatients versus those who survive to discharge. In addition, although spending on EOL health care in the United States has attracted considerable attention in recent years, the published literature focuses almost exclusively on adult populations.1012
Illuminating the patterns of childhood mortality in hospital settings may inform expanding institutional efforts to address death and dying for children and their families. We conducted an analysis of national patterns of hospitalization over a span of a decade (19922002), in order to characterize sociodemographic and health care factors associated with inpatient mortality, and to examine patterns of hospital resource use related to EOL care. We hypothesized that resource use would be higher for children who died versus those who survived, and would be higher for uninsured versus insured children.13 We also hypothesized that children admitted upon transfer from another hospital would have higher risk of mortality.14
METHODS
Our data source was the National Inpatient Sample (NIS), which is a component of the Healthcare Cost and Utilization Project (HCUP) sponsored by the Agency for Healthcare Research and Quality. The HCUP is a set of databases developed through partnership among health care institutions and federal and state governments.15 The NIS is the largest publicly available all‐payer inpatient database in the United States, and contains de‐identified, patient‐level clinical data included in a typical discharge abstract. For each year, these data reflect hospital stays from between 800 and 1000 institutions sampled to approximate a 20% stratified sample of nonfederal community hospitals, including public hospitals, children's hospitals, and academic medical centers but excluding long‐term hospitals, psychiatric hospitals, and chemical dependency treatment facilities.
We chose the NIS for this analysis because we were interested in the most common diagnoses for hospitalized children. An alternative database, such as the KID (Kids Inpatient Database), is optimal for less commonly seen discharge diagnoses and did not permit a full decade of retrospective analysis.
In order to characterize changes in mortality and health resource utilization related to our research questions, we conducted a comparative cross‐sectional analysis of 3 years of the NIS over the years 1992, 1997, and 2002. For each year of NIS data, discharge‐level weights were provided to permit calculation of national estimates of hospitalization rates standardized to the concurrent national population.15 All inpatient hospital stays of children aged 17 years and younger were selected.
Discharge data were analyzed based on age, sex, payer status, and transfer status on admission. Although transfer status is not often considered in studies of mortality, we expected that it would be associated with mortality, as a potential indicator of disease severity.14 We included only interhospital transfers, and excluded patients transferred from other locations such as long‐term care facilities. We categorized discharges into 5 age groups: newborns, whose hospitalization began at birth; infants up to 1 year of age who were not born during hospitalization; 15 years; 610 years; and 1117 years. This stratification allowed us to separate infants who were admitted from home or from another hospital versus those who were born during hospitalization. Payer groups included Medicaid, private insurance, and uninsured. Medicare and other payers were analyzed, but were present in very small numbers and are not reported.
Outcomes included weighted inpatient mortality rate, weighted mean of length of stay (in days), and weighted mean total hospital charges. For nationally weighted data, lengths of stay and hospital charges are typically reported as means because weighted medians cannot be estimated.16 We compared mortality patterns for patients who were transferred between hospitals versus those who were not, using multivariable logistic regression to identify factors associated with in‐hospital mortality. Of note, transfer status was evaluated from the standpoint of the receiving hospital as children who were admitted upon transfer from another hospital. Thus, our estimates likely underestimate the effects attributed to interhospital transfer, because this evaluation is unilateral and does not include the transferring hospital. The 5 most common principal Diagnosis‐Related Groups (DRGs) upon discharge were compiled for each of the study years for both survivors and decedents. In order to interpret the analyses of discharge‐related hospital charges in constant dollars, we standardized all hospital charges to 2002 US dollars using the Consumer Price Index.17
Statistical analyses included bivariate comparisons of sociodemographic characteristics and the study outcomes, for each of the study years. We also conducted multivariable regression analyses of mortality, comparing effects of sociodemographic variables and transfer status. We conducted all analyses using Stata, version 8 (Stata Corp., College Station, TX), with which we incorporated sample weights to account for the complex stratified sampling of hospitals that comprise the NIS, and to generate variance estimates with which we derived 95% confidence intervals (95% CI). NIS samples included weighted data for 6.2 million discharges in 1992, 7.1 million discharges in 1997, and 7.9 million discharges in 2002. All results are presented using weighted values. The study was funded internally and all analyses were conducted by the authors. The authors had no financial interest in the outcome. The study was exempt from human subjects review as an analysis of de‐identified secondary data.
RESULTS
Study Sample
NIS samples represented between 35 million and 37.8 million discharges nationally in each of the study years. Distributions of discharges across age group, gender, and payer group were similar across the study years (Table 1).
Characteristic | 1992 N = 6,722,647 | 1997 N = 6,365,886 | 2002 N = 6,456,077 |
---|---|---|---|
| |||
Age (%) | |||
Newborn | 60.0 | 63.0 | 65.0 |
Admitted as transfer* | 1.3 | 1.1 | 1.2 |
0‐<1 year | 8.7 | 8.0 | 8.6 |
Admitted as transfer* | 7.6 | 7.2 | 8.8 |
1‐5 years | 11.9 | 11.0 | 9.2 |
Admitted as transfer* | 5.1 | 4.5 | 5.6 |
6‐10 years | 5.5 | 5.0 | 5.0 |
Admitted as transfer* | 4.9 | 4.7 | 5.3 |
11‐17 years | 13.9 | 13.0 | 12.2 |
Admitted as transfer* | 3.1 | 4.2 | 4.8 |
Gender (%) | |||
Female | 49.0 | 49.0 | 49.0 |
Payer (%) | |||
Medicaid | 37.0 | 36.0 | 39.0 |
Admitted as transfer* | 3.3 | 3.0 | 3.4 |
Private | 52.0 | 55.0 | 53.0 |
Admitted as transfer* | 2.3 | 2.3 | 2.4 |
Uninsured | 7.0 | 5.0 | 5.0 |
Admitted as transfer* | 2.4 | 2.4 | 2.4 |
The proportions of patients admitted as transfers between hospitals are shown for each age group, as well as by payer. Non‐newborn infants had the highest rate of transfer for each year studied, compared with the other age groups. Across the study years, transfer status was fairly uniform across payers.
Patterns of Inpatient Mortality
During the study period, overall pediatric inpatient mortality decreased from 32,941 children (0.49% of all child discharges) in 1992 to 25,824 children (0.40%) in 2002, although this was not a statistically significant change. The inpatient mortality rate across all years studied was significantly higher for the non‐newborn infants (<1 years) than for all other age groups in all study years (P <.005) (Table 2). The newborn age group had the second highest mortality rate in all years, and the remaining 3 groups had similar mortality rates.
Age Groups* | Annual Inpatient Mortality Rate | ||
---|---|---|---|
1992 N = 6,722,647 | 1997 N = 6,365,886 | 2002 N = 6,456,077 | |
| |||
Overall | 0.49% | 0.41% | 0.40% |
Newborn | 0.50% | 0.41% | 0.40% |
0‐<1 year | 0.77% | 0.64% | 0.52% |
1‐5 years | 0.43% | 0.34% | 0.33% |
6‐10 years | 0.41% | 0.34% | 0.34% |
11‐17 years | 0.35% | 0.34% | 0.36% |
Payer groups | |||
Medicaid | 0.51% | 0.44% | 0.45% |
Private | 0.38% | 0.34% | 0.33% |
Uninsured | 0.69% | 0.69% | 0.58% |
However, because the majority of child hospitalizations are for newborns, the overall burden of mortality was greatest for newborns in all years studied. In 2002, 68.6% of pediatric inpatient deaths were newborns, 8.2% were non‐newborn infants, 7.7% were 15 years old, 4.2% were 610 years old, and 11.3% were 1117 years old. These findings were similarly distributed across age groups in 1992 and 1997 as well (data not shown).
Inpatient mortality rates also differed significantly by payer in all study years (Table 2). In each year, uninsured children had the highest mortality rates followed by children with Medicaid coverage and children with private health plans. Given the proportions of discharges with coverage by Medicaid versus private plans and the differences in mortality rates, the overall burden of mortality was greatest for children with private coverage in 1992 and 1997, and was equivalent to that of Medicaid (11,292 versus 11,330, respectively) in 2002.
Table 3 presents inpatient mortality rate by age and transfer status. Patients who were admitted on transfer from another acute care hospital had a significantly greater mortality rate for all age groups, compared with patients admitted not on transfer, within the same age group. The strong association of mortality with transfer status remained in multivariable regression analyses, adjusted for age and payer status (data not shown).
Mortality Rate (% of Discharges) | |||
---|---|---|---|
Age Group and Transfer Status | 1992 (95% CI) | 1997 (95% CI) | 2002 (95% CI) |
Newborn | |||
Admitted as transfer | 4.57 (3.56, 5.59) | 4.22 (3.44, 5.00) | 4.75 (3.80, 5.93) |
Admitted not on transfer | 0.45 (0.40, 0.51) | 0.37 (0.33, 0.40) | 0.36 (0.32, 0.40) |
0‐<1 year | |||
Admitted as transfer | 5.05 (3.83, 6.28) | 4.38 (3.59, 5.17) | 2.86 (2.32, 3.53) |
Admitted not on transfer | 0.43 (0.34, 0.50) | 0.35 (0.28, 0.43) | 0.30 (0.23, 0.40) |
1‐5 years | |||
Admitted as transfer | 2.26 (1.61, 2.19) | 1.59 (1.20, 1.98) | 1.33 (0.97, 1.83) |
Admitted not on transfer | 0.33 (0.25, 0.40) | 0.27 (0.22, 0.33) | 0.27 (0.22, 0.33) |
6‐10 years | |||
Admitted as transfer | 2.01 (1.23, 2.96) | 1.48 (0.92, 2.03) | 1.11 (0.83, 1.49) |
Admitted not on transfer | 0.32 (0.26, 0.39) | 0.28 (0.22, 0.34) | 0.29 (0.24, 0.36) |
11‐17 years | |||
Admitted as transfer | 1.87 (1.42, 2.33) | 1.09 (0.81, 1.38) | 1.33 (1.02, 1.73) |
Admitted not on transfer | 0.30 (0.25, 0.35) | 0.30 (0.25, 0.34) | 0.32 (0.27, 0.37) |
DRGs were evaluated based on transfer status, mortality, and study year. The most common DRGs for survivors were generally consistent across years and transfer status: neonate, bronchitis and asthma, pneumonia, esophagitis/gastroenteritis, nutritional and metabolic disturbances, and vaginal delivery. Among decedents, the primary diagnoses also included neonate, but in contrast with survivors were more likely to include traumatic injury, cardiothoracic surgery/medical care (ie, for congenital cardiac/valve disease), respiratory diagnosis with ventilatory support, and craniotomy. DRGs for decedents were consistent across years and transfer status (data available upon request to the authors).
DRGs were also evaluated based by payer status across all 3 study years (data not shown). The most common DRGs showed no meaningful differences in the types of conditions for children who were transferred versus not, across all payer types (including uninsured children).
Length of Stay and Hospital Charges, by Survival, Payer, and Transfer Status
Table 4 illustrates the national patterns of mean length of stay by age, survival, and transfer status. Data for 2002 are shown; the other study years had very similar findings and are available from the authors.
Admitted on Transfer (95% CI) | Admitted Not on Transfer (95% CI) | |||
---|---|---|---|---|
Alive | Died | Alive | Died | |
Age | ||||
Newborn | 16.9 (14.7‐19.0) | 19.6 (15.1‐24.0) | 3.2 (3.0‐3.3) | 8.3 (6.9‐9.7) |
0‐<1year | 11.3 (9.1‐13.0) | 24.8 (18.8‐30.8) | 3.5 (3.2‐3.8) | 20.1 (12.8‐27.5) |
1‐5 years | 4.8 (4.2‐5.6) | 16.0 (8.5‐23.4) | 3.0 (3.4‐4.0) | 12.7 (7.2‐18.2) |
6‐10 years | 6.4 (4.7‐8.2) | 12.9 (4.9‐20.8) | 3.7 (3.4‐4.0) | 13.8 (9.7‐17.8) |
11‐17 years | 8.0 (6.0‐10.0) | 8.8 (5.8‐11.7) | 4.0 (3.7‐4.3) | 10.2 (6.4‐14.0) |
Payer | ||||
Medicaid | 11.4 (9.7‐13.1) | 21.8 (16.2‐27.4) | 3.5 (3.4‐3.7) | 11.2 (9.2‐13.3) |
Private | 9.7 (8.6‐10.7) | 17.1 (13.5‐20.7) | 3.1 (3.0‐3.2) | 9.3 (7.4‐11.1) |
Uninsured | 7.0 (4.8‐9.2) | 5.3 (1.1‐9.5) | 2.8 (2.6‐3.1) | 3.1 (1.2‐5.0) |
Length of stay differed significantly by transfer and survival status, and also varied significantly by insurance coverage. In 2002, among children who were admitted not on transfer, those who died had significantly longer mean length stay than those who survived. Among children admitted as a transfer, for all but non‐newborn infants and those 15 years of age, length of stay did not differ significantly by survival status.
For children covered by Medicaid and private insurance, decedents had significantly longer length of stay compared to survivors, regardless of transfer status. However, this was not the case for uninsured children, for whom those who died and those who survived had statistically indistinguishable lengths of stay, within the transfer/non‐ transfer groups. Findings for 1997 and 1992 were similar (data not shown).
Mean hospital charges are presented in Table 5. For children covered by Medicaid and private insurance, among patients who were admitted not on transfer, those who died had more than 8‐fold greater charges than those who survived. A similar trend was seen for patients admitted on transfer who were covered by Medicaid and private insurance, with more than 3‐fold greater charges for those who died versus those who survived. In contrast, for uninsured children, those who were admitted not on transfer and died had only 3.5‐fold greater charges compared to survivors, and those who were admitted on transfer and died had only 2‐fold greater charges compared to survivors.
Admitted on Transfer (95% CI) | Admitted Not on Transfer (95% CI) | |||
---|---|---|---|---|
Alive | Died | Alive | Died | |
Payer | ||||
Medicaid | 43,123 (34,570‐51,675) | 141,280 (104,881‐177,679) | 8,456 (7,3489‐9,564) | 73,798 (59,71‐87,884) |
Private | 41,037 (33,420‐48,653) | 142,739 (110,122‐175,355) | 7,519 (6,597‐8,441) | 62,195 (50,722‐73,667) |
Uninsured | 21,228 (15,389‐27,068) | 48,036 (28,974‐67,099) | 5,591 (4,372‐6,810) | 19,910 (13,342‐26,479) |
DISCUSSION
Children's Inpatient Mortality
This is the first study of which we are aware that examines EOL hospitalization patterns for children in a national sample, spanning a decade. Our data revealed that the pediatric inpatient mortality rate is consistently highest among children in the non‐newborn infant age group over this time period, and that the burden of mortality is persistently greatest among newborns. These age‐specific findings are consistent with vital statistics published separately for each of the study years regarding overall childhood mortality.1820
This study highlights what many health care providers may not recognize: to meet the needs of the greatest numbers of families with gravely ill children, EOL care efforts must focus on the very youngest. Many of these children may not have chronic conditions, which have been a central focus of many pediatric EOL efforts to date. In fact, the parents of most gravely ill children in the hospital may have had just a few days or hours to prepare to face the loss of their children.
In addition, children admitted on interhospital transfer are significantly more likely to die while hospitalized. This pattern likely represents referral of severely ill children to medical centers that offer tertiary and quaternary specialty care, rather than risks associated with the transfer event itself. Some parents and their children may be far away from home and their closest networks of social support.7 Overall, these findings strongly indicate that EOL efforts will meet the needs of greater proportions of parents if they actively incorporate considerations of age and transfer status as institutions reach out to families in need of support.
Of note, this analysis does not capture children who were discharged into hospice, or long‐term care facilities, or who may have been discharged to home and may have died thereafter. Discharge disposition is known to vary by age, with older children with chronic conditions being more likely to use hospice services compared with infants.8 A recent study suggests that deaths outside the hospital have become increasingly common for older children over time, with the expansion of EOL supportive services in communities to meet the needs of families with gravely ill children.8
Length of Stay, Hospital Charges, and Mortality Related to Insurance Status
In this study, insured children who were admitted and died had significantly longer hospital stays compared to uninsured children who were admitted and died. DRG diagnoses by payer were very similar among children who died, although it is possible that differences in length of stay by payer status may reflect differences in severity of illness at admission and/or processes of care during hospitalization, which could not be fully accounted for using diagnostic codes. Hospitalizations that ended in death were significantly more expensive than hospitalizations in which children survived to discharge, regardless of age, payer status, or transfer status. However, incremental differences in spending for those who died versus those who survived were much greater for children with health insurance than for children without, suggesting greater resource utilization for children with coverage. Resource utilization is reflected largely in length of stay, which explains why our findings for differences in length of stay were echoed so strongly in our findings regarding differences in hospital charges.
Several studies of EOL care for adults have indicated that uninsured patients sustained higher inpatient mortality and lower hospital resource use versus insured adults, across similar diagnoses.13, 2123 Among children, Braveman and colleagues found differences in hospital resource allocation among sick newborns according to insurance coverage that are echoed in the findings of our study.24 Sick newborns without insurance received fewer inpatient services, with statistically significant shorter length of stay and total charges compared to insured newborns. In our study, disparities related to insurance coverage were consistent over the decade considered, and likely indicate ongoing challenges of broad disparities in access to care for children related to insurance coverage in the US health care system. Perhaps the greatest disparity was in mortality itself, which was highest among the uninsured, although the gap in mortality rates by insurance status appeared narrower in 2002 than in the prior study years.
Mortality Rates by Transfer Status
Mortality rates stratified by transfer status revealed that children transferred between hospitals had a significantly higher mortality rate, compared to children admitted not on transfer. Literature evaluating adult intensive care units found that transferred patients have more comorbid conditions, greater severity of illness, and 1.4‐fold to 2.5‐fold higher hospital mortality rates compared to direct admissions.25 Similar challenges face pediatric patients who are transferred to intensive care settings, where children at higher clinical risk have a higher morality rate and utilize greater resources compared with less critically ill children.14 Hospital EOL support personnel must be cognizant of the high mortality rate for transferred patients, and services may need to be adjusted to address the needs of these families. Additionally, further research is needed to better understand and remedy these potential disparities in care for children based on insurance status.
Limitations
This study is potentially limited by the accuracy of hospital discharge data, which may have influenced our outcomes. Further, not all states participate in the NIS; 11 states participated in 1992, 22 states participated in 1997, and 35 states participated in 2002. Although NIS data are weighted to be nationally representative in each year, it is possible that the participating states may have differed in systematic ways from nonparticipating states. However, the external validity of our data with regard to patterns of mortality by age and diagnoses, and the stability of patterns across a span of several years, suggest strongly that our findings are likely robust to these potential biases in this dataset.
As with any hospital resource use data, we are mindful that the distribution of data regarding length of stay and charges are typically right‐skewed, and therefore mean values should be interpreted with caution. In using mean values to test our hypotheses, we have followed the standard method of comparison for nationally weighted data.16
CONCLUSION
This national study of inpatient mortality patterns among US children over the span of a decade presents a new framework of challenges to clinicians and investigators regarding EOL care for children. As health care providers and institutions expand their efforts to meet the needs of severely ill children and their families, such efforts must be cognizant of the high burden of mortality among the youngest children, as well as those who are transferred between hospitals, and children without insurance coverage. These children and their families may require expanded EOL care and support services, beyond those typically available in most hospitals and communities.
APPENDIX
DIAGNOSIS‐RELATED GROUPS BY TRANSFER AND SURVIVAL STATUS
1992 | % | 1997 | % | 2002 | % |
---|---|---|---|---|---|
| |||||
Transferred ‐ Survived | |||||
Neonate* | 26.2 | Neonate* | 23.2 | Neonate* | 24.6 |
Bronchitis and Asthma | 6.4 | Bronchitis and Asthma | 7.4 | Bronchitis and Asthma | 8.0 |
Seizure and Headache | 3.7 | Simple Pneumonia | 3.3 | Seizure and Headache | 4.2 |
Simple Pneumonia | 3.4 | Seizure and Headache | 3.2 | Simple Pneumonia | 3.7 |
Esophagitis and Gastroenteritis | 3.0 | Psychoses | 3.2 | Esophagitis and Gastroenteritis | 3.0 |
Transferred ‐ Died | |||||
Neonate | 35.1 | Neonate | 38.2 | Neonate | 40.5 |
Cardiac Disease and/or Cardiothoracic surgery | 9.6 | Cardiac Disease and/or Cardiothoracic surgery | 12.2 | Cardiac Disease and/or Cardiothoracic surgery | 10.9 |
Respiratory diagnosis with ventilatory support | 6.8 | Respiratory diagnosis with ventilatory support | 7.7 | Respiratory diagnosis with ventilatory support | 7.0 |
Craniotomy | 3.5 | Septicemia | 2.8 | Injury, Poisoning | 2.4 |
Injury, Poisoning | 3.3 | Tracheostomy with ventilatory support | 2.8 | Craniotomy | 2.2 |
Not Transferred ‐ Survived | |||||
Neonate* | 60.6 | Neonate* | 63 | Neonate* | 66.4 |
Bronchitis and Asthma | 4.9 | Bronchitis and Asthma | 5.3 | Bronchitis and Asthma | 4.7 |
Esophagitis and Gastroenteritis | 3.1 | Simple Pneumonia | 2.9 | Simple Pneumonia | 2.5 |
Simple Pneumonia | 2.7 | Esophagitis and Gastroenteritis | 2.6 | Esophagitis and Gastroenteritis | 2.0 |
Vaginal Delivery | 2.2 | Vaginal Delivery | 2.3 | Nutritional and Metabolic Disorder | 1.8 |
Not Transferred ‐ Died | |||||
Neonate | 61.5 | Neonate | 66.2 | Neonate | 69.0 |
Traumatic Coma or Operative Procedure for Traumatic Injury | 3.3 | Traumatic Coma or Operative Procedure for Traumatic Injury | 4.8 | Traumatic Coma or Operative Procedure for Traumatic Injury | 4.7 |
Cardiac Disease and/or Cardiothoracic surgery | 2.9 | Cardiac Disease and/or Cardiothoracic surgery | 2.7 | Respiratory diagnosis with ventilatory support | 2.7 |
Craniotomy | 2.3 | Respiratory diagnosis with ventilatory support | 2.5 | Craniotomy | 2.4 |
Respiratory diagnosis with ventilatory support | 2.0 | Septicemia | 1.4 | Septicemia | 1.2 |
More than 53,000 children 19 years of age or younger died in 2004,1 and more than 40% of these children died while hospitalized.25 Recently, pediatric end‐of‐life (EOL) issues have gained clinical and research attention, primarily focused on children with chronic conditions, ethical dilemmas surrounding childhood death and dying, and the need for interdisciplinary palliative care efforts for dying children and their families.2, 3, 69
Much remains unknown about patterns of EOL hospital care at the national level for all children, both with and without complex chronic conditions. Because a large proportion of childhood mortality occurs during hospitalization, the inpatient setting is a crucial arena for patients and families facing EOL issues. However, little is known about how insurance status and interhospital transfer are associated with patterns of hospitalization and mortality for children while hospitalized, or about hospital charges and lengths of stay for children who die as inpatients versus those who survive to discharge. In addition, although spending on EOL health care in the United States has attracted considerable attention in recent years, the published literature focuses almost exclusively on adult populations.1012
Illuminating the patterns of childhood mortality in hospital settings may inform expanding institutional efforts to address death and dying for children and their families. We conducted an analysis of national patterns of hospitalization over a span of a decade (19922002), in order to characterize sociodemographic and health care factors associated with inpatient mortality, and to examine patterns of hospital resource use related to EOL care. We hypothesized that resource use would be higher for children who died versus those who survived, and would be higher for uninsured versus insured children.13 We also hypothesized that children admitted upon transfer from another hospital would have higher risk of mortality.14
METHODS
Our data source was the National Inpatient Sample (NIS), which is a component of the Healthcare Cost and Utilization Project (HCUP) sponsored by the Agency for Healthcare Research and Quality. The HCUP is a set of databases developed through partnership among health care institutions and federal and state governments.15 The NIS is the largest publicly available all‐payer inpatient database in the United States, and contains de‐identified, patient‐level clinical data included in a typical discharge abstract. For each year, these data reflect hospital stays from between 800 and 1000 institutions sampled to approximate a 20% stratified sample of nonfederal community hospitals, including public hospitals, children's hospitals, and academic medical centers but excluding long‐term hospitals, psychiatric hospitals, and chemical dependency treatment facilities.
We chose the NIS for this analysis because we were interested in the most common diagnoses for hospitalized children. An alternative database, such as the KID (Kids Inpatient Database), is optimal for less commonly seen discharge diagnoses and did not permit a full decade of retrospective analysis.
In order to characterize changes in mortality and health resource utilization related to our research questions, we conducted a comparative cross‐sectional analysis of 3 years of the NIS over the years 1992, 1997, and 2002. For each year of NIS data, discharge‐level weights were provided to permit calculation of national estimates of hospitalization rates standardized to the concurrent national population.15 All inpatient hospital stays of children aged 17 years and younger were selected.
Discharge data were analyzed based on age, sex, payer status, and transfer status on admission. Although transfer status is not often considered in studies of mortality, we expected that it would be associated with mortality, as a potential indicator of disease severity.14 We included only interhospital transfers, and excluded patients transferred from other locations such as long‐term care facilities. We categorized discharges into 5 age groups: newborns, whose hospitalization began at birth; infants up to 1 year of age who were not born during hospitalization; 15 years; 610 years; and 1117 years. This stratification allowed us to separate infants who were admitted from home or from another hospital versus those who were born during hospitalization. Payer groups included Medicaid, private insurance, and uninsured. Medicare and other payers were analyzed, but were present in very small numbers and are not reported.
Outcomes included weighted inpatient mortality rate, weighted mean of length of stay (in days), and weighted mean total hospital charges. For nationally weighted data, lengths of stay and hospital charges are typically reported as means because weighted medians cannot be estimated.16 We compared mortality patterns for patients who were transferred between hospitals versus those who were not, using multivariable logistic regression to identify factors associated with in‐hospital mortality. Of note, transfer status was evaluated from the standpoint of the receiving hospital as children who were admitted upon transfer from another hospital. Thus, our estimates likely underestimate the effects attributed to interhospital transfer, because this evaluation is unilateral and does not include the transferring hospital. The 5 most common principal Diagnosis‐Related Groups (DRGs) upon discharge were compiled for each of the study years for both survivors and decedents. In order to interpret the analyses of discharge‐related hospital charges in constant dollars, we standardized all hospital charges to 2002 US dollars using the Consumer Price Index.17
Statistical analyses included bivariate comparisons of sociodemographic characteristics and the study outcomes, for each of the study years. We also conducted multivariable regression analyses of mortality, comparing effects of sociodemographic variables and transfer status. We conducted all analyses using Stata, version 8 (Stata Corp., College Station, TX), with which we incorporated sample weights to account for the complex stratified sampling of hospitals that comprise the NIS, and to generate variance estimates with which we derived 95% confidence intervals (95% CI). NIS samples included weighted data for 6.2 million discharges in 1992, 7.1 million discharges in 1997, and 7.9 million discharges in 2002. All results are presented using weighted values. The study was funded internally and all analyses were conducted by the authors. The authors had no financial interest in the outcome. The study was exempt from human subjects review as an analysis of de‐identified secondary data.
RESULTS
Study Sample
NIS samples represented between 35 million and 37.8 million discharges nationally in each of the study years. Distributions of discharges across age group, gender, and payer group were similar across the study years (Table 1).
Characteristic | 1992 N = 6,722,647 | 1997 N = 6,365,886 | 2002 N = 6,456,077 |
---|---|---|---|
| |||
Age (%) | |||
Newborn | 60.0 | 63.0 | 65.0 |
Admitted as transfer* | 1.3 | 1.1 | 1.2 |
0‐<1 year | 8.7 | 8.0 | 8.6 |
Admitted as transfer* | 7.6 | 7.2 | 8.8 |
1‐5 years | 11.9 | 11.0 | 9.2 |
Admitted as transfer* | 5.1 | 4.5 | 5.6 |
6‐10 years | 5.5 | 5.0 | 5.0 |
Admitted as transfer* | 4.9 | 4.7 | 5.3 |
11‐17 years | 13.9 | 13.0 | 12.2 |
Admitted as transfer* | 3.1 | 4.2 | 4.8 |
Gender (%) | |||
Female | 49.0 | 49.0 | 49.0 |
Payer (%) | |||
Medicaid | 37.0 | 36.0 | 39.0 |
Admitted as transfer* | 3.3 | 3.0 | 3.4 |
Private | 52.0 | 55.0 | 53.0 |
Admitted as transfer* | 2.3 | 2.3 | 2.4 |
Uninsured | 7.0 | 5.0 | 5.0 |
Admitted as transfer* | 2.4 | 2.4 | 2.4 |
The proportions of patients admitted as transfers between hospitals are shown for each age group, as well as by payer. Non‐newborn infants had the highest rate of transfer for each year studied, compared with the other age groups. Across the study years, transfer status was fairly uniform across payers.
Patterns of Inpatient Mortality
During the study period, overall pediatric inpatient mortality decreased from 32,941 children (0.49% of all child discharges) in 1992 to 25,824 children (0.40%) in 2002, although this was not a statistically significant change. The inpatient mortality rate across all years studied was significantly higher for the non‐newborn infants (<1 years) than for all other age groups in all study years (P <.005) (Table 2). The newborn age group had the second highest mortality rate in all years, and the remaining 3 groups had similar mortality rates.
Age Groups* | Annual Inpatient Mortality Rate | ||
---|---|---|---|
1992 N = 6,722,647 | 1997 N = 6,365,886 | 2002 N = 6,456,077 | |
| |||
Overall | 0.49% | 0.41% | 0.40% |
Newborn | 0.50% | 0.41% | 0.40% |
0‐<1 year | 0.77% | 0.64% | 0.52% |
1‐5 years | 0.43% | 0.34% | 0.33% |
6‐10 years | 0.41% | 0.34% | 0.34% |
11‐17 years | 0.35% | 0.34% | 0.36% |
Payer groups | |||
Medicaid | 0.51% | 0.44% | 0.45% |
Private | 0.38% | 0.34% | 0.33% |
Uninsured | 0.69% | 0.69% | 0.58% |
However, because the majority of child hospitalizations are for newborns, the overall burden of mortality was greatest for newborns in all years studied. In 2002, 68.6% of pediatric inpatient deaths were newborns, 8.2% were non‐newborn infants, 7.7% were 15 years old, 4.2% were 610 years old, and 11.3% were 1117 years old. These findings were similarly distributed across age groups in 1992 and 1997 as well (data not shown).
Inpatient mortality rates also differed significantly by payer in all study years (Table 2). In each year, uninsured children had the highest mortality rates followed by children with Medicaid coverage and children with private health plans. Given the proportions of discharges with coverage by Medicaid versus private plans and the differences in mortality rates, the overall burden of mortality was greatest for children with private coverage in 1992 and 1997, and was equivalent to that of Medicaid (11,292 versus 11,330, respectively) in 2002.
Table 3 presents inpatient mortality rate by age and transfer status. Patients who were admitted on transfer from another acute care hospital had a significantly greater mortality rate for all age groups, compared with patients admitted not on transfer, within the same age group. The strong association of mortality with transfer status remained in multivariable regression analyses, adjusted for age and payer status (data not shown).
Mortality Rate (% of Discharges) | |||
---|---|---|---|
Age Group and Transfer Status | 1992 (95% CI) | 1997 (95% CI) | 2002 (95% CI) |
Newborn | |||
Admitted as transfer | 4.57 (3.56, 5.59) | 4.22 (3.44, 5.00) | 4.75 (3.80, 5.93) |
Admitted not on transfer | 0.45 (0.40, 0.51) | 0.37 (0.33, 0.40) | 0.36 (0.32, 0.40) |
0‐<1 year | |||
Admitted as transfer | 5.05 (3.83, 6.28) | 4.38 (3.59, 5.17) | 2.86 (2.32, 3.53) |
Admitted not on transfer | 0.43 (0.34, 0.50) | 0.35 (0.28, 0.43) | 0.30 (0.23, 0.40) |
1‐5 years | |||
Admitted as transfer | 2.26 (1.61, 2.19) | 1.59 (1.20, 1.98) | 1.33 (0.97, 1.83) |
Admitted not on transfer | 0.33 (0.25, 0.40) | 0.27 (0.22, 0.33) | 0.27 (0.22, 0.33) |
6‐10 years | |||
Admitted as transfer | 2.01 (1.23, 2.96) | 1.48 (0.92, 2.03) | 1.11 (0.83, 1.49) |
Admitted not on transfer | 0.32 (0.26, 0.39) | 0.28 (0.22, 0.34) | 0.29 (0.24, 0.36) |
11‐17 years | |||
Admitted as transfer | 1.87 (1.42, 2.33) | 1.09 (0.81, 1.38) | 1.33 (1.02, 1.73) |
Admitted not on transfer | 0.30 (0.25, 0.35) | 0.30 (0.25, 0.34) | 0.32 (0.27, 0.37) |
DRGs were evaluated based on transfer status, mortality, and study year. The most common DRGs for survivors were generally consistent across years and transfer status: neonate, bronchitis and asthma, pneumonia, esophagitis/gastroenteritis, nutritional and metabolic disturbances, and vaginal delivery. Among decedents, the primary diagnoses also included neonate, but in contrast with survivors were more likely to include traumatic injury, cardiothoracic surgery/medical care (ie, for congenital cardiac/valve disease), respiratory diagnosis with ventilatory support, and craniotomy. DRGs for decedents were consistent across years and transfer status (data available upon request to the authors).
DRGs were also evaluated based by payer status across all 3 study years (data not shown). The most common DRGs showed no meaningful differences in the types of conditions for children who were transferred versus not, across all payer types (including uninsured children).
Length of Stay and Hospital Charges, by Survival, Payer, and Transfer Status
Table 4 illustrates the national patterns of mean length of stay by age, survival, and transfer status. Data for 2002 are shown; the other study years had very similar findings and are available from the authors.
Admitted on Transfer (95% CI) | Admitted Not on Transfer (95% CI) | |||
---|---|---|---|---|
Alive | Died | Alive | Died | |
Age | ||||
Newborn | 16.9 (14.7‐19.0) | 19.6 (15.1‐24.0) | 3.2 (3.0‐3.3) | 8.3 (6.9‐9.7) |
0‐<1year | 11.3 (9.1‐13.0) | 24.8 (18.8‐30.8) | 3.5 (3.2‐3.8) | 20.1 (12.8‐27.5) |
1‐5 years | 4.8 (4.2‐5.6) | 16.0 (8.5‐23.4) | 3.0 (3.4‐4.0) | 12.7 (7.2‐18.2) |
6‐10 years | 6.4 (4.7‐8.2) | 12.9 (4.9‐20.8) | 3.7 (3.4‐4.0) | 13.8 (9.7‐17.8) |
11‐17 years | 8.0 (6.0‐10.0) | 8.8 (5.8‐11.7) | 4.0 (3.7‐4.3) | 10.2 (6.4‐14.0) |
Payer | ||||
Medicaid | 11.4 (9.7‐13.1) | 21.8 (16.2‐27.4) | 3.5 (3.4‐3.7) | 11.2 (9.2‐13.3) |
Private | 9.7 (8.6‐10.7) | 17.1 (13.5‐20.7) | 3.1 (3.0‐3.2) | 9.3 (7.4‐11.1) |
Uninsured | 7.0 (4.8‐9.2) | 5.3 (1.1‐9.5) | 2.8 (2.6‐3.1) | 3.1 (1.2‐5.0) |
Length of stay differed significantly by transfer and survival status, and also varied significantly by insurance coverage. In 2002, among children who were admitted not on transfer, those who died had significantly longer mean length stay than those who survived. Among children admitted as a transfer, for all but non‐newborn infants and those 15 years of age, length of stay did not differ significantly by survival status.
For children covered by Medicaid and private insurance, decedents had significantly longer length of stay compared to survivors, regardless of transfer status. However, this was not the case for uninsured children, for whom those who died and those who survived had statistically indistinguishable lengths of stay, within the transfer/non‐ transfer groups. Findings for 1997 and 1992 were similar (data not shown).
Mean hospital charges are presented in Table 5. For children covered by Medicaid and private insurance, among patients who were admitted not on transfer, those who died had more than 8‐fold greater charges than those who survived. A similar trend was seen for patients admitted on transfer who were covered by Medicaid and private insurance, with more than 3‐fold greater charges for those who died versus those who survived. In contrast, for uninsured children, those who were admitted not on transfer and died had only 3.5‐fold greater charges compared to survivors, and those who were admitted on transfer and died had only 2‐fold greater charges compared to survivors.
Admitted on Transfer (95% CI) | Admitted Not on Transfer (95% CI) | |||
---|---|---|---|---|
Alive | Died | Alive | Died | |
Payer | ||||
Medicaid | 43,123 (34,570‐51,675) | 141,280 (104,881‐177,679) | 8,456 (7,3489‐9,564) | 73,798 (59,71‐87,884) |
Private | 41,037 (33,420‐48,653) | 142,739 (110,122‐175,355) | 7,519 (6,597‐8,441) | 62,195 (50,722‐73,667) |
Uninsured | 21,228 (15,389‐27,068) | 48,036 (28,974‐67,099) | 5,591 (4,372‐6,810) | 19,910 (13,342‐26,479) |
DISCUSSION
Children's Inpatient Mortality
This is the first study of which we are aware that examines EOL hospitalization patterns for children in a national sample, spanning a decade. Our data revealed that the pediatric inpatient mortality rate is consistently highest among children in the non‐newborn infant age group over this time period, and that the burden of mortality is persistently greatest among newborns. These age‐specific findings are consistent with vital statistics published separately for each of the study years regarding overall childhood mortality.1820
This study highlights what many health care providers may not recognize: to meet the needs of the greatest numbers of families with gravely ill children, EOL care efforts must focus on the very youngest. Many of these children may not have chronic conditions, which have been a central focus of many pediatric EOL efforts to date. In fact, the parents of most gravely ill children in the hospital may have had just a few days or hours to prepare to face the loss of their children.
In addition, children admitted on interhospital transfer are significantly more likely to die while hospitalized. This pattern likely represents referral of severely ill children to medical centers that offer tertiary and quaternary specialty care, rather than risks associated with the transfer event itself. Some parents and their children may be far away from home and their closest networks of social support.7 Overall, these findings strongly indicate that EOL efforts will meet the needs of greater proportions of parents if they actively incorporate considerations of age and transfer status as institutions reach out to families in need of support.
Of note, this analysis does not capture children who were discharged into hospice, or long‐term care facilities, or who may have been discharged to home and may have died thereafter. Discharge disposition is known to vary by age, with older children with chronic conditions being more likely to use hospice services compared with infants.8 A recent study suggests that deaths outside the hospital have become increasingly common for older children over time, with the expansion of EOL supportive services in communities to meet the needs of families with gravely ill children.8
Length of Stay, Hospital Charges, and Mortality Related to Insurance Status
In this study, insured children who were admitted and died had significantly longer hospital stays compared to uninsured children who were admitted and died. DRG diagnoses by payer were very similar among children who died, although it is possible that differences in length of stay by payer status may reflect differences in severity of illness at admission and/or processes of care during hospitalization, which could not be fully accounted for using diagnostic codes. Hospitalizations that ended in death were significantly more expensive than hospitalizations in which children survived to discharge, regardless of age, payer status, or transfer status. However, incremental differences in spending for those who died versus those who survived were much greater for children with health insurance than for children without, suggesting greater resource utilization for children with coverage. Resource utilization is reflected largely in length of stay, which explains why our findings for differences in length of stay were echoed so strongly in our findings regarding differences in hospital charges.
Several studies of EOL care for adults have indicated that uninsured patients sustained higher inpatient mortality and lower hospital resource use versus insured adults, across similar diagnoses.13, 2123 Among children, Braveman and colleagues found differences in hospital resource allocation among sick newborns according to insurance coverage that are echoed in the findings of our study.24 Sick newborns without insurance received fewer inpatient services, with statistically significant shorter length of stay and total charges compared to insured newborns. In our study, disparities related to insurance coverage were consistent over the decade considered, and likely indicate ongoing challenges of broad disparities in access to care for children related to insurance coverage in the US health care system. Perhaps the greatest disparity was in mortality itself, which was highest among the uninsured, although the gap in mortality rates by insurance status appeared narrower in 2002 than in the prior study years.
Mortality Rates by Transfer Status
Mortality rates stratified by transfer status revealed that children transferred between hospitals had a significantly higher mortality rate, compared to children admitted not on transfer. Literature evaluating adult intensive care units found that transferred patients have more comorbid conditions, greater severity of illness, and 1.4‐fold to 2.5‐fold higher hospital mortality rates compared to direct admissions.25 Similar challenges face pediatric patients who are transferred to intensive care settings, where children at higher clinical risk have a higher morality rate and utilize greater resources compared with less critically ill children.14 Hospital EOL support personnel must be cognizant of the high mortality rate for transferred patients, and services may need to be adjusted to address the needs of these families. Additionally, further research is needed to better understand and remedy these potential disparities in care for children based on insurance status.
Limitations
This study is potentially limited by the accuracy of hospital discharge data, which may have influenced our outcomes. Further, not all states participate in the NIS; 11 states participated in 1992, 22 states participated in 1997, and 35 states participated in 2002. Although NIS data are weighted to be nationally representative in each year, it is possible that the participating states may have differed in systematic ways from nonparticipating states. However, the external validity of our data with regard to patterns of mortality by age and diagnoses, and the stability of patterns across a span of several years, suggest strongly that our findings are likely robust to these potential biases in this dataset.
As with any hospital resource use data, we are mindful that the distribution of data regarding length of stay and charges are typically right‐skewed, and therefore mean values should be interpreted with caution. In using mean values to test our hypotheses, we have followed the standard method of comparison for nationally weighted data.16
CONCLUSION
This national study of inpatient mortality patterns among US children over the span of a decade presents a new framework of challenges to clinicians and investigators regarding EOL care for children. As health care providers and institutions expand their efforts to meet the needs of severely ill children and their families, such efforts must be cognizant of the high burden of mortality among the youngest children, as well as those who are transferred between hospitals, and children without insurance coverage. These children and their families may require expanded EOL care and support services, beyond those typically available in most hospitals and communities.
APPENDIX
DIAGNOSIS‐RELATED GROUPS BY TRANSFER AND SURVIVAL STATUS
1992 | % | 1997 | % | 2002 | % |
---|---|---|---|---|---|
| |||||
Transferred ‐ Survived | |||||
Neonate* | 26.2 | Neonate* | 23.2 | Neonate* | 24.6 |
Bronchitis and Asthma | 6.4 | Bronchitis and Asthma | 7.4 | Bronchitis and Asthma | 8.0 |
Seizure and Headache | 3.7 | Simple Pneumonia | 3.3 | Seizure and Headache | 4.2 |
Simple Pneumonia | 3.4 | Seizure and Headache | 3.2 | Simple Pneumonia | 3.7 |
Esophagitis and Gastroenteritis | 3.0 | Psychoses | 3.2 | Esophagitis and Gastroenteritis | 3.0 |
Transferred ‐ Died | |||||
Neonate | 35.1 | Neonate | 38.2 | Neonate | 40.5 |
Cardiac Disease and/or Cardiothoracic surgery | 9.6 | Cardiac Disease and/or Cardiothoracic surgery | 12.2 | Cardiac Disease and/or Cardiothoracic surgery | 10.9 |
Respiratory diagnosis with ventilatory support | 6.8 | Respiratory diagnosis with ventilatory support | 7.7 | Respiratory diagnosis with ventilatory support | 7.0 |
Craniotomy | 3.5 | Septicemia | 2.8 | Injury, Poisoning | 2.4 |
Injury, Poisoning | 3.3 | Tracheostomy with ventilatory support | 2.8 | Craniotomy | 2.2 |
Not Transferred ‐ Survived | |||||
Neonate* | 60.6 | Neonate* | 63 | Neonate* | 66.4 |
Bronchitis and Asthma | 4.9 | Bronchitis and Asthma | 5.3 | Bronchitis and Asthma | 4.7 |
Esophagitis and Gastroenteritis | 3.1 | Simple Pneumonia | 2.9 | Simple Pneumonia | 2.5 |
Simple Pneumonia | 2.7 | Esophagitis and Gastroenteritis | 2.6 | Esophagitis and Gastroenteritis | 2.0 |
Vaginal Delivery | 2.2 | Vaginal Delivery | 2.3 | Nutritional and Metabolic Disorder | 1.8 |
Not Transferred ‐ Died | |||||
Neonate | 61.5 | Neonate | 66.2 | Neonate | 69.0 |
Traumatic Coma or Operative Procedure for Traumatic Injury | 3.3 | Traumatic Coma or Operative Procedure for Traumatic Injury | 4.8 | Traumatic Coma or Operative Procedure for Traumatic Injury | 4.7 |
Cardiac Disease and/or Cardiothoracic surgery | 2.9 | Cardiac Disease and/or Cardiothoracic surgery | 2.7 | Respiratory diagnosis with ventilatory support | 2.7 |
Craniotomy | 2.3 | Respiratory diagnosis with ventilatory support | 2.5 | Craniotomy | 2.4 |
Respiratory diagnosis with ventilatory support | 2.0 | Septicemia | 1.4 | Septicemia | 1.2 |
- Annual summary of vital statistics: 2005.Pediatrics.2007;119(2):345–360. , , , , , .
- Circumstances surrounding the deaths of hospitalized children: opportunities for pediatric palliative care.Pediatrics.2004;114(3):e361–e366. , , , , , .
- Characteristics of deaths occurring in children's hospitals: implications for supportive care services.Pediatrics.2002;109(5):887–893. , , , , , .
- Declining severity adjusted mortality: evidence of improving neonatal intensive care.Pediatrics.1998;102(4):893–899. , , , , , .
- Use of intensive care at the end of life in the United States: an epidemiologic study.Crit Care Med.2004;32(3):638–643. , , , et al.
- Cancer‐related deaths in children and adolescents.J Palliat Med.2005;8(1):86–95. , , , , .
- Where do children with complex chronic conditions die? Patterns in Washington State, 1980‐1998.Pediatrics.2002;109(4):656–660. , , .
- Deaths attributed to pediatric complex chronic conditions: national trends and implications for supportive care services.Pediatrics.2001;107(6):e99. , , , , , .
- Medical end‐of‐life decisions for children in the Netherlands.Arch Pediatr Adolescent Med.005;159(9):802–809. , , , et al.
- Medicare beneficiaries' costs of care in the last year of life.Health Affairs.2001;20(4):188–195. , , , .
- Medicare Beneficiaries' Costs and Use of Care in the Last Year of Life.Washington, DC:MedPAC;2000. , , , , .
- Trends in Medicare payments in the last year of life.N Engl J Med.1993;328(15):1092–1096. , .
- Comparing uninsured and privately insured hospital patients: admission severity, health outcomes and resource use.Health Serv Manage Res.2001;14(3):203–210. , , .
- Characteristics and outcomes of interhospital transfers from level II to level I pediatric intensive care units.Pediatr Crit Care Med.2006;7(6):536–540. , , , et al.
- Agency for Healthcare Research and Quality. National Inpatient Sample (NIS). Healthcare Cost and Utilization Project (HCUP). http://www.hcup‐us.ahrq.gov/nisoverview.jsp. Accessed August 26,2008.
- Agency for Healthcare Research and Quality, . Healthcare Cost and Utilization Project H CUP. Care of Children and Adolescents in U.S. Hospitals. HCUP Fact Book No. 4, Publication No. 04‐0004. http://www.ahrq.gov/data/hcup/factbk4/. Accessed August 26,2008.
- U.S. Department of Labor, Bureau of Labor Statistics. Consumer Price Index.ftp://ftp.bls.gov/pub/special.requests/cpi/cpiai.txt. Accessed August 26,2008.
- Annual summary of vital statistics‐‐2002.Pediatrics.2003;112(6):1215–1230. , , , .
- Annual summary of vital statistics‐‐1996.Pediatrics.1997;100(6):905–918. , , , , .
- Annual summary of vital statistics‐‐1992.Pediatrics.1993;92(6):743–754. .
- Acutely injured patients with trauma in Massachusetts: differences in care and mortality, by insurance status.Am J Publ Health.1994;84(10):1605–1608. , .
- Comparison of uninsured and privately insured hospital patients. Condition on admission, resource use, and outcome.JAMA.1991;265(3):374–379. , , .
- Inequities in hospital care, the Massachusetts experience.Inquiry.1991;28(3):255–262. , .
- Differences in hospital resource allocation among sick newborns according to insurance coverage.JAMA.1991;266(23):3300–3308. , , , .
- Accepting critically ill transfer patients: adverse effect on a referral center's outcome and benchmark measures. [summary for patients in Ann Intern Med. 2003;138(11):I42; PMID: 12779311].Ann Intern Med.2003;138(11):882–890. , , , , .
- Annual summary of vital statistics: 2005.Pediatrics.2007;119(2):345–360. , , , , , .
- Circumstances surrounding the deaths of hospitalized children: opportunities for pediatric palliative care.Pediatrics.2004;114(3):e361–e366. , , , , , .
- Characteristics of deaths occurring in children's hospitals: implications for supportive care services.Pediatrics.2002;109(5):887–893. , , , , , .
- Declining severity adjusted mortality: evidence of improving neonatal intensive care.Pediatrics.1998;102(4):893–899. , , , , , .
- Use of intensive care at the end of life in the United States: an epidemiologic study.Crit Care Med.2004;32(3):638–643. , , , et al.
- Cancer‐related deaths in children and adolescents.J Palliat Med.2005;8(1):86–95. , , , , .
- Where do children with complex chronic conditions die? Patterns in Washington State, 1980‐1998.Pediatrics.2002;109(4):656–660. , , .
- Deaths attributed to pediatric complex chronic conditions: national trends and implications for supportive care services.Pediatrics.2001;107(6):e99. , , , , , .
- Medical end‐of‐life decisions for children in the Netherlands.Arch Pediatr Adolescent Med.005;159(9):802–809. , , , et al.
- Medicare beneficiaries' costs of care in the last year of life.Health Affairs.2001;20(4):188–195. , , , .
- Medicare Beneficiaries' Costs and Use of Care in the Last Year of Life.Washington, DC:MedPAC;2000. , , , , .
- Trends in Medicare payments in the last year of life.N Engl J Med.1993;328(15):1092–1096. , .
- Comparing uninsured and privately insured hospital patients: admission severity, health outcomes and resource use.Health Serv Manage Res.2001;14(3):203–210. , , .
- Characteristics and outcomes of interhospital transfers from level II to level I pediatric intensive care units.Pediatr Crit Care Med.2006;7(6):536–540. , , , et al.
- Agency for Healthcare Research and Quality. National Inpatient Sample (NIS). Healthcare Cost and Utilization Project (HCUP). http://www.hcup‐us.ahrq.gov/nisoverview.jsp. Accessed August 26,2008.
- Agency for Healthcare Research and Quality, . Healthcare Cost and Utilization Project H CUP. Care of Children and Adolescents in U.S. Hospitals. HCUP Fact Book No. 4, Publication No. 04‐0004. http://www.ahrq.gov/data/hcup/factbk4/. Accessed August 26,2008.
- U.S. Department of Labor, Bureau of Labor Statistics. Consumer Price Index.ftp://ftp.bls.gov/pub/special.requests/cpi/cpiai.txt. Accessed August 26,2008.
- Annual summary of vital statistics‐‐2002.Pediatrics.2003;112(6):1215–1230. , , , .
- Annual summary of vital statistics‐‐1996.Pediatrics.1997;100(6):905–918. , , , , .
- Annual summary of vital statistics‐‐1992.Pediatrics.1993;92(6):743–754. .
- Acutely injured patients with trauma in Massachusetts: differences in care and mortality, by insurance status.Am J Publ Health.1994;84(10):1605–1608. , .
- Comparison of uninsured and privately insured hospital patients. Condition on admission, resource use, and outcome.JAMA.1991;265(3):374–379. , , .
- Inequities in hospital care, the Massachusetts experience.Inquiry.1991;28(3):255–262. , .
- Differences in hospital resource allocation among sick newborns according to insurance coverage.JAMA.1991;266(23):3300–3308. , , , .
- Accepting critically ill transfer patients: adverse effect on a referral center's outcome and benchmark measures. [summary for patients in Ann Intern Med. 2003;138(11):I42; PMID: 12779311].Ann Intern Med.2003;138(11):882–890. , , , , .
Copyright © 2008 Society of Hospital Medicine
Surgical Comanagement
With the rapid advance of medicine to its present‐day status in which it evokes the aid of all the natural sciences, an individual is no more able to undertake the more intricate problems alone, without the aid and cooperation of colleagues having special training in each of the various clinical and laboratory branches, than he would be today to make an automobile alone.1
It is ironic that our specialty of hospital‐based medicine grew out of the soil of managed care and a renewed emphasis on generalism.2 Historical precedence clearly confirms the virtue of specialization and multidisciplinary care. Taken in this context, hospitalists have been comanagers from the very start, working with primary care physicians. The unprecedented growth of hospitalists in the United States has been accelerated by forces that pulled generalists out of the hospital and off the hospital wardsnamely the expensive inefficiency of trying to be in 2 places at 1 time. Faced with an expanding scope of practice and increasing outpatient volumes coupled with declining reimbursements, primary care physicians (PCPs) recognized the need to share their patients with inpatient comanagers.
Today, the surgeon is faced with many of the same pressures experienced by PCPs. Surgical productivity, efficiency, and quality are highly valued, yet require the surgeon to be in 2 places at 1 time. In the past, many surgeons in teaching hospitals relied on surgical residents to manage uncomplicated presurgical and postsurgical care and collaborated with internists for more difficult problems. Now, surgical residents are limited by work‐hour restrictions imposed by the Accreditation Council for Graduate Medical Education,3 reducing their ability to respond to patients outside the operating room. Perhaps more importantly, surgical patients today continue to increase in age and complexity, with a projected 50% rise in surgery‐related costs and a 100% rise in surgical complications in the next 2 decades.4 An experienced comanager of surgical patients that does not rely on PCPs or the surgical education system makes great practical and economic sense, and is a natural evolution of the hospitalist concept and skill set. Hospital medicine core competencies highlight perioperative medicine as a body of knowledge and practice germane to hospitalists. In fact, it specifically states that hospitalists should strive to engage in efforts to improve the efficiency and quality of care through innovative models, which may include comanagement of surgical patients in the perioperative period.5
CONSULTATION VERSUS COMANAGEMENT
Historically, in academic settings surgeons and medical practitioners have collaborated via the framework of consultation. If a surgeon needed assistance with uncontrolled diabetes or blood pressure, he or she called the internist to make recommendations on appropriate treatment. If the internist was faced with a potential surgical issue, he or she consulted the surgeon for their evaluation and opinion. In today's chaotic hospital environment, this collaborative framework has obvious inefficiencies. By definition, the consultation involves a formal request, which demands seamless communication that often does not exist. Next, the consultant reviews the chart, evaluates the patient, reviews pertinent clinical data, and provides an assessment with recommendations for management and care. How and whether these recommendations are enacted may be explicitly defined by the requesting service, but often it is not, and a delay in execution of recommendations potentially ensues. An observational cohort study showed that patients receiving medical consultation were no more likely to have tight glycemic control, perioperative beta‐blockers administration, or venous thromboembolism (VTE) prophylaxis; however, patients receiving consultation had a longer length of stay and higher costs of care.6 Comanagement represents a patient care referral, not consultation. A comanager is requested at the outset, but subsequently plays a much more active role, which may involve daily or twice daily visits, writing progress notes and orders, assessing and managing acute issues, and facilitating discharge planning and care transitions. Despite the ability to facilitate care, the basis for comanagement should be the same as for specialty consultation.
In contrast to academic settings, comanagement by PCPs and medical subspecialists occurs routinely in community hospitals. This model works best for patients with few problems who are followed closely by a single comanager, typically the PCP. However, complex patients with multiple comorbidities may decompensate without an attentive and experienced PCP, or wind up with numerous subspecialists making recommendations and writing orders in a disorganized fashion. The extreme of this situation is an unsystematic and inefficient management by committee, where medical specialists pick and choose an area of comanagement, without clear boundaries between the various team members. This approach is fraught with pitfalls in communication and may lead to conflicting recommendations or false assumptions among team members, further increasing patient morbidity.
In both academic and community settings, comanagement by a hospitalist offers advantages of consistent availability and proactive perioperative expertise, both in diagnosing and treating relevant problems and in recognizing the need for subspecialty involvement, thus improving efficiency of care. Although some health care systems may consider automatic patient care referrals to hospitalists for all surgical patients, this approach should be discouraged unless the patient population demands specialty involvement. Best practice would identify comorbid surgical patients during the outpatient preoperative process and then hardwire the patient care referral to the hospitalist upon surgical admission.
COMANAGEMENT MAKES SENSE
The multidisciplinary nature of comanagement can streamline individual patient care from the moment the decision for surgery is made. Preoperative assessment and management by the hospitalist can uncover risks from known conditions requiring optimization; identify new, undiagnosed conditions affecting the perioperative period; and initiate prophylactic and therapeutic regimens that reduce the chances for postoperative complications. Specific examples may include beta‐blockers in higher risk patients, anticoagulation management, and VTE prophylaxis.
The comanaging hospitalist ensures that these strategies are implemented, tailors them to the individual patient, and diagnoses and treats complications promptly when they occur. In addition, hospitalist comanagers can be more involved to facilitate patient transitions to posthospital care venues; this might involve communication with patients, families, case managers, and PCPs, among others. Ultimately, the investment of the comanaging hospitalist in the surgical patient is much greater in both scope and time. This may be expected to improve patient care efficiency, reduce length of stay, and may decrease overall complications. In addition, this investment is often recognized by the other important members of the care team, including nursing, case management, and patients and families, thus improving both patient and nursing satisfaction ratings.
AVAILABLE DATA ON THE BENEFITS OF COMANAGEMENT
Early studies on comanagement focused on orthopedic surgery and geriatric collaboration. Zuckerman et al.7 studied the effects of an interdisciplinary team approach to the hip fracture patient, entitled the Geriatric Hip Fracture Program (GHFP), in the mid‐1980s. They compared 431 patients admitted under the care of the GHFP for surgical repair of hip fracture between 1985 and 1988 with 60 historical controls at the same institution prior to the inception of the program. GHFP patients were evaluated by an orthopedic surgeon and a consulting internist or geriatrician. In addition to therapy service evaluations, each patient was screened by an ophthalmologist for visual impairment, a psychiatrist for preexisting cognitive dysfunction and depression, a social worker, and a case manager. GHFP patients had fewer postoperative complications, fewer intensive care unit transfers for acute medical issues, better ambulatory status and distance ambulated at discharge, and nonsignificant trends toward decreased length of stay and increased likelihood of return to home. A more recent prospective observational study of patients with hip fracture in Australia8 compared a 4‐year period of geriatric comanagement of 447 patients with hip fracture with 3 years of historical control patients (n = 504) prior to the institution of the comanagement service. Postoperative medical complications, mortality, and 6‐month readmission rates were significantly lower in the geriatric comanagement cohort. No differences in median length of hospital stay or in discharge destination were noted. The proportion of patients receiving anti‐osteoporotic therapy (calcium, vitamin D, and bisphosphonates) increased from 12% to 93% after the institution of comanagement. Also, the proportion of patients prescribed pharmacologic VTE prophylaxis increased from 63% to 94%, and symptomatic VTE events (deep vein thrombosis or PE) decreased from 4.6% to 1.3% after implementation. In another geriatrician comanagement study, Marcantonio et al.9 performed a randomized trial in patients with hip fracture comparing geriatric comanagement with a structured treatment care protocol to usual care. Although length of stay was unchanged and costs of care were not reported, geriatric comanagement significantly reduced the number and severity of episodes of delirium.
Macpherson et al.10 studied the effect of internist comanagement of 165 cardiothoracic surgery patients in the Minneaoplis Veteran's Affairs Medical Center in 1990. They found that, compared with the prior year, the implementation of internist comanagement was associated with hospital stays of 6 days shorter length, lower use of resources such as lab and radiology, and a trend toward decreased mortality. Huddleston et al.11 conducted a randomized controlled trial of 526 patients undergoing elective total hip or knee arthroplasty, comparing a comanagement hospitalist‐orthopedic team with standard orthopedic surgery care and internal medicine consultation as needed. Despite comparison to the standard of tightly managed care protocols in elective hip and knee arthroplasty, patients comanaged by hospitalists were more likely to be discharged without postoperative complications, and were ready for discharge half a day sooner when adjusting for skilled facility bed availability. No difference in mortality rates or total cost of care was noted between the 2 models. However, nurses and surgeons both strongly preferred the comanagement model, with providers reporting that care was prompt and coordinated, and there was an enhanced ease of providing care. In a second study, the authors from the same institution12 studied 466 patients over 65 years of age admitted for surgical repair of hip fracture. Patients in the comanagement group went to surgery faster, were discharged sooner after surgery, and had an overall lower length of stay. No differences were noted in inpatient mortality, 30‐day readmission rates, or complication rates. Delirium was diagnosed more often in the comanagement group, but a diagnosis of delirium was associated with an earlier discharge after surgery. This may reflect greater attention to the presence of delirium, better documentation, and more prompt treatment.
Preoperative testing centers staffed by anesthesiologists have been shown to positively impact surgical care.1315 However, there has been little study to specifically evaluate the role of medical comanagement in the preoperative setting. Jaffer et al.16 demonstrated a reduction in postoperative pulmonary complications in a mixed surgical population by utilizing a structured preoperative assessment and management program of hospitalists.
COMANAGEMENT SATISFACTION
Surgical comanagement has been reported to improve surgeon and nurse satisfaction ratings.11 Salerno et al.,17 in their study of consultation preferences of surgeons, internists and family physicians, confirmed that surgeons, especially orthopedic surgeons, favor the comanagement model more than the traditional consultation model. This is not surprising as surgeons in the comanagement model may be expected to spend more time in the operating room as opposed to the hospital floors, thus improving patient access to timely surgery and reducing cancellations and delays. Ultimately, the comanagement model may result in a competitive advantage over traditional care. Improved patient access and throughput may improve patient satisfaction with their surgical experience, which could lead to increased surgical referrals, both patient and PCP initiated. Satisfaction and positive learning experiences of surgical residents with this system of care may improve the likelihood of them joining such a practice, which will then foster the cultural evolution of comanagement. In addition, because of the increased scrutiny and potential financial ties (ie, pay for performance) to quality and safety issues, a comanagement model involving hospitalists is ideally poised to systematically account for these issues. Finally, because of nurse staffing shortages, care processes that promote workplace satisfaction and respect may promote nurse recruitment and retention, thus improving the competitive advantage even further.
CONCLUSION
Surgical comanagement has many distinct advantages for all parties involved, including the surgeon, hospitalist, house staff, nurses, case manager, patient and family, and the health care system overall. As hospitalists have been comanaging medical inpatients with primary care physicians for years, the concept of surgical comanagement is truly a natural evolution of the scope of hospitalist practice.
- “..To Act as a Unit”: The Story of the Cleveland Clinic.Cleveland, OH:Cleveland Clinic Press;1996:17. .
- Inpatient medicine and the evolution of the hospitalist.Clev Clin J Med.1998;68(11):192–200. , , .
- New requirements for resident duty hours.JAMA.2002;288(9):1112–1114. , , .
- Why perioperative medicine matters more than ever.Clev Clin J Med.2006:73( ); suppl 1 2006:S1. , .
- Perioperative Medicine. In: The core competencies in hospital hedicine: a framework for curriculum development.J Hosp Med (Online).2006;1(Suppl 1):30–1. , , , , .
- Opportunity missed: medical consultation, resource use, and quality of care of patients undergoing major surgery.Arch Intern Med.2007;167(21):2338–2344. , , , , , .
- Hip fractures in geriatric patients. Results of an interdisciplinary hospital care program.Clin Orthopaed Relat Res.1992;274:213–225. , , , .
- Outcomes for older patients with hip fractures: the impact of orthopedic and geriatric medicine cocare.J Orthopaed Trauma.2006;20(3):172–178; discussion 9–80. , , , , , .
- Reducing delirium after hip fracture: a randomized trial.J Am Geriatr Soc.2001;49(5):516–522. , , , .
- An internist joins the surgery service: does comanagement make a difference?J Gen Intern Med.1994;9(8):440–444. , , , , .
- Medical and surgical comanagement after elective hip and knee arthroplasty: a randomized, controlled trial.Ann Intern Med.2004;141(1):28–38. , , , et al.
- Effects of a hospitalist model on elderly patients with hip fracture.Arch Intern Med.2005;165(7):796–801. , , , et al.
- Value of Preoperative clinic visits in identifying issues with potential impact on operating room efficiency.Anesthesiology.2006;105(6):1254–1259; discussion 6A. , , , , , .
- Preoperative clinic visits reduce operating room cancellations and delays.Anesthesiology.2005;103(4):855–859. , , , , .
- Development and effectiveness of an anesthesia preoperative evaluation clinic in a teaching hospital.Anesthesiology.1996;85(1):196–206. .
- Postoperative pulmonary complications: experience with an outpatient pre‐operative assessment program.J Clin Outcomes Manage.2005;12(10):505–510. , , , et al.
- Principles of effective consultation: an update for the 21st‐century consultant.Arch Intern Med.2007;167(3):271–275. , , , .
With the rapid advance of medicine to its present‐day status in which it evokes the aid of all the natural sciences, an individual is no more able to undertake the more intricate problems alone, without the aid and cooperation of colleagues having special training in each of the various clinical and laboratory branches, than he would be today to make an automobile alone.1
It is ironic that our specialty of hospital‐based medicine grew out of the soil of managed care and a renewed emphasis on generalism.2 Historical precedence clearly confirms the virtue of specialization and multidisciplinary care. Taken in this context, hospitalists have been comanagers from the very start, working with primary care physicians. The unprecedented growth of hospitalists in the United States has been accelerated by forces that pulled generalists out of the hospital and off the hospital wardsnamely the expensive inefficiency of trying to be in 2 places at 1 time. Faced with an expanding scope of practice and increasing outpatient volumes coupled with declining reimbursements, primary care physicians (PCPs) recognized the need to share their patients with inpatient comanagers.
Today, the surgeon is faced with many of the same pressures experienced by PCPs. Surgical productivity, efficiency, and quality are highly valued, yet require the surgeon to be in 2 places at 1 time. In the past, many surgeons in teaching hospitals relied on surgical residents to manage uncomplicated presurgical and postsurgical care and collaborated with internists for more difficult problems. Now, surgical residents are limited by work‐hour restrictions imposed by the Accreditation Council for Graduate Medical Education,3 reducing their ability to respond to patients outside the operating room. Perhaps more importantly, surgical patients today continue to increase in age and complexity, with a projected 50% rise in surgery‐related costs and a 100% rise in surgical complications in the next 2 decades.4 An experienced comanager of surgical patients that does not rely on PCPs or the surgical education system makes great practical and economic sense, and is a natural evolution of the hospitalist concept and skill set. Hospital medicine core competencies highlight perioperative medicine as a body of knowledge and practice germane to hospitalists. In fact, it specifically states that hospitalists should strive to engage in efforts to improve the efficiency and quality of care through innovative models, which may include comanagement of surgical patients in the perioperative period.5
CONSULTATION VERSUS COMANAGEMENT
Historically, in academic settings surgeons and medical practitioners have collaborated via the framework of consultation. If a surgeon needed assistance with uncontrolled diabetes or blood pressure, he or she called the internist to make recommendations on appropriate treatment. If the internist was faced with a potential surgical issue, he or she consulted the surgeon for their evaluation and opinion. In today's chaotic hospital environment, this collaborative framework has obvious inefficiencies. By definition, the consultation involves a formal request, which demands seamless communication that often does not exist. Next, the consultant reviews the chart, evaluates the patient, reviews pertinent clinical data, and provides an assessment with recommendations for management and care. How and whether these recommendations are enacted may be explicitly defined by the requesting service, but often it is not, and a delay in execution of recommendations potentially ensues. An observational cohort study showed that patients receiving medical consultation were no more likely to have tight glycemic control, perioperative beta‐blockers administration, or venous thromboembolism (VTE) prophylaxis; however, patients receiving consultation had a longer length of stay and higher costs of care.6 Comanagement represents a patient care referral, not consultation. A comanager is requested at the outset, but subsequently plays a much more active role, which may involve daily or twice daily visits, writing progress notes and orders, assessing and managing acute issues, and facilitating discharge planning and care transitions. Despite the ability to facilitate care, the basis for comanagement should be the same as for specialty consultation.
In contrast to academic settings, comanagement by PCPs and medical subspecialists occurs routinely in community hospitals. This model works best for patients with few problems who are followed closely by a single comanager, typically the PCP. However, complex patients with multiple comorbidities may decompensate without an attentive and experienced PCP, or wind up with numerous subspecialists making recommendations and writing orders in a disorganized fashion. The extreme of this situation is an unsystematic and inefficient management by committee, where medical specialists pick and choose an area of comanagement, without clear boundaries between the various team members. This approach is fraught with pitfalls in communication and may lead to conflicting recommendations or false assumptions among team members, further increasing patient morbidity.
In both academic and community settings, comanagement by a hospitalist offers advantages of consistent availability and proactive perioperative expertise, both in diagnosing and treating relevant problems and in recognizing the need for subspecialty involvement, thus improving efficiency of care. Although some health care systems may consider automatic patient care referrals to hospitalists for all surgical patients, this approach should be discouraged unless the patient population demands specialty involvement. Best practice would identify comorbid surgical patients during the outpatient preoperative process and then hardwire the patient care referral to the hospitalist upon surgical admission.
COMANAGEMENT MAKES SENSE
The multidisciplinary nature of comanagement can streamline individual patient care from the moment the decision for surgery is made. Preoperative assessment and management by the hospitalist can uncover risks from known conditions requiring optimization; identify new, undiagnosed conditions affecting the perioperative period; and initiate prophylactic and therapeutic regimens that reduce the chances for postoperative complications. Specific examples may include beta‐blockers in higher risk patients, anticoagulation management, and VTE prophylaxis.
The comanaging hospitalist ensures that these strategies are implemented, tailors them to the individual patient, and diagnoses and treats complications promptly when they occur. In addition, hospitalist comanagers can be more involved to facilitate patient transitions to posthospital care venues; this might involve communication with patients, families, case managers, and PCPs, among others. Ultimately, the investment of the comanaging hospitalist in the surgical patient is much greater in both scope and time. This may be expected to improve patient care efficiency, reduce length of stay, and may decrease overall complications. In addition, this investment is often recognized by the other important members of the care team, including nursing, case management, and patients and families, thus improving both patient and nursing satisfaction ratings.
AVAILABLE DATA ON THE BENEFITS OF COMANAGEMENT
Early studies on comanagement focused on orthopedic surgery and geriatric collaboration. Zuckerman et al.7 studied the effects of an interdisciplinary team approach to the hip fracture patient, entitled the Geriatric Hip Fracture Program (GHFP), in the mid‐1980s. They compared 431 patients admitted under the care of the GHFP for surgical repair of hip fracture between 1985 and 1988 with 60 historical controls at the same institution prior to the inception of the program. GHFP patients were evaluated by an orthopedic surgeon and a consulting internist or geriatrician. In addition to therapy service evaluations, each patient was screened by an ophthalmologist for visual impairment, a psychiatrist for preexisting cognitive dysfunction and depression, a social worker, and a case manager. GHFP patients had fewer postoperative complications, fewer intensive care unit transfers for acute medical issues, better ambulatory status and distance ambulated at discharge, and nonsignificant trends toward decreased length of stay and increased likelihood of return to home. A more recent prospective observational study of patients with hip fracture in Australia8 compared a 4‐year period of geriatric comanagement of 447 patients with hip fracture with 3 years of historical control patients (n = 504) prior to the institution of the comanagement service. Postoperative medical complications, mortality, and 6‐month readmission rates were significantly lower in the geriatric comanagement cohort. No differences in median length of hospital stay or in discharge destination were noted. The proportion of patients receiving anti‐osteoporotic therapy (calcium, vitamin D, and bisphosphonates) increased from 12% to 93% after the institution of comanagement. Also, the proportion of patients prescribed pharmacologic VTE prophylaxis increased from 63% to 94%, and symptomatic VTE events (deep vein thrombosis or PE) decreased from 4.6% to 1.3% after implementation. In another geriatrician comanagement study, Marcantonio et al.9 performed a randomized trial in patients with hip fracture comparing geriatric comanagement with a structured treatment care protocol to usual care. Although length of stay was unchanged and costs of care were not reported, geriatric comanagement significantly reduced the number and severity of episodes of delirium.
Macpherson et al.10 studied the effect of internist comanagement of 165 cardiothoracic surgery patients in the Minneaoplis Veteran's Affairs Medical Center in 1990. They found that, compared with the prior year, the implementation of internist comanagement was associated with hospital stays of 6 days shorter length, lower use of resources such as lab and radiology, and a trend toward decreased mortality. Huddleston et al.11 conducted a randomized controlled trial of 526 patients undergoing elective total hip or knee arthroplasty, comparing a comanagement hospitalist‐orthopedic team with standard orthopedic surgery care and internal medicine consultation as needed. Despite comparison to the standard of tightly managed care protocols in elective hip and knee arthroplasty, patients comanaged by hospitalists were more likely to be discharged without postoperative complications, and were ready for discharge half a day sooner when adjusting for skilled facility bed availability. No difference in mortality rates or total cost of care was noted between the 2 models. However, nurses and surgeons both strongly preferred the comanagement model, with providers reporting that care was prompt and coordinated, and there was an enhanced ease of providing care. In a second study, the authors from the same institution12 studied 466 patients over 65 years of age admitted for surgical repair of hip fracture. Patients in the comanagement group went to surgery faster, were discharged sooner after surgery, and had an overall lower length of stay. No differences were noted in inpatient mortality, 30‐day readmission rates, or complication rates. Delirium was diagnosed more often in the comanagement group, but a diagnosis of delirium was associated with an earlier discharge after surgery. This may reflect greater attention to the presence of delirium, better documentation, and more prompt treatment.
Preoperative testing centers staffed by anesthesiologists have been shown to positively impact surgical care.1315 However, there has been little study to specifically evaluate the role of medical comanagement in the preoperative setting. Jaffer et al.16 demonstrated a reduction in postoperative pulmonary complications in a mixed surgical population by utilizing a structured preoperative assessment and management program of hospitalists.
COMANAGEMENT SATISFACTION
Surgical comanagement has been reported to improve surgeon and nurse satisfaction ratings.11 Salerno et al.,17 in their study of consultation preferences of surgeons, internists and family physicians, confirmed that surgeons, especially orthopedic surgeons, favor the comanagement model more than the traditional consultation model. This is not surprising as surgeons in the comanagement model may be expected to spend more time in the operating room as opposed to the hospital floors, thus improving patient access to timely surgery and reducing cancellations and delays. Ultimately, the comanagement model may result in a competitive advantage over traditional care. Improved patient access and throughput may improve patient satisfaction with their surgical experience, which could lead to increased surgical referrals, both patient and PCP initiated. Satisfaction and positive learning experiences of surgical residents with this system of care may improve the likelihood of them joining such a practice, which will then foster the cultural evolution of comanagement. In addition, because of the increased scrutiny and potential financial ties (ie, pay for performance) to quality and safety issues, a comanagement model involving hospitalists is ideally poised to systematically account for these issues. Finally, because of nurse staffing shortages, care processes that promote workplace satisfaction and respect may promote nurse recruitment and retention, thus improving the competitive advantage even further.
CONCLUSION
Surgical comanagement has many distinct advantages for all parties involved, including the surgeon, hospitalist, house staff, nurses, case manager, patient and family, and the health care system overall. As hospitalists have been comanaging medical inpatients with primary care physicians for years, the concept of surgical comanagement is truly a natural evolution of the scope of hospitalist practice.
With the rapid advance of medicine to its present‐day status in which it evokes the aid of all the natural sciences, an individual is no more able to undertake the more intricate problems alone, without the aid and cooperation of colleagues having special training in each of the various clinical and laboratory branches, than he would be today to make an automobile alone.1
It is ironic that our specialty of hospital‐based medicine grew out of the soil of managed care and a renewed emphasis on generalism.2 Historical precedence clearly confirms the virtue of specialization and multidisciplinary care. Taken in this context, hospitalists have been comanagers from the very start, working with primary care physicians. The unprecedented growth of hospitalists in the United States has been accelerated by forces that pulled generalists out of the hospital and off the hospital wardsnamely the expensive inefficiency of trying to be in 2 places at 1 time. Faced with an expanding scope of practice and increasing outpatient volumes coupled with declining reimbursements, primary care physicians (PCPs) recognized the need to share their patients with inpatient comanagers.
Today, the surgeon is faced with many of the same pressures experienced by PCPs. Surgical productivity, efficiency, and quality are highly valued, yet require the surgeon to be in 2 places at 1 time. In the past, many surgeons in teaching hospitals relied on surgical residents to manage uncomplicated presurgical and postsurgical care and collaborated with internists for more difficult problems. Now, surgical residents are limited by work‐hour restrictions imposed by the Accreditation Council for Graduate Medical Education,3 reducing their ability to respond to patients outside the operating room. Perhaps more importantly, surgical patients today continue to increase in age and complexity, with a projected 50% rise in surgery‐related costs and a 100% rise in surgical complications in the next 2 decades.4 An experienced comanager of surgical patients that does not rely on PCPs or the surgical education system makes great practical and economic sense, and is a natural evolution of the hospitalist concept and skill set. Hospital medicine core competencies highlight perioperative medicine as a body of knowledge and practice germane to hospitalists. In fact, it specifically states that hospitalists should strive to engage in efforts to improve the efficiency and quality of care through innovative models, which may include comanagement of surgical patients in the perioperative period.5
CONSULTATION VERSUS COMANAGEMENT
Historically, in academic settings surgeons and medical practitioners have collaborated via the framework of consultation. If a surgeon needed assistance with uncontrolled diabetes or blood pressure, he or she called the internist to make recommendations on appropriate treatment. If the internist was faced with a potential surgical issue, he or she consulted the surgeon for their evaluation and opinion. In today's chaotic hospital environment, this collaborative framework has obvious inefficiencies. By definition, the consultation involves a formal request, which demands seamless communication that often does not exist. Next, the consultant reviews the chart, evaluates the patient, reviews pertinent clinical data, and provides an assessment with recommendations for management and care. How and whether these recommendations are enacted may be explicitly defined by the requesting service, but often it is not, and a delay in execution of recommendations potentially ensues. An observational cohort study showed that patients receiving medical consultation were no more likely to have tight glycemic control, perioperative beta‐blockers administration, or venous thromboembolism (VTE) prophylaxis; however, patients receiving consultation had a longer length of stay and higher costs of care.6 Comanagement represents a patient care referral, not consultation. A comanager is requested at the outset, but subsequently plays a much more active role, which may involve daily or twice daily visits, writing progress notes and orders, assessing and managing acute issues, and facilitating discharge planning and care transitions. Despite the ability to facilitate care, the basis for comanagement should be the same as for specialty consultation.
In contrast to academic settings, comanagement by PCPs and medical subspecialists occurs routinely in community hospitals. This model works best for patients with few problems who are followed closely by a single comanager, typically the PCP. However, complex patients with multiple comorbidities may decompensate without an attentive and experienced PCP, or wind up with numerous subspecialists making recommendations and writing orders in a disorganized fashion. The extreme of this situation is an unsystematic and inefficient management by committee, where medical specialists pick and choose an area of comanagement, without clear boundaries between the various team members. This approach is fraught with pitfalls in communication and may lead to conflicting recommendations or false assumptions among team members, further increasing patient morbidity.
In both academic and community settings, comanagement by a hospitalist offers advantages of consistent availability and proactive perioperative expertise, both in diagnosing and treating relevant problems and in recognizing the need for subspecialty involvement, thus improving efficiency of care. Although some health care systems may consider automatic patient care referrals to hospitalists for all surgical patients, this approach should be discouraged unless the patient population demands specialty involvement. Best practice would identify comorbid surgical patients during the outpatient preoperative process and then hardwire the patient care referral to the hospitalist upon surgical admission.
COMANAGEMENT MAKES SENSE
The multidisciplinary nature of comanagement can streamline individual patient care from the moment the decision for surgery is made. Preoperative assessment and management by the hospitalist can uncover risks from known conditions requiring optimization; identify new, undiagnosed conditions affecting the perioperative period; and initiate prophylactic and therapeutic regimens that reduce the chances for postoperative complications. Specific examples may include beta‐blockers in higher risk patients, anticoagulation management, and VTE prophylaxis.
The comanaging hospitalist ensures that these strategies are implemented, tailors them to the individual patient, and diagnoses and treats complications promptly when they occur. In addition, hospitalist comanagers can be more involved to facilitate patient transitions to posthospital care venues; this might involve communication with patients, families, case managers, and PCPs, among others. Ultimately, the investment of the comanaging hospitalist in the surgical patient is much greater in both scope and time. This may be expected to improve patient care efficiency, reduce length of stay, and may decrease overall complications. In addition, this investment is often recognized by the other important members of the care team, including nursing, case management, and patients and families, thus improving both patient and nursing satisfaction ratings.
AVAILABLE DATA ON THE BENEFITS OF COMANAGEMENT
Early studies on comanagement focused on orthopedic surgery and geriatric collaboration. Zuckerman et al.7 studied the effects of an interdisciplinary team approach to the hip fracture patient, entitled the Geriatric Hip Fracture Program (GHFP), in the mid‐1980s. They compared 431 patients admitted under the care of the GHFP for surgical repair of hip fracture between 1985 and 1988 with 60 historical controls at the same institution prior to the inception of the program. GHFP patients were evaluated by an orthopedic surgeon and a consulting internist or geriatrician. In addition to therapy service evaluations, each patient was screened by an ophthalmologist for visual impairment, a psychiatrist for preexisting cognitive dysfunction and depression, a social worker, and a case manager. GHFP patients had fewer postoperative complications, fewer intensive care unit transfers for acute medical issues, better ambulatory status and distance ambulated at discharge, and nonsignificant trends toward decreased length of stay and increased likelihood of return to home. A more recent prospective observational study of patients with hip fracture in Australia8 compared a 4‐year period of geriatric comanagement of 447 patients with hip fracture with 3 years of historical control patients (n = 504) prior to the institution of the comanagement service. Postoperative medical complications, mortality, and 6‐month readmission rates were significantly lower in the geriatric comanagement cohort. No differences in median length of hospital stay or in discharge destination were noted. The proportion of patients receiving anti‐osteoporotic therapy (calcium, vitamin D, and bisphosphonates) increased from 12% to 93% after the institution of comanagement. Also, the proportion of patients prescribed pharmacologic VTE prophylaxis increased from 63% to 94%, and symptomatic VTE events (deep vein thrombosis or PE) decreased from 4.6% to 1.3% after implementation. In another geriatrician comanagement study, Marcantonio et al.9 performed a randomized trial in patients with hip fracture comparing geriatric comanagement with a structured treatment care protocol to usual care. Although length of stay was unchanged and costs of care were not reported, geriatric comanagement significantly reduced the number and severity of episodes of delirium.
Macpherson et al.10 studied the effect of internist comanagement of 165 cardiothoracic surgery patients in the Minneaoplis Veteran's Affairs Medical Center in 1990. They found that, compared with the prior year, the implementation of internist comanagement was associated with hospital stays of 6 days shorter length, lower use of resources such as lab and radiology, and a trend toward decreased mortality. Huddleston et al.11 conducted a randomized controlled trial of 526 patients undergoing elective total hip or knee arthroplasty, comparing a comanagement hospitalist‐orthopedic team with standard orthopedic surgery care and internal medicine consultation as needed. Despite comparison to the standard of tightly managed care protocols in elective hip and knee arthroplasty, patients comanaged by hospitalists were more likely to be discharged without postoperative complications, and were ready for discharge half a day sooner when adjusting for skilled facility bed availability. No difference in mortality rates or total cost of care was noted between the 2 models. However, nurses and surgeons both strongly preferred the comanagement model, with providers reporting that care was prompt and coordinated, and there was an enhanced ease of providing care. In a second study, the authors from the same institution12 studied 466 patients over 65 years of age admitted for surgical repair of hip fracture. Patients in the comanagement group went to surgery faster, were discharged sooner after surgery, and had an overall lower length of stay. No differences were noted in inpatient mortality, 30‐day readmission rates, or complication rates. Delirium was diagnosed more often in the comanagement group, but a diagnosis of delirium was associated with an earlier discharge after surgery. This may reflect greater attention to the presence of delirium, better documentation, and more prompt treatment.
Preoperative testing centers staffed by anesthesiologists have been shown to positively impact surgical care.1315 However, there has been little study to specifically evaluate the role of medical comanagement in the preoperative setting. Jaffer et al.16 demonstrated a reduction in postoperative pulmonary complications in a mixed surgical population by utilizing a structured preoperative assessment and management program of hospitalists.
COMANAGEMENT SATISFACTION
Surgical comanagement has been reported to improve surgeon and nurse satisfaction ratings.11 Salerno et al.,17 in their study of consultation preferences of surgeons, internists and family physicians, confirmed that surgeons, especially orthopedic surgeons, favor the comanagement model more than the traditional consultation model. This is not surprising as surgeons in the comanagement model may be expected to spend more time in the operating room as opposed to the hospital floors, thus improving patient access to timely surgery and reducing cancellations and delays. Ultimately, the comanagement model may result in a competitive advantage over traditional care. Improved patient access and throughput may improve patient satisfaction with their surgical experience, which could lead to increased surgical referrals, both patient and PCP initiated. Satisfaction and positive learning experiences of surgical residents with this system of care may improve the likelihood of them joining such a practice, which will then foster the cultural evolution of comanagement. In addition, because of the increased scrutiny and potential financial ties (ie, pay for performance) to quality and safety issues, a comanagement model involving hospitalists is ideally poised to systematically account for these issues. Finally, because of nurse staffing shortages, care processes that promote workplace satisfaction and respect may promote nurse recruitment and retention, thus improving the competitive advantage even further.
CONCLUSION
Surgical comanagement has many distinct advantages for all parties involved, including the surgeon, hospitalist, house staff, nurses, case manager, patient and family, and the health care system overall. As hospitalists have been comanaging medical inpatients with primary care physicians for years, the concept of surgical comanagement is truly a natural evolution of the scope of hospitalist practice.
- “..To Act as a Unit”: The Story of the Cleveland Clinic.Cleveland, OH:Cleveland Clinic Press;1996:17. .
- Inpatient medicine and the evolution of the hospitalist.Clev Clin J Med.1998;68(11):192–200. , , .
- New requirements for resident duty hours.JAMA.2002;288(9):1112–1114. , , .
- Why perioperative medicine matters more than ever.Clev Clin J Med.2006:73( ); suppl 1 2006:S1. , .
- Perioperative Medicine. In: The core competencies in hospital hedicine: a framework for curriculum development.J Hosp Med (Online).2006;1(Suppl 1):30–1. , , , , .
- Opportunity missed: medical consultation, resource use, and quality of care of patients undergoing major surgery.Arch Intern Med.2007;167(21):2338–2344. , , , , , .
- Hip fractures in geriatric patients. Results of an interdisciplinary hospital care program.Clin Orthopaed Relat Res.1992;274:213–225. , , , .
- Outcomes for older patients with hip fractures: the impact of orthopedic and geriatric medicine cocare.J Orthopaed Trauma.2006;20(3):172–178; discussion 9–80. , , , , , .
- Reducing delirium after hip fracture: a randomized trial.J Am Geriatr Soc.2001;49(5):516–522. , , , .
- An internist joins the surgery service: does comanagement make a difference?J Gen Intern Med.1994;9(8):440–444. , , , , .
- Medical and surgical comanagement after elective hip and knee arthroplasty: a randomized, controlled trial.Ann Intern Med.2004;141(1):28–38. , , , et al.
- Effects of a hospitalist model on elderly patients with hip fracture.Arch Intern Med.2005;165(7):796–801. , , , et al.
- Value of Preoperative clinic visits in identifying issues with potential impact on operating room efficiency.Anesthesiology.2006;105(6):1254–1259; discussion 6A. , , , , , .
- Preoperative clinic visits reduce operating room cancellations and delays.Anesthesiology.2005;103(4):855–859. , , , , .
- Development and effectiveness of an anesthesia preoperative evaluation clinic in a teaching hospital.Anesthesiology.1996;85(1):196–206. .
- Postoperative pulmonary complications: experience with an outpatient pre‐operative assessment program.J Clin Outcomes Manage.2005;12(10):505–510. , , , et al.
- Principles of effective consultation: an update for the 21st‐century consultant.Arch Intern Med.2007;167(3):271–275. , , , .
- “..To Act as a Unit”: The Story of the Cleveland Clinic.Cleveland, OH:Cleveland Clinic Press;1996:17. .
- Inpatient medicine and the evolution of the hospitalist.Clev Clin J Med.1998;68(11):192–200. , , .
- New requirements for resident duty hours.JAMA.2002;288(9):1112–1114. , , .
- Why perioperative medicine matters more than ever.Clev Clin J Med.2006:73( ); suppl 1 2006:S1. , .
- Perioperative Medicine. In: The core competencies in hospital hedicine: a framework for curriculum development.J Hosp Med (Online).2006;1(Suppl 1):30–1. , , , , .
- Opportunity missed: medical consultation, resource use, and quality of care of patients undergoing major surgery.Arch Intern Med.2007;167(21):2338–2344. , , , , , .
- Hip fractures in geriatric patients. Results of an interdisciplinary hospital care program.Clin Orthopaed Relat Res.1992;274:213–225. , , , .
- Outcomes for older patients with hip fractures: the impact of orthopedic and geriatric medicine cocare.J Orthopaed Trauma.2006;20(3):172–178; discussion 9–80. , , , , , .
- Reducing delirium after hip fracture: a randomized trial.J Am Geriatr Soc.2001;49(5):516–522. , , , .
- An internist joins the surgery service: does comanagement make a difference?J Gen Intern Med.1994;9(8):440–444. , , , , .
- Medical and surgical comanagement after elective hip and knee arthroplasty: a randomized, controlled trial.Ann Intern Med.2004;141(1):28–38. , , , et al.
- Effects of a hospitalist model on elderly patients with hip fracture.Arch Intern Med.2005;165(7):796–801. , , , et al.
- Value of Preoperative clinic visits in identifying issues with potential impact on operating room efficiency.Anesthesiology.2006;105(6):1254–1259; discussion 6A. , , , , , .
- Preoperative clinic visits reduce operating room cancellations and delays.Anesthesiology.2005;103(4):855–859. , , , , .
- Development and effectiveness of an anesthesia preoperative evaluation clinic in a teaching hospital.Anesthesiology.1996;85(1):196–206. .
- Postoperative pulmonary complications: experience with an outpatient pre‐operative assessment program.J Clin Outcomes Manage.2005;12(10):505–510. , , , et al.
- Principles of effective consultation: an update for the 21st‐century consultant.Arch Intern Med.2007;167(3):271–275. , , , .
Algorithms for Diagnosing and Treating VAP
Ventilator‐associated pneumonia (VAP) is a serious and common complication for patients in the intensive care unit (ICU).1 VAP is defined as a pulmonary infection occurring after hospital admission in a mechanically‐ventilated patient with a tracheostomy or endotracheal tube.2, 3 With an attributable mortality that may exceed 20% and an estimated cost of $5000‐$20,000 per episode,49 the management of VAP is an important issue for both patient safety and cost of care.
The diagnosis of VAP is a controversial topic in critical care, primarily because of the difficulty distinguishing between airway colonization, upper respiratory tract infection (eg, tracheobronchitis), and early‐onset pneumonia. Some clinicians insist that an invasive sampling technique (eg, bronchoalveolar lavage) with quantitative cultures is essential for determining the presence of VAP.10 However, other clinicians suggest that a noninvasive approach using qualitative cultures (eg, tracheal suctioning) is an acceptable alternative.11 Regardless, nearly all experts agree that a specimen for microbiologic culture should be obtained prior to initiating antibiotics. Subsequent therapy should then be adjusted according to culture results.
Studies from both Europe and North America have demonstrated considerable variation in the diagnostic approaches used for patients with suspected VAP.12, 13 This variation is likely a result of several factors including controversy about the best diagnostic approach, variation in clinician knowledge and experience, and variation in ICU management protocols. Such practice variability is common for many ICU behaviors.1416 Quality‐of‐care proponents view this variation as an important opportunity for improvement.17
During a recent national collaborative aimed at reducing health careassociated infections in the ICU, we discovered many participants were uncertain about how to diagnose and manage VAP, and considerable practice variability existed among participating hospitals. This uncertainty provided an important opportunity for developing consensus on VAP management. On the basis of diagnostic criteria outlined by the Centers for Disease Control and Prevention (CDC), we developed algorithms as tools for diagnosing VAP in 4 ICU populations: infant, pediatric, immunocompromised, and adult ICU patients. We also developed an algorithm for initial VAP treatment. An interdisciplinary team of experts reviewed the current literature and developed these evidence‐based consensus guidelines. Our intent is that the algorithms provide guidance to clinicians looking for a standardized approach to the diagnosis and management of this complicated clinical situation.
METHODS
Our primary goal was to develop practical algorithms that assist ICU clinicians in the diagnosis and management of VAP during daily practice. To improve the quality and credibility of these algorithms, the development process used a stepwise approach that included assembling an interdisciplinary team of experts, appraising the published evidence, and formulating the algorithms through a consensus process.18
AHRQ National Collaborative
We developed these diagnostic algorithms as part of a national collaborative effort aimed at reducing VAP and central venous catheterrelated bloodstream infections in the ICU. This effort was possible through a 2‐year Partnerships in Implementing Patient Safety grant funded by the Agency for Healthcare Research and Quality (AHRQ).19 The voluntary collaborative was conducted in 61 medical/surgical and children's hospitals across the Hospital Corporation of America (HCA), a company that owns and/or operates 173 hospitals and 107 freestanding surgery centers in 20 states, England, and Switzerland. HCA is one of the largest providers of health care in the United States. All participating hospitals had at least 1 ICU, and a total of 110 ICUs were included in the project. Most hospitals were in the southern or southeastern regions of the United States.
Interdisciplinary Team
We assembled an interdisciplinary team to develop the diagnostic algorithms. Individuals on the team represented the specialties of infectious diseases, infection control, anesthesia, critical care medicine, hospital medicine, critical care nursing, pharmacy, and biostatistics. The development phase occurred over 34 months and used an iterative process that consisted of both group conference calls and in‐person meetings.
Our goal was not to conduct a systematic review but rather to develop practical algorithms for collaborative participants in a timely manner. Our literature search strategy included MEDLINE and the Cochrane Library. We focused on articles that addressed key diagnostic issues, proposed an algorithm, or summarized a topic relevant to practicing clinicians. Extra attention was given to articles that were randomized trials, meta‐analyses, or systematic reviews. No explicit grading of articles was performed. We examined studies with outcomes of interest to clinicians, including mortality, number of ventilator days, length of stay, antibiotic utilization, and antibiotic resistance.
We screened potentially relevant articles and the references of these articles. The search results were reviewed by all members of the team, and an iterative consensus process was used to derive the current algorithms. Preliminary versions of the algorithms were shown to other AHRQ investigators and outside experts in the field, and additional modifications were made based on their feedback. The final algorithms were approved by all study investigators.
RESULTS
Literature Overview
Overall, there is an enormous body of published literature on diagnosing and managing VAP. The Medline database has listed more than 500 articles on VAP diagnosis in the past decade. Nonetheless, the best diagnostic approach remains unclear. The gold standard for diagnosing VAP is lung biopsy with histopathologic examination and tissue culture. However, this procedure is fraught with potential dangers and impractical for most critically ill patients.20 Therefore, practitioners traditionally combine their clinical suspicion (based on fever, leukocytosis, character of sputum, and radiographic changes), epidemiologic data (eg, patient demographics, medical history, and ICU infection surveillance data), and microbiologic data.
Several issues relevant to practicing clinicians deserve further mention.
Definition of VAP
Although early articles used variable criteria for diagnosing VAP, recent studies have traditionally defined VAP as an infection occurring more than 48 hours after hospital admission in a mechanically ventilated patient with a tracheostomy or endotracheal tube.2 In early 2007, the CDC revised their definition for diagnosing VAP.3 These latest criteria state there is no minimum period that the ventilator must be in place in order to diagnose VAP. This important change must be kept in mind when examining future studies.
The term VAP is more specific than the term health careassociated pneumonia. The latter encompasses patients residing in a nursing home or long‐term care facility; hospitalized in an acute care hospital for more than 48 hours in the past 90 days; receiving antibiotics, chemotherapy, or wound care within the past 30 days; or attending a hospital or hemodialysis clinic.
The CDC published detailed criteria for diagnosing VAP in its member hospitals (Tables 1 and 2).3 Because diagnosing VAP in infants, children, elderly, and immunocompromised patients is often confusing because of other conditions with similar signs and symptoms, the CDC published alternate criteria for these populations. A key objective during development of our algorithms was to consolidate and simplify these diagnostic criteria for ICU clinicians.
Radiology | Signs/symptoms/laboratory |
---|---|
| |
Two or more serial chest radiographs with at least 1 of the following*: | CRITERIA FOR ANY PATIENT |
New or progressive and persistent infiltrate | At least 1 of the following: |
Consolidation | Fever (>38C or >100.4F) with no other recognized cause |
Cavitation | Leukopenia (<4000 WBC/mm3) or leukocytosis (12,000 WBC/mm3) |
Pneumatoceles, in infants 1 year old | For adults 70 years old, altered mental status with no other recognized causeand |
Note: In patients without underlying pulmonary or cardiac disease (eg, respiratory distress syndrome, bronchopulmonary dysplasia, pulmonary edema, or chronic obstructive pulmonary disease), 1 definitive chest radiograph is acceptable.* | |
At least 2 of the following: | |
New onset of purulent sputum, or change in character of sputum, or increased respiratory secretions, or increased suctioning requirements | |
New‐onset or worsening cough or dyspnea or tachypnea‖ | |
Rales or bronchial breath sounds | |
Worsening gas exchange (eg, O2 desaturation [eg, PaO2/FiO2 240],** increased oxygen requirement, or increased ventilation demand) | |
Any laboratory criterion from Table 2 |
|
ALTERNATE CRITERIA FOR INFANTS 1 YEAR OLD | |
Worsening gas exchange (eg, O2 desaturation, increased ventilation demand or O2 requirement) | |
and | |
At least 3 of the following: | |
Temperature instability with no other recognized cause | |
Leukopenia (<4000 WBC/mm3) or leukocytosis (15,000 WBC/mm3) and left shift (10% bands) | |
New‐onset purulent sputum, change in character of sputum, increased respiratory secretions, or increased suctioning requirements | |
Apnea, tachypnea,‖ nasal flaring with retraction of chest wall, or grunting | |
Wheezing, rales, or rhonchi | |
Cough | |
Bradycadia (<100 beats/min) or tachycardia (>170 beats/min) | |
ALTERNATE CRITERIA FOR CHILD >1 OR 12 YEARS OLD | |
At least 3 of the following: | |
Fever (>38.4C or >101.1F) or hypothermia (<36.5C or <97.7F) with no other recognized cause | |
Leukopenia (<4000 WBC/mm3) or leukocytosis (15,000 WBC/mm3) | |
New‐onset purulent sputum, change in character of sputum, increased respiratory secretions, or increased suctioning requirements | |
New‐onset or worsening cough or dyspnea, apnea, or tachypnea‖ | |
Rales or bronchial breath sounds | |
Worsening gas exchange (eg, O2 desaturation <94%, increased ventilation demand or O2 requirement) | |
Any laboratory criterion from Table 2 |
|
ALTERNATE CRITERIA FOR IMMUNOCOMPROMISED PATIENTS*** | |
At least 1 of the following: | |
Fever (>38.4C or >101.1F) with no other recognized cause | |
For adults > 70 years old, altered mental status with no other recognized cause | |
New‐onset purulent sputum, change in character of sputum, increased respiratory secretions, or increased suctioning requirements | |
New‐onset or worsening cough, dyspnea, or tachypnea‖ | |
Rales or bronchial breath sounds | |
Worsening gas exchange (eg, O2 desaturation [eg, PaO2/FiO2 240],** increased oxygen requirement, or increased ventilation demand) | |
Hemoptysis | |
Pleuritic chest pain | |
Matching positive blood and sputum cultures with Candida spp. | |
Evidence of fungi or Pneumocytis from minimally contaminated LRT specimen (eg, BAL or protected specimen brushing) from 1 of the following: | |
Direct microscopic exam | |
Positive culture of fungi | |
Any laboratory criterion from Table 2 |
|
Positive growth in blood culture* not related to another source of infection |
Positive growth in culture of pleural fluid |
Positive quantitative culture from minimally contaminated LRT specimen (eg, BAL) |
5% BAL‐obtained cells contain intracellular bacteria on direct microscopic exam (eg, gram stain) |
Histopathologic exam shows at least 1 of the following: |
Abscess formation or foci of consolidation with intense PMN accumulation in bronchioles and alveoli |
Positive quantitative culture of lung parenchyma |
Evidence of lung parenchyma invasion by fungal hyphae or pseudohyphae |
Positive culture of virus or Chlamydia from respiratory secretions |
Positive detection of viral antigen or antibody from respiratory secretions (eg, EIA, FAMA, shell vial assay, PCR) |
Fourfold rise in paired sera (IgG) for pathogen (eg, influenza viruses, Chlamydia) |
Positive PCR for Chlamydia or Mycoplasma |
Positive micro‐IF test for Chlamydia |
Positive culture or visualization by micro‐IF of Legionella spp. from respiratory secretions or tissue |
Detection of Legionella pneumophila serogroup 1 antigens in urine by RIA or EIA |
Fourfold rise in L. pneumophila serogroup 1 antibody titer to 1:128 in paired acute and convalescent sera by indirect IFA |
Etiology
The most commonly isolated VAP pathogens in all patients are bacteria.21 Most of these organisms normally colonize the respiratory and gastrointestinal tracts, but some are unique to health care settings. Tracheal intubation disrupts the body's natural anatomic and physiologic defenses and facilitates easier entry of these pathogens. Typical organisms include Staphylococcus aureus, Pseudomonas aeruginosa, Enterobacter species, Klebsiella pneumoniae, Acinetobacter species, Escherichia coli, and Haemophilus influenzae.22, 23 Unfortunately, the prevalence of antimicrobial resistance among VAP pathogens is increasing.24 Risk factors for antibiotic resistance are common to ICU patients and include recent antibiotics, hemodialysis, nursing home residence, immunosuppression, and chronic wound care.5 Polymicrobial infections are frequently seen in VAP, with up to 50% of all VAP episodes caused by more than 1 organism.25
Viral VAP is rare in immunocompetent hosts, and seasonal outbreaks of influenza and other similar viruses are usually limited to nonventilated patients.26 However, influenza is underrecognized as a potential nosocomial pathogen, and numerous nosocomial outbreaks because of influenza have been reported.2731 Although herpes simplex virus is often detected in the respiratory tract of critically ill patients, its clinical importance remains unclear.32
Fungal VAP is also rare in immunocompetent hosts. On the other hand, pulmonary fungal infections are common in immunocompromised patients, especially following chemotherapy and transplantation. Candida species are often isolated from the airways of normal hosts, but most cases traditionally have been considered clinically unimportant because these organisms are normal oropharyngeal flora and rarely invade lung tissue.33, 34 It is unclear whether recent studies suggesting Candida colonization is associated with a higher risk for Pseudomonas VAP will change this conventional wisdom.3537
Immunocompromised patients with suspected VAP are unique because they are at risk not only for typical bacteria (which are the most common causes of VAP) but also for rarer opportunistic infections and noninfectious processes that mimic pneumonia.3840 While assessing these patients, clinicians must consider the status of the underlying disease, duration and type of immunosuppression, prophylactic regimens, and risk factors for noninfectious causes of pulmonary infiltrates.41 Common opportunistic infections include viruses, mycobacteria, fungi, and Pneumocystis. Noninfectious processes include pulmonary edema, drug toxicity, radiation pneumonitis, engraftment syndrome, bronchiolitis obliterans organizing pneumonia, alveolar proteinosis, transfusion‐related lung injury, alveolar hemorrhage, and progression of underlying disease. In general, diagnosing VAP in the immunocompromised patient requires a prompt, comprehensive, and multidisciplinary approach.38
In preterm and term infants, the most common VAP pathogens are gram‐negative organisms such as E. coli and P. aeruginosa. Other less common pathogens are Enterobacter, Klebsiella, Acinetobacter, Proteus, Citrobacter, and Stenotrophomonas maltophilia.42, 43 Infants with a preceding bloodstream infection or prolonged intubation are more likely to develop VAP.43, 44 Unfortunately, gram‐negative bacteria often colonize the airways of mechanically ventilated infants, and tracheal aspirate culture data are difficult to interpret in this population.42
Children are more likely to develop VAP if they are intubated for more than 48 hours. The most common pathogens isolated from tracheal aspirates in mechanically ventilated children are enteric gram‐negative bacteria, P. aeruginosa, and S. aureus.45, 46 Few studies have precisely delineated the pathogenesis of VAP in the pediatric ICU population.
Overall, the causes of VAP vary by hospital, patient population, and ICU type. Therefore, it is essential that ICU clinicians remain knowledgeable about their local surveillance data.21 Awareness of VAP microbiology is essential for optimizing initial antibiotic therapy and improving outcomes.
Early Versus Late VAP
Distinguishing between early and late VAP is important for initial antibiotic selection because the etiologic pathogens vary between these 2 periods.4749 Early VAP (days 14 of hospitalization) usually involves antibiotic‐sensitive community‐acquired bacteria and carries a better prognosis. In contrast, late VAP (5 days after hospital admission) is more likely to be caused by antibiotic‐resistant nosocomial bacteria that lead to increased morbidity and mortality. All patients who have been hospitalized or have received antibiotics during the prior 90 days should be treated as having late VAP because they are at much higher risk for colonization and infection with antibiotic‐resistant bacteria.47 Of note, 2 recent studies suggest that pathogens in the early and late periods are becoming similar at some institutions.50, 51 Overall, the distinction between early and late VAP is important because it affects the likelihood that a patient has antibiotic‐resistant bacteria. If antibiotic‐resistant pathogens are suspected, initial therapy should include empiric triple antibiotics until culture data are available.
Culturing Approaches
Because clinical criteria alone are rarely able to accurately diagnose VAP,52, 53 clinicians should also obtain a respiratory specimen for microbiologic culture. Despite the convenience of blood cultures, their sensitivity for diagnosing VAP is poor, and they rarely make the diagnosis alone.54 Two methods are available for culturing the lungsan invasive approach (eg, bronchoscopy with bronchoalveolar lavage) and a noninvasive approach (eg, tracheal aspirate).
Some investigators believe that adult patients with suspected VAP should always undergo an invasive sampling of lower‐respiratory‐tract secretions.55 Proponents of the invasive approach cite the frequency with which potential pathogens colonize the trachea of ICU patients and create spurious results on tracheal aspirates.22 In addition, several studies have shown that clinicians are more likely to narrow the spectrum of antibiotics after obtaining an invasive diagnostic sample.56 In other words, the invasive approach has been associated with better antimicrobial stewardship.
Other investigators believe that a noninvasive approach is equally safe and effective for diagnosing VAP.57 This clinical approach involves culturing a tracheal aspirate and using a pneumonia prediction score such as the clinical pulmonary infection score (CPIS; Table 3). The CPIS assigns 012 points based on 6 clinical criteria: fever, leukocyte count, oxygenation, quantity and purulence of secretions, type of radiographic abnormality, and results of sputum gram stain and culture.58 As developed, a CPIS > 6 has a sensitivity of 93% and a specificity of 100% for diagnosing VAP.58 However, the CPIS requires that nurses record sputum volume and that the laboratory stains the specimen. When the CPIS has been modified based on the unavailability of such resources, the results have been less impressive.5961 Despite studies showing that a noninvasive clinical approach can achieve adequate initial antibiotic coverage and reduce overuse of broad‐spectrum agents,62, 63 clinicians who use the CPIS must understand its inherent limitations.
Criterion | Range | Score |
---|---|---|
| ||
Temperature (C) | 36.138.4 | 0 |
38.538.9 | 1 | |
39 or 36 | 2 | |
Blood leukocytes (/mm3) | 4000 and 11,000 | 0 |
<4000 or >11,000 | 1 | |
+ band forms 500 | 2 | |
Oxygenation: PaO2/FiO2 (mmHg) | >240 or ARDS | 0 |
240 and no evidence of ARDS | 2 | |
Chest radiograph | No infiltrate | 0 |
Diffuse (or patchy) infiltrate | 1 | |
Localized infiltrate | 2 | |
Tracheal secretions | Absence of tracheal secretions | 0 |
Nonpurulent tracheal secretions | 1 | |
Purulent tracheal secretions | 2 | |
Culture of tracheal aspirate | Pathogenic bacteria culture: no growth or light growth | 0 |
Pathogenic bacteria culture: moderate/heavy growth | 1 | |
Same pathogenic bacteria seen on gram stain (add 1 point) | 2 |
A meta‐analysis56 comparing the utility of an invasive versus a noninvasive culturing approach identified 4 randomized trials examining this issue.6669 Overall, an invasive approach did not alter mortality, but patients undergoing bronchoscopy were much more likely to have their antibiotic regimens modified by clinicians. This suggests that the invasive approach may allow more directed use of antibiotics. Recently, the Canadian Critical Care Trials Group conducted a multicenter randomized trial looking at this issue.11 There was no difference between the 2 approaches in mortality, number of ventilator days, and antibiotic usage. However, all patients in this study were immediately treated with empiric broad‐spectrum antibiotics until culture results were available, and the investigators did not have a protocol for stopping antibiotics after culture data were available.
In summary, both invasive and noninvasive culturing approaches are considered acceptable options for diagnosing VAP. Readers interested in learning more about this topic should read the worthwhile Expert Discussion70 by Chastre and colleagues55 at the end of this article. In general, we recommend that ICU clinicians use a combination of clinical suspicion (based on the CPIS or other objective data) and cultures ideally obtained prior to antibiotics. Regardless of the chosen culturing approach, clinicians must recognize that 1 of the most important determinants of patient outcome is prompt administration of adequate initial antibiotics.7175
Initial Antibiotic Administration
Delaying initial antibiotics in VAP increases the risk of death.7175 If a patient receives ineffective initial therapy, a later switch to appropriate therapy does not eliminate the increased mortality risk. Therefore, a comprehensive approach to VAP diagnosis requires consideration of initial empiric antibiotic administration.
Whenever possible, clinicians should obtain a lower respiratory tract sample for microscopy and culture before administering antibiotics because performing cultures after antibiotics have been recently started will lead to a higher rate of false‐negative results.76 Unless the patient has no signs of sepsis and microscopy is completely negative, clinicians should then immediately start empiric broad‐spectrum antibiotics.57 Once the culture sensitivities are known, therapy can be deescalated to a narrower spectrum.77 Recent studies suggest that shorter durations of therapy (8 days) are as effective as longer courses and are associated with lower colonization rates by antibiotic‐resistant bacteria.62, 78
Initial broad‐spectrum antibiotics should be chosen based on local bacteriology and resistance patterns. Clinicians must remain aware of the most common bacterial pathogens in their local community, hospital, and ICU. This is essential for both ensuring adequate initial antibiotic coverage and reducing overall antibiotic days.65 Unrestrained use of broad‐spectrum antibiotics increases the risk of resistant pathogens. Clinicians must continually deescalate therapy and use narrow‐spectrum drugs as pathogens are identified.79
Prevention of VAP
In 2005, the American Thoracic Society published guidelines for the management of adults with VAP.5 These guidelines included a discussion of modifiable risk factors for preventing VAP and used an evidence‐based grading system to rank the various recommendations. The highest evidence (level 1) comes from randomized clinical trials, moderate evidence (level 2) comes from nonrandomized studies, and the lowest evidence (level 3) comes from case studies or expert opinion. Others have also published their own guidelines and recommendations for preventing VAP.8082 Table 4 shows the key VAP preventive strategies.
Strategy | Level of evidence | References |
---|---|---|
| ||
General infection control measures (hand hygiene, staff education, isolate MDR pathogens, etc.) | 1 | 2,83,84 |
ICU infection surveillance | 2 | 2,8385 |
Avoid reintubation if possible, but promptly reintubate if a patients inexorably fails extubation | 1 | 2,83,86,87 |
Use NPPV when appropriate (in selected patients) | 1 | 88 |
Use oral route for endotracheal and gastric tubes (vs. nasal route) | 2 | 89 |
Continuous suctioning of subglottic secretions (to avoid pooling on cuff and leakage into LRT) | 1 | 9092 |
Maintain endotracheal cuff pressure > 20 cm H2O (to prevent secretion leakage into LRT) | 2 | 93 |
Avoid unnecessary ventilator circuit changes | 1 | 94 |
Routinely empty condensate in ventilator circuit | 2 | 95 |
Maintain adequate nursing and therapist staffing | 2 | 9698 |
Implement ventilator weaning and sedation protocols | 2 | 99101 |
Semierect patient positioning (vs. supine) | 1 | 102 |
Avoid aspiration when using enteral nutrition | 1 | 103,104 |
Topical oral antisepsis (eg, chlorhexidine) | 1 | 105108 |
Control blood sugar with insulin | 1 | 109 |
Use heat‐moisture exchanger (vs. conventional humidifier) to reduce tubing condensate | 1 | 95 |
Avoid unnecessary red blood cell transfusions | 1 | 110 |
Use of sucralfate for GI prophylaxis | 1 | 111,112 |
Influenza vaccination for health care workers | 2 | 2 |
Some strategies are not recommended for VAP prevention in general ICU patients. Selective decontamination of the digestive tract (ie, prophylactic oral antibiotics) has been shown to reduce respiratory infections in ICU patients,113 but its overall role remains controversial because of concerns it may increase the incidence of multi‐drug‐resistant pathogens.114 Similarly, prophylactic intravenous antibiotics administered at the time of intubation can reduce VAP in certain patient populations,115 but this strategy is also associated with an increased risk of antibiotic‐resistant nosocomial infections.116 Using kinetic beds and scheduled chest physiotherapy to reduce VAP is based on the premise that critically ill patients often develop atelectasis and cannot effectively clear their secretions. Unfortunately, neither of these modalities has been shown to consistently reduce VAP in medical ICU patients.117119
Algorithms for Diagnosis and Treatment of VAP
We present algorithms for diagnosing VAP in 4 ICU populations: infant (1 year old), pediatric (1‐12 years old), immunocompromised, and adult ICU patients (Figs. 14). Because clinicians face considerable uncertainty when diagnosing VAP, we sought to develop practical algorithms for use in daily ICU practice. Although we provided the algorithms to collaborative participants as a tool for improving care, we never mandated use, and we did not monitor levels of adherence.
Five teaching cases are presented in the Appendix. We demonstrate how to utilize the diagnostic algorithms in these clinical scenarios and offer tips for clinicians wishing to employ these tools in their daily practice. These cases are useful for educating residents, nurses, and hospitalists.
Overall, our intent is that the combined use of these VAP algorithms facilitate a streamlined diagnostic approach and minimize delays in initial antibiotic administration. A primary focus of any VAP guideline should be early and appropriate antibiotics in adequate doses, with deescalation of therapy as culture data permit.5 In general, the greatest risk to a patient with VAP is delaying initial adequate antibiotic coverage, and for this reason, antibiotics must always be administered promptly. However, if culture data are negative, the clinician should consider withdrawing unnecessary antibiotics. For example, the absence of gram‐positive organisms on BAL after 72 hours would strongly suggest that MRSA is not playing a role and that vancomycin can be safely stopped. We agree with Neiderman that the decision point is not whether to start antibiotics, but whether to continue them at day 23.57
DISCUSSION
In this article, we introduce algorithms for diagnosing and managing VAP in infant, pediatric, immunocompromised, and adult ICU patients. We developed 4 algorithms because the hospitals in our system care for a wide range of patients. Our definitions for VAP were based on criteria outlined by the CDC because these rigorously developed criteria have been widely disseminated as components of the Institute for Healthcare Improvement's ventilator bundle.120 Clinicians should be able to easily incorporate these practical algorithms into their current practice.
The algorithms were developed during a collaborative across a large national health care system. We undertook this task because many clinicians were uncertain how to integrate the enormous volume of VAP literature into their daily practice, and we suspected there was large variation in practice in our ICUs. Recent studies from other health care systems provided empiric evidence to support this notion.12, 13
We offer these algorithms as practical tools to assist ICU clinicians and not as proscriptive mandates. We realize that the algorithms may need modification based on a hospital's unique bacteriology and patient populations. We also anticipate that the algorithms will adapt to future changes in VAP epidemiology, preventive strategies, emerging pathogens, and new antibiotics.
Numerous resources are available to learn more about VAP management. An excellent guideline from the Infectious Diseases Society of America and the American Thoracic Society discusses VAP issues in detail,5 although this guideline only focuses on immunocompetent adult patients. The journal Respiratory Care organized an international conference with numerous VAP experts in 2005 and subsequently devoted an entire issue to this topic.81 The Canadian Critical Care Trials Group and the Canadian Critical Care Society conducted systematic reviews and developed separate guidelines for the prevention, diagnosis, and treatment of VAP.80, 121
In summary, we present diagnostic and treatment algorithms for VAP. Our intent is that these algorithms may provide evidence‐based practical guidance to clinicians seeking a standardized approach to diagnosing and managing this challenging problem.
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Ventilator‐associated pneumonia (VAP) is a serious and common complication for patients in the intensive care unit (ICU).1 VAP is defined as a pulmonary infection occurring after hospital admission in a mechanically‐ventilated patient with a tracheostomy or endotracheal tube.2, 3 With an attributable mortality that may exceed 20% and an estimated cost of $5000‐$20,000 per episode,49 the management of VAP is an important issue for both patient safety and cost of care.
The diagnosis of VAP is a controversial topic in critical care, primarily because of the difficulty distinguishing between airway colonization, upper respiratory tract infection (eg, tracheobronchitis), and early‐onset pneumonia. Some clinicians insist that an invasive sampling technique (eg, bronchoalveolar lavage) with quantitative cultures is essential for determining the presence of VAP.10 However, other clinicians suggest that a noninvasive approach using qualitative cultures (eg, tracheal suctioning) is an acceptable alternative.11 Regardless, nearly all experts agree that a specimen for microbiologic culture should be obtained prior to initiating antibiotics. Subsequent therapy should then be adjusted according to culture results.
Studies from both Europe and North America have demonstrated considerable variation in the diagnostic approaches used for patients with suspected VAP.12, 13 This variation is likely a result of several factors including controversy about the best diagnostic approach, variation in clinician knowledge and experience, and variation in ICU management protocols. Such practice variability is common for many ICU behaviors.1416 Quality‐of‐care proponents view this variation as an important opportunity for improvement.17
During a recent national collaborative aimed at reducing health careassociated infections in the ICU, we discovered many participants were uncertain about how to diagnose and manage VAP, and considerable practice variability existed among participating hospitals. This uncertainty provided an important opportunity for developing consensus on VAP management. On the basis of diagnostic criteria outlined by the Centers for Disease Control and Prevention (CDC), we developed algorithms as tools for diagnosing VAP in 4 ICU populations: infant, pediatric, immunocompromised, and adult ICU patients. We also developed an algorithm for initial VAP treatment. An interdisciplinary team of experts reviewed the current literature and developed these evidence‐based consensus guidelines. Our intent is that the algorithms provide guidance to clinicians looking for a standardized approach to the diagnosis and management of this complicated clinical situation.
METHODS
Our primary goal was to develop practical algorithms that assist ICU clinicians in the diagnosis and management of VAP during daily practice. To improve the quality and credibility of these algorithms, the development process used a stepwise approach that included assembling an interdisciplinary team of experts, appraising the published evidence, and formulating the algorithms through a consensus process.18
AHRQ National Collaborative
We developed these diagnostic algorithms as part of a national collaborative effort aimed at reducing VAP and central venous catheterrelated bloodstream infections in the ICU. This effort was possible through a 2‐year Partnerships in Implementing Patient Safety grant funded by the Agency for Healthcare Research and Quality (AHRQ).19 The voluntary collaborative was conducted in 61 medical/surgical and children's hospitals across the Hospital Corporation of America (HCA), a company that owns and/or operates 173 hospitals and 107 freestanding surgery centers in 20 states, England, and Switzerland. HCA is one of the largest providers of health care in the United States. All participating hospitals had at least 1 ICU, and a total of 110 ICUs were included in the project. Most hospitals were in the southern or southeastern regions of the United States.
Interdisciplinary Team
We assembled an interdisciplinary team to develop the diagnostic algorithms. Individuals on the team represented the specialties of infectious diseases, infection control, anesthesia, critical care medicine, hospital medicine, critical care nursing, pharmacy, and biostatistics. The development phase occurred over 34 months and used an iterative process that consisted of both group conference calls and in‐person meetings.
Our goal was not to conduct a systematic review but rather to develop practical algorithms for collaborative participants in a timely manner. Our literature search strategy included MEDLINE and the Cochrane Library. We focused on articles that addressed key diagnostic issues, proposed an algorithm, or summarized a topic relevant to practicing clinicians. Extra attention was given to articles that were randomized trials, meta‐analyses, or systematic reviews. No explicit grading of articles was performed. We examined studies with outcomes of interest to clinicians, including mortality, number of ventilator days, length of stay, antibiotic utilization, and antibiotic resistance.
We screened potentially relevant articles and the references of these articles. The search results were reviewed by all members of the team, and an iterative consensus process was used to derive the current algorithms. Preliminary versions of the algorithms were shown to other AHRQ investigators and outside experts in the field, and additional modifications were made based on their feedback. The final algorithms were approved by all study investigators.
RESULTS
Literature Overview
Overall, there is an enormous body of published literature on diagnosing and managing VAP. The Medline database has listed more than 500 articles on VAP diagnosis in the past decade. Nonetheless, the best diagnostic approach remains unclear. The gold standard for diagnosing VAP is lung biopsy with histopathologic examination and tissue culture. However, this procedure is fraught with potential dangers and impractical for most critically ill patients.20 Therefore, practitioners traditionally combine their clinical suspicion (based on fever, leukocytosis, character of sputum, and radiographic changes), epidemiologic data (eg, patient demographics, medical history, and ICU infection surveillance data), and microbiologic data.
Several issues relevant to practicing clinicians deserve further mention.
Definition of VAP
Although early articles used variable criteria for diagnosing VAP, recent studies have traditionally defined VAP as an infection occurring more than 48 hours after hospital admission in a mechanically ventilated patient with a tracheostomy or endotracheal tube.2 In early 2007, the CDC revised their definition for diagnosing VAP.3 These latest criteria state there is no minimum period that the ventilator must be in place in order to diagnose VAP. This important change must be kept in mind when examining future studies.
The term VAP is more specific than the term health careassociated pneumonia. The latter encompasses patients residing in a nursing home or long‐term care facility; hospitalized in an acute care hospital for more than 48 hours in the past 90 days; receiving antibiotics, chemotherapy, or wound care within the past 30 days; or attending a hospital or hemodialysis clinic.
The CDC published detailed criteria for diagnosing VAP in its member hospitals (Tables 1 and 2).3 Because diagnosing VAP in infants, children, elderly, and immunocompromised patients is often confusing because of other conditions with similar signs and symptoms, the CDC published alternate criteria for these populations. A key objective during development of our algorithms was to consolidate and simplify these diagnostic criteria for ICU clinicians.
Radiology | Signs/symptoms/laboratory |
---|---|
| |
Two or more serial chest radiographs with at least 1 of the following*: | CRITERIA FOR ANY PATIENT |
New or progressive and persistent infiltrate | At least 1 of the following: |
Consolidation | Fever (>38C or >100.4F) with no other recognized cause |
Cavitation | Leukopenia (<4000 WBC/mm3) or leukocytosis (12,000 WBC/mm3) |
Pneumatoceles, in infants 1 year old | For adults 70 years old, altered mental status with no other recognized causeand |
Note: In patients without underlying pulmonary or cardiac disease (eg, respiratory distress syndrome, bronchopulmonary dysplasia, pulmonary edema, or chronic obstructive pulmonary disease), 1 definitive chest radiograph is acceptable.* | |
At least 2 of the following: | |
New onset of purulent sputum, or change in character of sputum, or increased respiratory secretions, or increased suctioning requirements | |
New‐onset or worsening cough or dyspnea or tachypnea‖ | |
Rales or bronchial breath sounds | |
Worsening gas exchange (eg, O2 desaturation [eg, PaO2/FiO2 240],** increased oxygen requirement, or increased ventilation demand) | |
Any laboratory criterion from Table 2 |
|
ALTERNATE CRITERIA FOR INFANTS 1 YEAR OLD | |
Worsening gas exchange (eg, O2 desaturation, increased ventilation demand or O2 requirement) | |
and | |
At least 3 of the following: | |
Temperature instability with no other recognized cause | |
Leukopenia (<4000 WBC/mm3) or leukocytosis (15,000 WBC/mm3) and left shift (10% bands) | |
New‐onset purulent sputum, change in character of sputum, increased respiratory secretions, or increased suctioning requirements | |
Apnea, tachypnea,‖ nasal flaring with retraction of chest wall, or grunting | |
Wheezing, rales, or rhonchi | |
Cough | |
Bradycadia (<100 beats/min) or tachycardia (>170 beats/min) | |
ALTERNATE CRITERIA FOR CHILD >1 OR 12 YEARS OLD | |
At least 3 of the following: | |
Fever (>38.4C or >101.1F) or hypothermia (<36.5C or <97.7F) with no other recognized cause | |
Leukopenia (<4000 WBC/mm3) or leukocytosis (15,000 WBC/mm3) | |
New‐onset purulent sputum, change in character of sputum, increased respiratory secretions, or increased suctioning requirements | |
New‐onset or worsening cough or dyspnea, apnea, or tachypnea‖ | |
Rales or bronchial breath sounds | |
Worsening gas exchange (eg, O2 desaturation <94%, increased ventilation demand or O2 requirement) | |
Any laboratory criterion from Table 2 |
|
ALTERNATE CRITERIA FOR IMMUNOCOMPROMISED PATIENTS*** | |
At least 1 of the following: | |
Fever (>38.4C or >101.1F) with no other recognized cause | |
For adults > 70 years old, altered mental status with no other recognized cause | |
New‐onset purulent sputum, change in character of sputum, increased respiratory secretions, or increased suctioning requirements | |
New‐onset or worsening cough, dyspnea, or tachypnea‖ | |
Rales or bronchial breath sounds | |
Worsening gas exchange (eg, O2 desaturation [eg, PaO2/FiO2 240],** increased oxygen requirement, or increased ventilation demand) | |
Hemoptysis | |
Pleuritic chest pain | |
Matching positive blood and sputum cultures with Candida spp. | |
Evidence of fungi or Pneumocytis from minimally contaminated LRT specimen (eg, BAL or protected specimen brushing) from 1 of the following: | |
Direct microscopic exam | |
Positive culture of fungi | |
Any laboratory criterion from Table 2 |
|
Positive growth in blood culture* not related to another source of infection |
Positive growth in culture of pleural fluid |
Positive quantitative culture from minimally contaminated LRT specimen (eg, BAL) |
5% BAL‐obtained cells contain intracellular bacteria on direct microscopic exam (eg, gram stain) |
Histopathologic exam shows at least 1 of the following: |
Abscess formation or foci of consolidation with intense PMN accumulation in bronchioles and alveoli |
Positive quantitative culture of lung parenchyma |
Evidence of lung parenchyma invasion by fungal hyphae or pseudohyphae |
Positive culture of virus or Chlamydia from respiratory secretions |
Positive detection of viral antigen or antibody from respiratory secretions (eg, EIA, FAMA, shell vial assay, PCR) |
Fourfold rise in paired sera (IgG) for pathogen (eg, influenza viruses, Chlamydia) |
Positive PCR for Chlamydia or Mycoplasma |
Positive micro‐IF test for Chlamydia |
Positive culture or visualization by micro‐IF of Legionella spp. from respiratory secretions or tissue |
Detection of Legionella pneumophila serogroup 1 antigens in urine by RIA or EIA |
Fourfold rise in L. pneumophila serogroup 1 antibody titer to 1:128 in paired acute and convalescent sera by indirect IFA |
Etiology
The most commonly isolated VAP pathogens in all patients are bacteria.21 Most of these organisms normally colonize the respiratory and gastrointestinal tracts, but some are unique to health care settings. Tracheal intubation disrupts the body's natural anatomic and physiologic defenses and facilitates easier entry of these pathogens. Typical organisms include Staphylococcus aureus, Pseudomonas aeruginosa, Enterobacter species, Klebsiella pneumoniae, Acinetobacter species, Escherichia coli, and Haemophilus influenzae.22, 23 Unfortunately, the prevalence of antimicrobial resistance among VAP pathogens is increasing.24 Risk factors for antibiotic resistance are common to ICU patients and include recent antibiotics, hemodialysis, nursing home residence, immunosuppression, and chronic wound care.5 Polymicrobial infections are frequently seen in VAP, with up to 50% of all VAP episodes caused by more than 1 organism.25
Viral VAP is rare in immunocompetent hosts, and seasonal outbreaks of influenza and other similar viruses are usually limited to nonventilated patients.26 However, influenza is underrecognized as a potential nosocomial pathogen, and numerous nosocomial outbreaks because of influenza have been reported.2731 Although herpes simplex virus is often detected in the respiratory tract of critically ill patients, its clinical importance remains unclear.32
Fungal VAP is also rare in immunocompetent hosts. On the other hand, pulmonary fungal infections are common in immunocompromised patients, especially following chemotherapy and transplantation. Candida species are often isolated from the airways of normal hosts, but most cases traditionally have been considered clinically unimportant because these organisms are normal oropharyngeal flora and rarely invade lung tissue.33, 34 It is unclear whether recent studies suggesting Candida colonization is associated with a higher risk for Pseudomonas VAP will change this conventional wisdom.3537
Immunocompromised patients with suspected VAP are unique because they are at risk not only for typical bacteria (which are the most common causes of VAP) but also for rarer opportunistic infections and noninfectious processes that mimic pneumonia.3840 While assessing these patients, clinicians must consider the status of the underlying disease, duration and type of immunosuppression, prophylactic regimens, and risk factors for noninfectious causes of pulmonary infiltrates.41 Common opportunistic infections include viruses, mycobacteria, fungi, and Pneumocystis. Noninfectious processes include pulmonary edema, drug toxicity, radiation pneumonitis, engraftment syndrome, bronchiolitis obliterans organizing pneumonia, alveolar proteinosis, transfusion‐related lung injury, alveolar hemorrhage, and progression of underlying disease. In general, diagnosing VAP in the immunocompromised patient requires a prompt, comprehensive, and multidisciplinary approach.38
In preterm and term infants, the most common VAP pathogens are gram‐negative organisms such as E. coli and P. aeruginosa. Other less common pathogens are Enterobacter, Klebsiella, Acinetobacter, Proteus, Citrobacter, and Stenotrophomonas maltophilia.42, 43 Infants with a preceding bloodstream infection or prolonged intubation are more likely to develop VAP.43, 44 Unfortunately, gram‐negative bacteria often colonize the airways of mechanically ventilated infants, and tracheal aspirate culture data are difficult to interpret in this population.42
Children are more likely to develop VAP if they are intubated for more than 48 hours. The most common pathogens isolated from tracheal aspirates in mechanically ventilated children are enteric gram‐negative bacteria, P. aeruginosa, and S. aureus.45, 46 Few studies have precisely delineated the pathogenesis of VAP in the pediatric ICU population.
Overall, the causes of VAP vary by hospital, patient population, and ICU type. Therefore, it is essential that ICU clinicians remain knowledgeable about their local surveillance data.21 Awareness of VAP microbiology is essential for optimizing initial antibiotic therapy and improving outcomes.
Early Versus Late VAP
Distinguishing between early and late VAP is important for initial antibiotic selection because the etiologic pathogens vary between these 2 periods.4749 Early VAP (days 14 of hospitalization) usually involves antibiotic‐sensitive community‐acquired bacteria and carries a better prognosis. In contrast, late VAP (5 days after hospital admission) is more likely to be caused by antibiotic‐resistant nosocomial bacteria that lead to increased morbidity and mortality. All patients who have been hospitalized or have received antibiotics during the prior 90 days should be treated as having late VAP because they are at much higher risk for colonization and infection with antibiotic‐resistant bacteria.47 Of note, 2 recent studies suggest that pathogens in the early and late periods are becoming similar at some institutions.50, 51 Overall, the distinction between early and late VAP is important because it affects the likelihood that a patient has antibiotic‐resistant bacteria. If antibiotic‐resistant pathogens are suspected, initial therapy should include empiric triple antibiotics until culture data are available.
Culturing Approaches
Because clinical criteria alone are rarely able to accurately diagnose VAP,52, 53 clinicians should also obtain a respiratory specimen for microbiologic culture. Despite the convenience of blood cultures, their sensitivity for diagnosing VAP is poor, and they rarely make the diagnosis alone.54 Two methods are available for culturing the lungsan invasive approach (eg, bronchoscopy with bronchoalveolar lavage) and a noninvasive approach (eg, tracheal aspirate).
Some investigators believe that adult patients with suspected VAP should always undergo an invasive sampling of lower‐respiratory‐tract secretions.55 Proponents of the invasive approach cite the frequency with which potential pathogens colonize the trachea of ICU patients and create spurious results on tracheal aspirates.22 In addition, several studies have shown that clinicians are more likely to narrow the spectrum of antibiotics after obtaining an invasive diagnostic sample.56 In other words, the invasive approach has been associated with better antimicrobial stewardship.
Other investigators believe that a noninvasive approach is equally safe and effective for diagnosing VAP.57 This clinical approach involves culturing a tracheal aspirate and using a pneumonia prediction score such as the clinical pulmonary infection score (CPIS; Table 3). The CPIS assigns 012 points based on 6 clinical criteria: fever, leukocyte count, oxygenation, quantity and purulence of secretions, type of radiographic abnormality, and results of sputum gram stain and culture.58 As developed, a CPIS > 6 has a sensitivity of 93% and a specificity of 100% for diagnosing VAP.58 However, the CPIS requires that nurses record sputum volume and that the laboratory stains the specimen. When the CPIS has been modified based on the unavailability of such resources, the results have been less impressive.5961 Despite studies showing that a noninvasive clinical approach can achieve adequate initial antibiotic coverage and reduce overuse of broad‐spectrum agents,62, 63 clinicians who use the CPIS must understand its inherent limitations.
Criterion | Range | Score |
---|---|---|
| ||
Temperature (C) | 36.138.4 | 0 |
38.538.9 | 1 | |
39 or 36 | 2 | |
Blood leukocytes (/mm3) | 4000 and 11,000 | 0 |
<4000 or >11,000 | 1 | |
+ band forms 500 | 2 | |
Oxygenation: PaO2/FiO2 (mmHg) | >240 or ARDS | 0 |
240 and no evidence of ARDS | 2 | |
Chest radiograph | No infiltrate | 0 |
Diffuse (or patchy) infiltrate | 1 | |
Localized infiltrate | 2 | |
Tracheal secretions | Absence of tracheal secretions | 0 |
Nonpurulent tracheal secretions | 1 | |
Purulent tracheal secretions | 2 | |
Culture of tracheal aspirate | Pathogenic bacteria culture: no growth or light growth | 0 |
Pathogenic bacteria culture: moderate/heavy growth | 1 | |
Same pathogenic bacteria seen on gram stain (add 1 point) | 2 |
A meta‐analysis56 comparing the utility of an invasive versus a noninvasive culturing approach identified 4 randomized trials examining this issue.6669 Overall, an invasive approach did not alter mortality, but patients undergoing bronchoscopy were much more likely to have their antibiotic regimens modified by clinicians. This suggests that the invasive approach may allow more directed use of antibiotics. Recently, the Canadian Critical Care Trials Group conducted a multicenter randomized trial looking at this issue.11 There was no difference between the 2 approaches in mortality, number of ventilator days, and antibiotic usage. However, all patients in this study were immediately treated with empiric broad‐spectrum antibiotics until culture results were available, and the investigators did not have a protocol for stopping antibiotics after culture data were available.
In summary, both invasive and noninvasive culturing approaches are considered acceptable options for diagnosing VAP. Readers interested in learning more about this topic should read the worthwhile Expert Discussion70 by Chastre and colleagues55 at the end of this article. In general, we recommend that ICU clinicians use a combination of clinical suspicion (based on the CPIS or other objective data) and cultures ideally obtained prior to antibiotics. Regardless of the chosen culturing approach, clinicians must recognize that 1 of the most important determinants of patient outcome is prompt administration of adequate initial antibiotics.7175
Initial Antibiotic Administration
Delaying initial antibiotics in VAP increases the risk of death.7175 If a patient receives ineffective initial therapy, a later switch to appropriate therapy does not eliminate the increased mortality risk. Therefore, a comprehensive approach to VAP diagnosis requires consideration of initial empiric antibiotic administration.
Whenever possible, clinicians should obtain a lower respiratory tract sample for microscopy and culture before administering antibiotics because performing cultures after antibiotics have been recently started will lead to a higher rate of false‐negative results.76 Unless the patient has no signs of sepsis and microscopy is completely negative, clinicians should then immediately start empiric broad‐spectrum antibiotics.57 Once the culture sensitivities are known, therapy can be deescalated to a narrower spectrum.77 Recent studies suggest that shorter durations of therapy (8 days) are as effective as longer courses and are associated with lower colonization rates by antibiotic‐resistant bacteria.62, 78
Initial broad‐spectrum antibiotics should be chosen based on local bacteriology and resistance patterns. Clinicians must remain aware of the most common bacterial pathogens in their local community, hospital, and ICU. This is essential for both ensuring adequate initial antibiotic coverage and reducing overall antibiotic days.65 Unrestrained use of broad‐spectrum antibiotics increases the risk of resistant pathogens. Clinicians must continually deescalate therapy and use narrow‐spectrum drugs as pathogens are identified.79
Prevention of VAP
In 2005, the American Thoracic Society published guidelines for the management of adults with VAP.5 These guidelines included a discussion of modifiable risk factors for preventing VAP and used an evidence‐based grading system to rank the various recommendations. The highest evidence (level 1) comes from randomized clinical trials, moderate evidence (level 2) comes from nonrandomized studies, and the lowest evidence (level 3) comes from case studies or expert opinion. Others have also published their own guidelines and recommendations for preventing VAP.8082 Table 4 shows the key VAP preventive strategies.
Strategy | Level of evidence | References |
---|---|---|
| ||
General infection control measures (hand hygiene, staff education, isolate MDR pathogens, etc.) | 1 | 2,83,84 |
ICU infection surveillance | 2 | 2,8385 |
Avoid reintubation if possible, but promptly reintubate if a patients inexorably fails extubation | 1 | 2,83,86,87 |
Use NPPV when appropriate (in selected patients) | 1 | 88 |
Use oral route for endotracheal and gastric tubes (vs. nasal route) | 2 | 89 |
Continuous suctioning of subglottic secretions (to avoid pooling on cuff and leakage into LRT) | 1 | 9092 |
Maintain endotracheal cuff pressure > 20 cm H2O (to prevent secretion leakage into LRT) | 2 | 93 |
Avoid unnecessary ventilator circuit changes | 1 | 94 |
Routinely empty condensate in ventilator circuit | 2 | 95 |
Maintain adequate nursing and therapist staffing | 2 | 9698 |
Implement ventilator weaning and sedation protocols | 2 | 99101 |
Semierect patient positioning (vs. supine) | 1 | 102 |
Avoid aspiration when using enteral nutrition | 1 | 103,104 |
Topical oral antisepsis (eg, chlorhexidine) | 1 | 105108 |
Control blood sugar with insulin | 1 | 109 |
Use heat‐moisture exchanger (vs. conventional humidifier) to reduce tubing condensate | 1 | 95 |
Avoid unnecessary red blood cell transfusions | 1 | 110 |
Use of sucralfate for GI prophylaxis | 1 | 111,112 |
Influenza vaccination for health care workers | 2 | 2 |
Some strategies are not recommended for VAP prevention in general ICU patients. Selective decontamination of the digestive tract (ie, prophylactic oral antibiotics) has been shown to reduce respiratory infections in ICU patients,113 but its overall role remains controversial because of concerns it may increase the incidence of multi‐drug‐resistant pathogens.114 Similarly, prophylactic intravenous antibiotics administered at the time of intubation can reduce VAP in certain patient populations,115 but this strategy is also associated with an increased risk of antibiotic‐resistant nosocomial infections.116 Using kinetic beds and scheduled chest physiotherapy to reduce VAP is based on the premise that critically ill patients often develop atelectasis and cannot effectively clear their secretions. Unfortunately, neither of these modalities has been shown to consistently reduce VAP in medical ICU patients.117119
Algorithms for Diagnosis and Treatment of VAP
We present algorithms for diagnosing VAP in 4 ICU populations: infant (1 year old), pediatric (1‐12 years old), immunocompromised, and adult ICU patients (Figs. 14). Because clinicians face considerable uncertainty when diagnosing VAP, we sought to develop practical algorithms for use in daily ICU practice. Although we provided the algorithms to collaborative participants as a tool for improving care, we never mandated use, and we did not monitor levels of adherence.
Five teaching cases are presented in the Appendix. We demonstrate how to utilize the diagnostic algorithms in these clinical scenarios and offer tips for clinicians wishing to employ these tools in their daily practice. These cases are useful for educating residents, nurses, and hospitalists.
Overall, our intent is that the combined use of these VAP algorithms facilitate a streamlined diagnostic approach and minimize delays in initial antibiotic administration. A primary focus of any VAP guideline should be early and appropriate antibiotics in adequate doses, with deescalation of therapy as culture data permit.5 In general, the greatest risk to a patient with VAP is delaying initial adequate antibiotic coverage, and for this reason, antibiotics must always be administered promptly. However, if culture data are negative, the clinician should consider withdrawing unnecessary antibiotics. For example, the absence of gram‐positive organisms on BAL after 72 hours would strongly suggest that MRSA is not playing a role and that vancomycin can be safely stopped. We agree with Neiderman that the decision point is not whether to start antibiotics, but whether to continue them at day 23.57
DISCUSSION
In this article, we introduce algorithms for diagnosing and managing VAP in infant, pediatric, immunocompromised, and adult ICU patients. We developed 4 algorithms because the hospitals in our system care for a wide range of patients. Our definitions for VAP were based on criteria outlined by the CDC because these rigorously developed criteria have been widely disseminated as components of the Institute for Healthcare Improvement's ventilator bundle.120 Clinicians should be able to easily incorporate these practical algorithms into their current practice.
The algorithms were developed during a collaborative across a large national health care system. We undertook this task because many clinicians were uncertain how to integrate the enormous volume of VAP literature into their daily practice, and we suspected there was large variation in practice in our ICUs. Recent studies from other health care systems provided empiric evidence to support this notion.12, 13
We offer these algorithms as practical tools to assist ICU clinicians and not as proscriptive mandates. We realize that the algorithms may need modification based on a hospital's unique bacteriology and patient populations. We also anticipate that the algorithms will adapt to future changes in VAP epidemiology, preventive strategies, emerging pathogens, and new antibiotics.
Numerous resources are available to learn more about VAP management. An excellent guideline from the Infectious Diseases Society of America and the American Thoracic Society discusses VAP issues in detail,5 although this guideline only focuses on immunocompetent adult patients. The journal Respiratory Care organized an international conference with numerous VAP experts in 2005 and subsequently devoted an entire issue to this topic.81 The Canadian Critical Care Trials Group and the Canadian Critical Care Society conducted systematic reviews and developed separate guidelines for the prevention, diagnosis, and treatment of VAP.80, 121
In summary, we present diagnostic and treatment algorithms for VAP. Our intent is that these algorithms may provide evidence‐based practical guidance to clinicians seeking a standardized approach to diagnosing and managing this challenging problem.
Ventilator‐associated pneumonia (VAP) is a serious and common complication for patients in the intensive care unit (ICU).1 VAP is defined as a pulmonary infection occurring after hospital admission in a mechanically‐ventilated patient with a tracheostomy or endotracheal tube.2, 3 With an attributable mortality that may exceed 20% and an estimated cost of $5000‐$20,000 per episode,49 the management of VAP is an important issue for both patient safety and cost of care.
The diagnosis of VAP is a controversial topic in critical care, primarily because of the difficulty distinguishing between airway colonization, upper respiratory tract infection (eg, tracheobronchitis), and early‐onset pneumonia. Some clinicians insist that an invasive sampling technique (eg, bronchoalveolar lavage) with quantitative cultures is essential for determining the presence of VAP.10 However, other clinicians suggest that a noninvasive approach using qualitative cultures (eg, tracheal suctioning) is an acceptable alternative.11 Regardless, nearly all experts agree that a specimen for microbiologic culture should be obtained prior to initiating antibiotics. Subsequent therapy should then be adjusted according to culture results.
Studies from both Europe and North America have demonstrated considerable variation in the diagnostic approaches used for patients with suspected VAP.12, 13 This variation is likely a result of several factors including controversy about the best diagnostic approach, variation in clinician knowledge and experience, and variation in ICU management protocols. Such practice variability is common for many ICU behaviors.1416 Quality‐of‐care proponents view this variation as an important opportunity for improvement.17
During a recent national collaborative aimed at reducing health careassociated infections in the ICU, we discovered many participants were uncertain about how to diagnose and manage VAP, and considerable practice variability existed among participating hospitals. This uncertainty provided an important opportunity for developing consensus on VAP management. On the basis of diagnostic criteria outlined by the Centers for Disease Control and Prevention (CDC), we developed algorithms as tools for diagnosing VAP in 4 ICU populations: infant, pediatric, immunocompromised, and adult ICU patients. We also developed an algorithm for initial VAP treatment. An interdisciplinary team of experts reviewed the current literature and developed these evidence‐based consensus guidelines. Our intent is that the algorithms provide guidance to clinicians looking for a standardized approach to the diagnosis and management of this complicated clinical situation.
METHODS
Our primary goal was to develop practical algorithms that assist ICU clinicians in the diagnosis and management of VAP during daily practice. To improve the quality and credibility of these algorithms, the development process used a stepwise approach that included assembling an interdisciplinary team of experts, appraising the published evidence, and formulating the algorithms through a consensus process.18
AHRQ National Collaborative
We developed these diagnostic algorithms as part of a national collaborative effort aimed at reducing VAP and central venous catheterrelated bloodstream infections in the ICU. This effort was possible through a 2‐year Partnerships in Implementing Patient Safety grant funded by the Agency for Healthcare Research and Quality (AHRQ).19 The voluntary collaborative was conducted in 61 medical/surgical and children's hospitals across the Hospital Corporation of America (HCA), a company that owns and/or operates 173 hospitals and 107 freestanding surgery centers in 20 states, England, and Switzerland. HCA is one of the largest providers of health care in the United States. All participating hospitals had at least 1 ICU, and a total of 110 ICUs were included in the project. Most hospitals were in the southern or southeastern regions of the United States.
Interdisciplinary Team
We assembled an interdisciplinary team to develop the diagnostic algorithms. Individuals on the team represented the specialties of infectious diseases, infection control, anesthesia, critical care medicine, hospital medicine, critical care nursing, pharmacy, and biostatistics. The development phase occurred over 34 months and used an iterative process that consisted of both group conference calls and in‐person meetings.
Our goal was not to conduct a systematic review but rather to develop practical algorithms for collaborative participants in a timely manner. Our literature search strategy included MEDLINE and the Cochrane Library. We focused on articles that addressed key diagnostic issues, proposed an algorithm, or summarized a topic relevant to practicing clinicians. Extra attention was given to articles that were randomized trials, meta‐analyses, or systematic reviews. No explicit grading of articles was performed. We examined studies with outcomes of interest to clinicians, including mortality, number of ventilator days, length of stay, antibiotic utilization, and antibiotic resistance.
We screened potentially relevant articles and the references of these articles. The search results were reviewed by all members of the team, and an iterative consensus process was used to derive the current algorithms. Preliminary versions of the algorithms were shown to other AHRQ investigators and outside experts in the field, and additional modifications were made based on their feedback. The final algorithms were approved by all study investigators.
RESULTS
Literature Overview
Overall, there is an enormous body of published literature on diagnosing and managing VAP. The Medline database has listed more than 500 articles on VAP diagnosis in the past decade. Nonetheless, the best diagnostic approach remains unclear. The gold standard for diagnosing VAP is lung biopsy with histopathologic examination and tissue culture. However, this procedure is fraught with potential dangers and impractical for most critically ill patients.20 Therefore, practitioners traditionally combine their clinical suspicion (based on fever, leukocytosis, character of sputum, and radiographic changes), epidemiologic data (eg, patient demographics, medical history, and ICU infection surveillance data), and microbiologic data.
Several issues relevant to practicing clinicians deserve further mention.
Definition of VAP
Although early articles used variable criteria for diagnosing VAP, recent studies have traditionally defined VAP as an infection occurring more than 48 hours after hospital admission in a mechanically ventilated patient with a tracheostomy or endotracheal tube.2 In early 2007, the CDC revised their definition for diagnosing VAP.3 These latest criteria state there is no minimum period that the ventilator must be in place in order to diagnose VAP. This important change must be kept in mind when examining future studies.
The term VAP is more specific than the term health careassociated pneumonia. The latter encompasses patients residing in a nursing home or long‐term care facility; hospitalized in an acute care hospital for more than 48 hours in the past 90 days; receiving antibiotics, chemotherapy, or wound care within the past 30 days; or attending a hospital or hemodialysis clinic.
The CDC published detailed criteria for diagnosing VAP in its member hospitals (Tables 1 and 2).3 Because diagnosing VAP in infants, children, elderly, and immunocompromised patients is often confusing because of other conditions with similar signs and symptoms, the CDC published alternate criteria for these populations. A key objective during development of our algorithms was to consolidate and simplify these diagnostic criteria for ICU clinicians.
Radiology | Signs/symptoms/laboratory |
---|---|
| |
Two or more serial chest radiographs with at least 1 of the following*: | CRITERIA FOR ANY PATIENT |
New or progressive and persistent infiltrate | At least 1 of the following: |
Consolidation | Fever (>38C or >100.4F) with no other recognized cause |
Cavitation | Leukopenia (<4000 WBC/mm3) or leukocytosis (12,000 WBC/mm3) |
Pneumatoceles, in infants 1 year old | For adults 70 years old, altered mental status with no other recognized causeand |
Note: In patients without underlying pulmonary or cardiac disease (eg, respiratory distress syndrome, bronchopulmonary dysplasia, pulmonary edema, or chronic obstructive pulmonary disease), 1 definitive chest radiograph is acceptable.* | |
At least 2 of the following: | |
New onset of purulent sputum, or change in character of sputum, or increased respiratory secretions, or increased suctioning requirements | |
New‐onset or worsening cough or dyspnea or tachypnea‖ | |
Rales or bronchial breath sounds | |
Worsening gas exchange (eg, O2 desaturation [eg, PaO2/FiO2 240],** increased oxygen requirement, or increased ventilation demand) | |
Any laboratory criterion from Table 2 |
|
ALTERNATE CRITERIA FOR INFANTS 1 YEAR OLD | |
Worsening gas exchange (eg, O2 desaturation, increased ventilation demand or O2 requirement) | |
and | |
At least 3 of the following: | |
Temperature instability with no other recognized cause | |
Leukopenia (<4000 WBC/mm3) or leukocytosis (15,000 WBC/mm3) and left shift (10% bands) | |
New‐onset purulent sputum, change in character of sputum, increased respiratory secretions, or increased suctioning requirements | |
Apnea, tachypnea,‖ nasal flaring with retraction of chest wall, or grunting | |
Wheezing, rales, or rhonchi | |
Cough | |
Bradycadia (<100 beats/min) or tachycardia (>170 beats/min) | |
ALTERNATE CRITERIA FOR CHILD >1 OR 12 YEARS OLD | |
At least 3 of the following: | |
Fever (>38.4C or >101.1F) or hypothermia (<36.5C or <97.7F) with no other recognized cause | |
Leukopenia (<4000 WBC/mm3) or leukocytosis (15,000 WBC/mm3) | |
New‐onset purulent sputum, change in character of sputum, increased respiratory secretions, or increased suctioning requirements | |
New‐onset or worsening cough or dyspnea, apnea, or tachypnea‖ | |
Rales or bronchial breath sounds | |
Worsening gas exchange (eg, O2 desaturation <94%, increased ventilation demand or O2 requirement) | |
Any laboratory criterion from Table 2 |
|
ALTERNATE CRITERIA FOR IMMUNOCOMPROMISED PATIENTS*** | |
At least 1 of the following: | |
Fever (>38.4C or >101.1F) with no other recognized cause | |
For adults > 70 years old, altered mental status with no other recognized cause | |
New‐onset purulent sputum, change in character of sputum, increased respiratory secretions, or increased suctioning requirements | |
New‐onset or worsening cough, dyspnea, or tachypnea‖ | |
Rales or bronchial breath sounds | |
Worsening gas exchange (eg, O2 desaturation [eg, PaO2/FiO2 240],** increased oxygen requirement, or increased ventilation demand) | |
Hemoptysis | |
Pleuritic chest pain | |
Matching positive blood and sputum cultures with Candida spp. | |
Evidence of fungi or Pneumocytis from minimally contaminated LRT specimen (eg, BAL or protected specimen brushing) from 1 of the following: | |
Direct microscopic exam | |
Positive culture of fungi | |
Any laboratory criterion from Table 2 |
|
Positive growth in blood culture* not related to another source of infection |
Positive growth in culture of pleural fluid |
Positive quantitative culture from minimally contaminated LRT specimen (eg, BAL) |
5% BAL‐obtained cells contain intracellular bacteria on direct microscopic exam (eg, gram stain) |
Histopathologic exam shows at least 1 of the following: |
Abscess formation or foci of consolidation with intense PMN accumulation in bronchioles and alveoli |
Positive quantitative culture of lung parenchyma |
Evidence of lung parenchyma invasion by fungal hyphae or pseudohyphae |
Positive culture of virus or Chlamydia from respiratory secretions |
Positive detection of viral antigen or antibody from respiratory secretions (eg, EIA, FAMA, shell vial assay, PCR) |
Fourfold rise in paired sera (IgG) for pathogen (eg, influenza viruses, Chlamydia) |
Positive PCR for Chlamydia or Mycoplasma |
Positive micro‐IF test for Chlamydia |
Positive culture or visualization by micro‐IF of Legionella spp. from respiratory secretions or tissue |
Detection of Legionella pneumophila serogroup 1 antigens in urine by RIA or EIA |
Fourfold rise in L. pneumophila serogroup 1 antibody titer to 1:128 in paired acute and convalescent sera by indirect IFA |
Etiology
The most commonly isolated VAP pathogens in all patients are bacteria.21 Most of these organisms normally colonize the respiratory and gastrointestinal tracts, but some are unique to health care settings. Tracheal intubation disrupts the body's natural anatomic and physiologic defenses and facilitates easier entry of these pathogens. Typical organisms include Staphylococcus aureus, Pseudomonas aeruginosa, Enterobacter species, Klebsiella pneumoniae, Acinetobacter species, Escherichia coli, and Haemophilus influenzae.22, 23 Unfortunately, the prevalence of antimicrobial resistance among VAP pathogens is increasing.24 Risk factors for antibiotic resistance are common to ICU patients and include recent antibiotics, hemodialysis, nursing home residence, immunosuppression, and chronic wound care.5 Polymicrobial infections are frequently seen in VAP, with up to 50% of all VAP episodes caused by more than 1 organism.25
Viral VAP is rare in immunocompetent hosts, and seasonal outbreaks of influenza and other similar viruses are usually limited to nonventilated patients.26 However, influenza is underrecognized as a potential nosocomial pathogen, and numerous nosocomial outbreaks because of influenza have been reported.2731 Although herpes simplex virus is often detected in the respiratory tract of critically ill patients, its clinical importance remains unclear.32
Fungal VAP is also rare in immunocompetent hosts. On the other hand, pulmonary fungal infections are common in immunocompromised patients, especially following chemotherapy and transplantation. Candida species are often isolated from the airways of normal hosts, but most cases traditionally have been considered clinically unimportant because these organisms are normal oropharyngeal flora and rarely invade lung tissue.33, 34 It is unclear whether recent studies suggesting Candida colonization is associated with a higher risk for Pseudomonas VAP will change this conventional wisdom.3537
Immunocompromised patients with suspected VAP are unique because they are at risk not only for typical bacteria (which are the most common causes of VAP) but also for rarer opportunistic infections and noninfectious processes that mimic pneumonia.3840 While assessing these patients, clinicians must consider the status of the underlying disease, duration and type of immunosuppression, prophylactic regimens, and risk factors for noninfectious causes of pulmonary infiltrates.41 Common opportunistic infections include viruses, mycobacteria, fungi, and Pneumocystis. Noninfectious processes include pulmonary edema, drug toxicity, radiation pneumonitis, engraftment syndrome, bronchiolitis obliterans organizing pneumonia, alveolar proteinosis, transfusion‐related lung injury, alveolar hemorrhage, and progression of underlying disease. In general, diagnosing VAP in the immunocompromised patient requires a prompt, comprehensive, and multidisciplinary approach.38
In preterm and term infants, the most common VAP pathogens are gram‐negative organisms such as E. coli and P. aeruginosa. Other less common pathogens are Enterobacter, Klebsiella, Acinetobacter, Proteus, Citrobacter, and Stenotrophomonas maltophilia.42, 43 Infants with a preceding bloodstream infection or prolonged intubation are more likely to develop VAP.43, 44 Unfortunately, gram‐negative bacteria often colonize the airways of mechanically ventilated infants, and tracheal aspirate culture data are difficult to interpret in this population.42
Children are more likely to develop VAP if they are intubated for more than 48 hours. The most common pathogens isolated from tracheal aspirates in mechanically ventilated children are enteric gram‐negative bacteria, P. aeruginosa, and S. aureus.45, 46 Few studies have precisely delineated the pathogenesis of VAP in the pediatric ICU population.
Overall, the causes of VAP vary by hospital, patient population, and ICU type. Therefore, it is essential that ICU clinicians remain knowledgeable about their local surveillance data.21 Awareness of VAP microbiology is essential for optimizing initial antibiotic therapy and improving outcomes.
Early Versus Late VAP
Distinguishing between early and late VAP is important for initial antibiotic selection because the etiologic pathogens vary between these 2 periods.4749 Early VAP (days 14 of hospitalization) usually involves antibiotic‐sensitive community‐acquired bacteria and carries a better prognosis. In contrast, late VAP (5 days after hospital admission) is more likely to be caused by antibiotic‐resistant nosocomial bacteria that lead to increased morbidity and mortality. All patients who have been hospitalized or have received antibiotics during the prior 90 days should be treated as having late VAP because they are at much higher risk for colonization and infection with antibiotic‐resistant bacteria.47 Of note, 2 recent studies suggest that pathogens in the early and late periods are becoming similar at some institutions.50, 51 Overall, the distinction between early and late VAP is important because it affects the likelihood that a patient has antibiotic‐resistant bacteria. If antibiotic‐resistant pathogens are suspected, initial therapy should include empiric triple antibiotics until culture data are available.
Culturing Approaches
Because clinical criteria alone are rarely able to accurately diagnose VAP,52, 53 clinicians should also obtain a respiratory specimen for microbiologic culture. Despite the convenience of blood cultures, their sensitivity for diagnosing VAP is poor, and they rarely make the diagnosis alone.54 Two methods are available for culturing the lungsan invasive approach (eg, bronchoscopy with bronchoalveolar lavage) and a noninvasive approach (eg, tracheal aspirate).
Some investigators believe that adult patients with suspected VAP should always undergo an invasive sampling of lower‐respiratory‐tract secretions.55 Proponents of the invasive approach cite the frequency with which potential pathogens colonize the trachea of ICU patients and create spurious results on tracheal aspirates.22 In addition, several studies have shown that clinicians are more likely to narrow the spectrum of antibiotics after obtaining an invasive diagnostic sample.56 In other words, the invasive approach has been associated with better antimicrobial stewardship.
Other investigators believe that a noninvasive approach is equally safe and effective for diagnosing VAP.57 This clinical approach involves culturing a tracheal aspirate and using a pneumonia prediction score such as the clinical pulmonary infection score (CPIS; Table 3). The CPIS assigns 012 points based on 6 clinical criteria: fever, leukocyte count, oxygenation, quantity and purulence of secretions, type of radiographic abnormality, and results of sputum gram stain and culture.58 As developed, a CPIS > 6 has a sensitivity of 93% and a specificity of 100% for diagnosing VAP.58 However, the CPIS requires that nurses record sputum volume and that the laboratory stains the specimen. When the CPIS has been modified based on the unavailability of such resources, the results have been less impressive.5961 Despite studies showing that a noninvasive clinical approach can achieve adequate initial antibiotic coverage and reduce overuse of broad‐spectrum agents,62, 63 clinicians who use the CPIS must understand its inherent limitations.
Criterion | Range | Score |
---|---|---|
| ||
Temperature (C) | 36.138.4 | 0 |
38.538.9 | 1 | |
39 or 36 | 2 | |
Blood leukocytes (/mm3) | 4000 and 11,000 | 0 |
<4000 or >11,000 | 1 | |
+ band forms 500 | 2 | |
Oxygenation: PaO2/FiO2 (mmHg) | >240 or ARDS | 0 |
240 and no evidence of ARDS | 2 | |
Chest radiograph | No infiltrate | 0 |
Diffuse (or patchy) infiltrate | 1 | |
Localized infiltrate | 2 | |
Tracheal secretions | Absence of tracheal secretions | 0 |
Nonpurulent tracheal secretions | 1 | |
Purulent tracheal secretions | 2 | |
Culture of tracheal aspirate | Pathogenic bacteria culture: no growth or light growth | 0 |
Pathogenic bacteria culture: moderate/heavy growth | 1 | |
Same pathogenic bacteria seen on gram stain (add 1 point) | 2 |
A meta‐analysis56 comparing the utility of an invasive versus a noninvasive culturing approach identified 4 randomized trials examining this issue.6669 Overall, an invasive approach did not alter mortality, but patients undergoing bronchoscopy were much more likely to have their antibiotic regimens modified by clinicians. This suggests that the invasive approach may allow more directed use of antibiotics. Recently, the Canadian Critical Care Trials Group conducted a multicenter randomized trial looking at this issue.11 There was no difference between the 2 approaches in mortality, number of ventilator days, and antibiotic usage. However, all patients in this study were immediately treated with empiric broad‐spectrum antibiotics until culture results were available, and the investigators did not have a protocol for stopping antibiotics after culture data were available.
In summary, both invasive and noninvasive culturing approaches are considered acceptable options for diagnosing VAP. Readers interested in learning more about this topic should read the worthwhile Expert Discussion70 by Chastre and colleagues55 at the end of this article. In general, we recommend that ICU clinicians use a combination of clinical suspicion (based on the CPIS or other objective data) and cultures ideally obtained prior to antibiotics. Regardless of the chosen culturing approach, clinicians must recognize that 1 of the most important determinants of patient outcome is prompt administration of adequate initial antibiotics.7175
Initial Antibiotic Administration
Delaying initial antibiotics in VAP increases the risk of death.7175 If a patient receives ineffective initial therapy, a later switch to appropriate therapy does not eliminate the increased mortality risk. Therefore, a comprehensive approach to VAP diagnosis requires consideration of initial empiric antibiotic administration.
Whenever possible, clinicians should obtain a lower respiratory tract sample for microscopy and culture before administering antibiotics because performing cultures after antibiotics have been recently started will lead to a higher rate of false‐negative results.76 Unless the patient has no signs of sepsis and microscopy is completely negative, clinicians should then immediately start empiric broad‐spectrum antibiotics.57 Once the culture sensitivities are known, therapy can be deescalated to a narrower spectrum.77 Recent studies suggest that shorter durations of therapy (8 days) are as effective as longer courses and are associated with lower colonization rates by antibiotic‐resistant bacteria.62, 78
Initial broad‐spectrum antibiotics should be chosen based on local bacteriology and resistance patterns. Clinicians must remain aware of the most common bacterial pathogens in their local community, hospital, and ICU. This is essential for both ensuring adequate initial antibiotic coverage and reducing overall antibiotic days.65 Unrestrained use of broad‐spectrum antibiotics increases the risk of resistant pathogens. Clinicians must continually deescalate therapy and use narrow‐spectrum drugs as pathogens are identified.79
Prevention of VAP
In 2005, the American Thoracic Society published guidelines for the management of adults with VAP.5 These guidelines included a discussion of modifiable risk factors for preventing VAP and used an evidence‐based grading system to rank the various recommendations. The highest evidence (level 1) comes from randomized clinical trials, moderate evidence (level 2) comes from nonrandomized studies, and the lowest evidence (level 3) comes from case studies or expert opinion. Others have also published their own guidelines and recommendations for preventing VAP.8082 Table 4 shows the key VAP preventive strategies.
Strategy | Level of evidence | References |
---|---|---|
| ||
General infection control measures (hand hygiene, staff education, isolate MDR pathogens, etc.) | 1 | 2,83,84 |
ICU infection surveillance | 2 | 2,8385 |
Avoid reintubation if possible, but promptly reintubate if a patients inexorably fails extubation | 1 | 2,83,86,87 |
Use NPPV when appropriate (in selected patients) | 1 | 88 |
Use oral route for endotracheal and gastric tubes (vs. nasal route) | 2 | 89 |
Continuous suctioning of subglottic secretions (to avoid pooling on cuff and leakage into LRT) | 1 | 9092 |
Maintain endotracheal cuff pressure > 20 cm H2O (to prevent secretion leakage into LRT) | 2 | 93 |
Avoid unnecessary ventilator circuit changes | 1 | 94 |
Routinely empty condensate in ventilator circuit | 2 | 95 |
Maintain adequate nursing and therapist staffing | 2 | 9698 |
Implement ventilator weaning and sedation protocols | 2 | 99101 |
Semierect patient positioning (vs. supine) | 1 | 102 |
Avoid aspiration when using enteral nutrition | 1 | 103,104 |
Topical oral antisepsis (eg, chlorhexidine) | 1 | 105108 |
Control blood sugar with insulin | 1 | 109 |
Use heat‐moisture exchanger (vs. conventional humidifier) to reduce tubing condensate | 1 | 95 |
Avoid unnecessary red blood cell transfusions | 1 | 110 |
Use of sucralfate for GI prophylaxis | 1 | 111,112 |
Influenza vaccination for health care workers | 2 | 2 |
Some strategies are not recommended for VAP prevention in general ICU patients. Selective decontamination of the digestive tract (ie, prophylactic oral antibiotics) has been shown to reduce respiratory infections in ICU patients,113 but its overall role remains controversial because of concerns it may increase the incidence of multi‐drug‐resistant pathogens.114 Similarly, prophylactic intravenous antibiotics administered at the time of intubation can reduce VAP in certain patient populations,115 but this strategy is also associated with an increased risk of antibiotic‐resistant nosocomial infections.116 Using kinetic beds and scheduled chest physiotherapy to reduce VAP is based on the premise that critically ill patients often develop atelectasis and cannot effectively clear their secretions. Unfortunately, neither of these modalities has been shown to consistently reduce VAP in medical ICU patients.117119
Algorithms for Diagnosis and Treatment of VAP
We present algorithms for diagnosing VAP in 4 ICU populations: infant (1 year old), pediatric (1‐12 years old), immunocompromised, and adult ICU patients (Figs. 14). Because clinicians face considerable uncertainty when diagnosing VAP, we sought to develop practical algorithms for use in daily ICU practice. Although we provided the algorithms to collaborative participants as a tool for improving care, we never mandated use, and we did not monitor levels of adherence.
Five teaching cases are presented in the Appendix. We demonstrate how to utilize the diagnostic algorithms in these clinical scenarios and offer tips for clinicians wishing to employ these tools in their daily practice. These cases are useful for educating residents, nurses, and hospitalists.
Overall, our intent is that the combined use of these VAP algorithms facilitate a streamlined diagnostic approach and minimize delays in initial antibiotic administration. A primary focus of any VAP guideline should be early and appropriate antibiotics in adequate doses, with deescalation of therapy as culture data permit.5 In general, the greatest risk to a patient with VAP is delaying initial adequate antibiotic coverage, and for this reason, antibiotics must always be administered promptly. However, if culture data are negative, the clinician should consider withdrawing unnecessary antibiotics. For example, the absence of gram‐positive organisms on BAL after 72 hours would strongly suggest that MRSA is not playing a role and that vancomycin can be safely stopped. We agree with Neiderman that the decision point is not whether to start antibiotics, but whether to continue them at day 23.57
DISCUSSION
In this article, we introduce algorithms for diagnosing and managing VAP in infant, pediatric, immunocompromised, and adult ICU patients. We developed 4 algorithms because the hospitals in our system care for a wide range of patients. Our definitions for VAP were based on criteria outlined by the CDC because these rigorously developed criteria have been widely disseminated as components of the Institute for Healthcare Improvement's ventilator bundle.120 Clinicians should be able to easily incorporate these practical algorithms into their current practice.
The algorithms were developed during a collaborative across a large national health care system. We undertook this task because many clinicians were uncertain how to integrate the enormous volume of VAP literature into their daily practice, and we suspected there was large variation in practice in our ICUs. Recent studies from other health care systems provided empiric evidence to support this notion.12, 13
We offer these algorithms as practical tools to assist ICU clinicians and not as proscriptive mandates. We realize that the algorithms may need modification based on a hospital's unique bacteriology and patient populations. We also anticipate that the algorithms will adapt to future changes in VAP epidemiology, preventive strategies, emerging pathogens, and new antibiotics.
Numerous resources are available to learn more about VAP management. An excellent guideline from the Infectious Diseases Society of America and the American Thoracic Society discusses VAP issues in detail,5 although this guideline only focuses on immunocompetent adult patients. The journal Respiratory Care organized an international conference with numerous VAP experts in 2005 and subsequently devoted an entire issue to this topic.81 The Canadian Critical Care Trials Group and the Canadian Critical Care Society conducted systematic reviews and developed separate guidelines for the prevention, diagnosis, and treatment of VAP.80, 121
In summary, we present diagnostic and treatment algorithms for VAP. Our intent is that these algorithms may provide evidence‐based practical guidance to clinicians seeking a standardized approach to diagnosing and managing this challenging problem.
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- Cost‐effectiveness issues in ventilator‐associated pneumonia.Respir Care.2005;50:956–963; discussion 963–964. .
- Diagnosis and treatment of ventilator‐associated pneumonia: fiberoptic bronchoscopy with bronchoalveolar lavage is essential.Semin Respir Crit Care Med.2006;27:34–44. .
- A randomized trial of diagnostic techniques for ventilator‐associated pneumonia.N Engl J Med.2006;355:2619–2630. , , , .
- Clinical characteristics and treatment patterns among patients with ventilator‐associated pneumonia.Chest.2006;129:1210–1218. , , , et al.
- Prevention and diagnosis of ventilator‐associated pneumonia: a survey on current practices in Southern Spanish ICUs.Chest.2005;128:1667–1673. , , , .
- Why don't physicians follow clinical practice guidelines? A framework for improvement.JAMA.1999;282:1458–1465. , , , et al.
- Why do physicians not follow evidence‐based guidelines for preventing ventilator‐associated pneumonia?: a survey based on the opinions of an international panel of intensivists.Chest.2002;122:656–661. , , , , , .
- Invitation to a dialogue between researchers and clinicians about evidence‐based behavioral medicine.Ann Behav Med.2005;30:125–137. , , , et al.
- Connections between quality measurement and improvement.Med Care.2003;41:I30–I38. , , .
- Practice guidelines developed by specialty societies: the need for a critical appraisal.Lancet.2000;355:103–106. , , , , .
- Agency for Healthcare Research and Quality (AHRQ). Partnerships in Implementing Patient Safety. Online at http://www.ahrq.gov/qual/pips.htm. Accessed March 1,2007.
- The utility of open lung biopsy in patients requiring mechanical ventilation.Chest.1999;115:811–817. , .
- The microbiology of ventilator‐associated pneumonia.Respir Care.2005;50:742–763; discussion 763–765. .
- Ventilator‐associated pneumonia.Am J Respir Crit Care Med.2002;165:867–903. , .
- Overview of nosocomial infections caused by gram‐negative bacilli.Clin Infect Dis.2005;41:848–854. , .
- Increasing prevalence of antimicrobial resistance in intensive care units.Crit Care Med.2001;29:N64–N68. .
- Incidence and outcome of polymicrobial ventilator‐associated pneumonia.Chest.2002;121:1618–1623. , , , et al.
- Nosocomial transmission of influenza.Occup Med (Lond).2002;52:249–253. , , .
- Nosocomial influenza at a Canadian pediatric hospital from 1995 to 1999: opportunities for prevention.Infect Control Hosp Epidemiol.2002;23:627–629. , .
- Nosocomial influenza infection as a cause of intercurrent fevers in infants.Pediatrics.1975;55:673–677. ,
- Nosocomial influenza infection.Lancet.2000;355:1187. , .
- Nosocomial influenza B virus infection in the elderly.Ann Intern Med.1982;96:153–158. , , .
- Influenza vaccination of healthcare workers and vaccine allocation for healthcare workers during vaccine shortages.Infect Control Hosp Epidemiol.2005;26:882–890. , , , , , .
- Herpes simplex virus in the respiratory tract of critical care patients: a prospective study.Lancet.2003;362:1536–1541. , , , et al.
- Significance of the isolation of Candida species from respiratory samples in critically ill, non‐neutropenic patients. An immediate postmortem histologic study.Am J Respir Crit Care Med.1997;156:583–590. , , , et al.
- The role of Candida sp isolated from bronchoscopic samples in nonneutropenic patients.Chest.1998;114:146– 149. , , , , , .
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Physician Assistant/Hospitalist Service
Midlevel providers (physician assistants and nurse practitioners) have long been employed by academic medical centers, predominantly on surgical services, or on medical subspecialty services, where they have typically had a limited scope of practice, focused in a narrowly defined area or set of procedures.17 In contrast, there are relatively few reports of experiences deploying midlevel providers to replace house staff on inpatient general medicine services in academic centers,810 and few studies of the effect of midlevel providers on quality and efficiency of care in the academic setting. Despite this, reductions in house officer duty hours as mandated by the Accreditation Council on Graduate Medical Education (ACGME)11 have resulted in academic centers increasingly using midlevel providers to decrease house staff workload on inpatient services.12, 13 In general, midlevel practitioners on general medicine services have been deployed to: (1) care for a population of patients separate from and in parallel with house staff; this population may be narrowly defined (eg, patients with chest pain) or not; (2) assist with the management of patients cared for by house staff by performing certain tasks (eg, scheduling appointments, discharging patients). Even as midlevel providers become more prevalent on academic general medicine services, the best model of care incorporating them into clinical care remains unclear, and few studies have rigorously examined the care provided on services that use them.
We developed an inpatient general medicine service within a large academic medical center staffed by physician assistants and hospitalists to help our residency program meet ACGME duty hour requirements. We hypothesized that by creating a service that is geographically localized and supervised by full‐time hospitalists, by instituting multidisciplinary rounds, and by investing in the professional development of highly‐skilled physician assistants, we could provide care for medically complex, acutely ill general medicine inpatients with similar quality and efficiency as compared to house staff teams. We report our experience during the first year of implementing the service, and compare quality and efficiency of care on this service with that of our traditional house staff services. We also evaluate the effects of this service on patient satisfaction and self‐reported house staff workload.
PATIENTS AND METHODS
Study Setting
The study was conducted in a 747‐bed urban, academic medical center in the northeastern United States. The hospital's human research committee reviewed and approved the study design. The hospital has accredited residency and fellowship programs in all major specialties. Prior to July 2005, physician assistants were employed only on surgical and medical subspecialty services (ie, bone marrow transplant, interventional cardiology); none were employed on the inpatient general medicine service. There were approximately 44,000 inpatient admissions during the year of the study, with approximately 6500 of these to the general medicine service.
Description of the General Medicine Service
The General Medicine Service consisted of 8 traditional house staff teams, with 1 attending, 1 junior or senior resident, 2 interns, and 1 or 2 medical students. These teams admitted patients on a rotating basis every fourth day. On 4 of these teams, the attending was a hospitalist, with clinical responsibility for the majority of the patients admitted to the team. On the remaining 4 teams, the teaching attending was a primary care physician or medical subspecialist, responsible for the direct care of a small number of the team's patients, with the remainder cared for by private primary care physicians or subspecialists.
Description of the Physician Assistant/Hospitalist Service
The Physician Assistant/Clinician Educator (PACE) service opened in July 2005, and consisted of 15 beds localized to 2 adjacent inpatient pods, staffed by a single cadre of nurses and medically staffed by 1 hospitalist and 2 physician assistants from 7:00 AM to 7:00 PM on weekdays and by 1 hospitalist, 1 physician assistant, and 1 moonlighter (usually a senior medical resident or fellow) from 7:00 AM to 7:00 PM on weekends. A moonlighter, typically a senior resident or medical subspecialty fellow, admitted patients and covered nights on the service from 7:00 PM to 7:00 AM 7 days a week. The daily census goal for the service was 15 patients, limited by the number of available beds on the 2 pods, and the service accepted admissions 24 hours per day, 7 days per week, whenever beds were available. Daily morning rounds occurred at 8:00 AM and included the hospitalist, physician assistants, nurses, a care coordinator, and a pharmacist. The PACE service did not have triage guidelines related to diagnosis, complexity, or acuity, but only accepted patients via the emergency department or via a primary care physician's office, and did not accept patients transferred from outside hospitals or from the intensive care units.
Physician Assistants
All of the physician assistants on the PACE service had prior inpatient medicine experience, ranging from 6 months to 5 years. The physician assistants worked in 3‐day to 6‐day blocks of 12‐hour shifts. Their clinical responsibilities were similar to those of interns at the study hospital, and included taking histories and performing physical examinations, writing notes and orders, reviewing and assimilating data, creating and updating patient signouts, completing discharge summaries, consulting other services as needed, and communicating with nurses and family members.
Many physician assistants also had nonclinical responsibilities, taking on physician‐mentored roles in education, quality improvement, and administration. They were involved in several initiatives: (1) developing a physician assistant curriculum in hospital medicine, (2) presenting at hospital‐wide physician assistant grand rounds, (3) surveying and tracking patient and family satisfaction on the service, (4) reviewing all 72‐hour hospital readmissions, intensive care unit transfers, and deaths on the service, and (5) maintaining the service's compliance with state regulations regarding physician assistant scope of practice and prescribing.
Hospitalists
The 3 hospitalists on the PACE service worked in 7‐day blocks of 12‐hour shifts (7:00 AM to 7:00 PM). They directly supervised the physician assistants and had no competing responsibilities. The hospitalists were all recent graduates of the study hospital's internal medicine residency, with no prior clinical experience beyond residency. All were planning to work on the service for 1 to 2 years before beginning a subspecialty fellowship. In addition to supervising the clinical work of the physician assistants, the hospitalists were responsible for teaching the physician assistants on rounds and in weekly didactic sessions, guided by a curriculum in hospital medicine that focused on the most common general medicine diagnoses seen on the PACE service. The medical director of the PACE service periodically reviewed each physician assistant's clinical experience, skills and knowledge base, and held semiannual feedback sessions.
Study Patients
All general medicine patients admitted to the PACE service from July 1, 2005 to June 30, 2006 comprised the study population. The comparison group consisted of general medicine patients admitted to the 8 house staff general medicine teams; patients transferred from an intensive care unit (ICU) or another facility were excluded in order to match the admission criteria for the PACE service and improve comparability between the 2 study arms.
Data Collection and Study Outcomes
We obtained all patient data from the hospital's administrative databases. We identified patients assigned to the PACE service or to the comparison group based on the admitting service, team, and attending. We obtained patient demographics, insurance, admission source and discharge destination, admission and discharge times, dates, diagnoses, and diagnosis‐related groups (DRGs), as well as dates and times of transfers to other services, including to the intensive care unit. We also obtained the Medicare case‐mix index (CMI, based on DRG weight), and calculated a Charlson score based on billing diagnoses coded in the year prior to the index admission.14 Outcomes included length of stay (LOS) to the nearest hour, in‐hospital mortality, transfers to the intensive care unit, readmissions to the study hospital within 72 hours, 14 days, and 30 days, and total costs as derived from the hospital's cost accounting system (Transition Systems Inc., Boston, MA). Other outcomes included patient satisfaction as measured by responses to the Press‐Ganey survey routinely administered to a randomly selected 70% of recently discharged patients and effect on self‐reported resident work hours.
Statistical Analysis
Patient demographics, clinical characteristics, and study outcomes are presented using proportions, means with standard deviations, and medians with inter‐quartile ranges as appropriate. Unadjusted differences in outcomes between the two services were calculated using univariable regression techniques with service as the independent variable and each outcome as the dependent variable. We used logistic regression for dichotomous outcomes (readmissions, ICU transfers, and inpatient mortality), and linear regression for log‐transformed LOS and log‐transformed total costs of care. To adjust each outcome for potential confounders, we then built multivariable regression models. Each potential confounder was entered into the model one at a time as the independent variable. All variables found to be significant predictors of the outcome at the P < 0.10 level were then retained in the final model along with service as the predictor of interest. We used general estimating equations in all multivariable models to adjust for clustering of patients by attending physician. For logistic regression models, the effect size is presented as an odds ratio (OR); for log‐transformed linear regression models, the effect size is presented as the percent difference between groups. We also performed 2 subgroup analyses, limited to (1) the patients with the 10 most common discharge DRGs, and (2) patients admitted between the hours of 7:00 AM and 7:00 PM to remove the effects of moonlighters performing the initial admission. Except as noted above, 2‐sided P values < 0.05 were considered significant. SAS 9.1 (SAS Institute, Cary, NC) was used for all analyses.
RESULTS
Patient Demographics
Table 1 shows patient demographics and clinical characteristics of the PACE service and the comparison group. Patients in the comparison group were slightly older and tended to have slightly higher CMI and Charlson scores. Patients on the PACE service were more likely to be admitted at night (10:00 PM to 7:00 AM; 43.8% versus 30.3%; P < 0.0001). There were no significant differences in sex, race, insurance, or percentage of patients discharged to home. The 10 most common DRGs in the comparison group accounted for 37.0% of discharges, and these same DRGs accounted for 37.5% of discharges on the PACE service (Table 2).
Characteristic | PACE Service (n = 992) | House Staff Services (n = 4,202) | P value |
---|---|---|---|
| |||
Age (years) | |||
1844 | 19.1 | 18.2 | |
4564 | 35.5 | 31.9 | 0.04 |
65+ | 45.5 | 49.9 | |
Sex (% female) | 57.7 | 60.0 | NS |
Race/ethnicity | |||
White | 57.3 | 59.3 | |
Black | 24.0 | 23.5 | NS |
Hispanic | 14.1 | 13.3 | |
Other | 4.6 | 3.9 | |
Insurance | |||
Medicare | 41.9 | 43.8 | |
Commercial | 34.9 | 35.9 | |
Medicaid | 14.4 | 11.7 | NS |
Free care | 4.5 | 3.9 | |
Self pay | 1.1 | 0.8 | |
Median income by zip code of residence, USD (IQR) | 45,517 (32,49362,932) | 45,517 (35,88963,275) | NS |
Case‐mix index, median (IQR) | 1.1 (0.81.5) | 1.2 (0.91.8) | 0.001 |
Charlson score | |||
0 | 27.2 | 24.9 | |
1 | 22.6 | 21.1 | 0.02 |
2 | 16.2 | 16.5 | |
3+ | 34.0 | 37.6 | |
Admissions between 10:00 PM and 7:00 AM | 43.8 | 30.3 | <0.0001 |
Discharged to home | 81.1 | 80.5 | NS |
Diagnosis‐Related Group at Discharge | PACE Service (n = 992)* | House Staff Services (n = 4,202)* |
---|---|---|
| ||
Chest pain | 5.4 | 6.4 |
Esophagitis, gastroenteritis, and miscellaneous digestive disorders | 4.5 | 4.4 |
Heart failure and shock | 3.4 | 4.6 |
Simple pneumonia and pleurisy | 2.7 | 4.4 |
Kidney and urinary tract infections | 4.7 | 3.2 |
Chronic obstructive pulmonary disease | 4.0 | 3.3 |
Renal failure | 2.7 | 3.5 |
Gastrointestinal hemorrhage | 3.7 | 2.7 |
Nutritional and miscellaneous metabolic disorders | 3.3 | 2.4 |
Disorders of the pancreas except malignancy | 3.1 | 2.1 |
Cumulative percent | 37.5 | 37.0 |
Efficiency and Quality of Care
Table 3 compares the performance of the PACE service and the comparison group on several efficiency and quality measures. Unadjusted LOS was not significantly different, and adjusted LOS was slightly but not statistically significantly higher on the study service (adjusted LOS 5.0% higher; 95% confidence interval [CI], 0.4% to +10%). Unadjusted and adjusted total costs of care were marginally lower on the study service (adjusted total cost of care 3.9% lower; 95% CI, 7.5% to 0.3%).
PACE Service | House Staff Services | Unadjusted % Difference (95%CI) | Adjusted % Difference (95%CI)* | |
---|---|---|---|---|
PACE Service | House Staff Services | Unadjusted OR (95% CI) | Adjusted OR (95% CI) | |
| ||||
Efficiency measure | ||||
Length of stay, days, median (IQR) | 2.6 (1.6, 4.4) | 2.6 (1.4, 4.6) | +0.1% (5.6% to +6.1%) | +5.0% (0.4% to +10.0%) |
Total costs, USD, median (IQR) | 4,536 (2,848, 7,201) | 4,749 (3,046, 8,161) | 9.1% (14.0% to 3.8%) | 3.9% (7.5% to 0.3%)‖ |
Quality measure | ||||
72‐hour readmissions/100 discharges | 0.8 | 1.3 | 0.6 (0.31.3) | 0.7 (0.21.8) |
14‐day readmissions/100 discharges | 5.4 | 5.4 | 1.0 (0.71.4) | 1.1 (0.81.4) |
30‐day readmissions/100 discharges | 8.0 | 8.1 | 1.0 (0.81.3) | 1.1 (0.91.3) |
ICU transfers/100 discharges | 2.0 | 2.3 | 0.9 (0.51.4) | 1.4 (0.82.4)# |
Inpatient mortality/100 discharges | 0.7 | 1.2 | 0.6 (0.31.3) | 0.8 (0.31.8)** |
We found no differences between the PACE service and comparison group in unadjusted rates of hospital readmissions within 72 hours, 14 days, and 30 days, transfer to the intensive care units, or inpatient mortality (Table 3). The associated ORs for each outcome were similar after adjusting for patient demographics and clinical characteristics including severity of illness, as well as for clustering by attending physician.
Subgroup Analyses
When the analysis was limited to the subset of patients with the 10 most common discharge DRGs, the difference in adjusted total cost of care was similar but lost statistical significance (4.0% lower on PACE service; 95% CI, 11.0% to +3.3%). In this subgroup, LOS, readmission rates, and ICU transfer rates were not different. ORs for mortality could not be calculated because there were no deaths in this subgroup on the PACE service (data not shown). When analysis was limited to daytime admissions (to remove any potential effect of admitting by a moonlighter), the difference in total cost of care was attenuated and lost statistical significance (0.2% lower on PACE service; 95%CI, 5.9% to +5.5%). No differences were seen in LOS, mortality, and ICU transfers (data not shown). However, 14‐day readmissions (but not 72‐hour or 30‐day readmissions) were lower on the PACE service (OR, 0.49; 95% CI, 0.25‐0.93).
Patient Satisfaction
Patients were similarly satisfied with their care on the PACE service and on the house staff services. In specific areas and globally, percentages of patients satisfied with their physicians and with the discharge process were not different, as measured by the Press‐Ganey survey (Press‐Ganey Associates, South Bend, IN; Figures 1 and 2). The survey distinguishes between attendings and residents, but not physician assistants; therefore, Figure 1 only includes responses to the attending questions. Given the sampling procedure of the Press‐Ganey survey, exact response rates cannot be calculated, but Press‐Ganey reports a response rate of about 40% for the English survey and about 20% for the Spanish survey.


Resident Duty Hours
Comparing the same month 1 year prior to implementation of the PACE service, mean self‐reported resident duty hours on the general medicine service were unchanged; however, self‐reported data were incomplete, and multiple changes took place in the residency program during the study period. For example, implementation of the PACE service allowed for the dissolution of one full house staff general medicine team and redistribution of these house staff to night float positions and an expanded medical intensive care unit.
Costs of Implementation
The costs associated with implementing the PACE service included physician and physician assistant salaries (2.5 full‐time physicians, 5 full‐time physician assistants, plus fringe) and night coverage by resident and fellow moonlighters (without fringe, and estimated at 50% effort given other moonlighter coverage responsibilities on subspecialty services). We estimated these costs at $257.50/patient‐day ($115/patient‐day for attending physician compensation, $110/patient‐day for physician assistant compensation, and $32.50/patient‐day for moonlighting coverage).
DISCUSSION
As academic centers struggle with developing a workforce to provide patient care no longer provided by residents, questions about the ideal structure of nonhouse staff inpatient services abound. Although solutions to this problem will be determined to some extent by local factors such as institutional culture and resources, some lessons learned in developing such services will be more widely applicable. We found that by implementing a geographically localized, physician assistant‐staffed hospitalist service, we were able to provide care of similar quality and efficiency to that of traditional house staff services, despite inexperienced hospitalists staffing the service and a medical residency program commonly recognized as one of the best in the country. Adjusted total costs were slightly lower on the PACE service, but this difference was small and of borderline statistical significance. Likewise, no significant differences were seen in any of several quality measures or in patient satisfaction.
Our findings add to the available evidence supporting the use of physician assistants on academic general medicine services, and are germane to academic centers facing reductions in house staff availability and seeking alternative models of care for inpatients. Several specific characteristics of the PACE service and the implications of these should be considered:
The service accepted all patients, regardless of diagnosis, acuity, or complexity of illness. This was unlike many previously described nonhouse staff services which were more limited in scope, and allowed more flexibility with patient flow. However, in the end, patients on the PACE service did have a modestly lower case mix index and Charlson score, suggesting that, despite a lack of triage guidelines, there was some bias in the triage of admissions, possibly due to a perception that physician assistants should take care of lower complexity patients. If it is desirable to have a similar distribution of higher complexity patients across house staff and nonhouse staff services, extra efforts may be necessary to overcome this perception.
The service was geographically regionalized. Geographic regionalization offered many important advantages, especially with regards to communication among staff, nursing, and consultants, and allowed for multidisciplinary rounds. However, it is possible that the modest, but not statistically significant, trend toward an increased LOS seen on the PACE service might be a reflection of geographic admitting (less incentive to discharge since discharging a patient means taking a new admission).
The education and professional development of the physician assistants was a priority. Physician assistants had considerable autonomy and responsibility, and rather than being assigned only lower level administrative tasks, performed all aspects of patient care. They also received regular teaching from the hospitalists, attended house staff teaching conferences, and developed nonclinical roles in education and quality improvement. The higher standards expected of the physician assistants were quite possibly a factor in the quality of care delivered, and almost certainly contributed to physician assistant satisfaction and retention.
Our findings contrast with those of Myers et al.,9 who found that a nonteaching service staffed by hospitalists and nurse practitioners had a significantly lower median LOS and hospital charges compared to similar patients on resident‐based services. However, unlike ours, their service cared for a select patient population, and only accepted patients with chest pain at low risk for acute coronary syndrome. Van Rhee et al.10 found that physician assistants on a general medicine service used fewer resources for patients with pneumonia, stroke, and congestive heart failure than resident physicians, and did not exceed the resources used by residents in other diagnoses. The authors did not find a difference in LOS, but did find a significantly higher mortality among patients with pneumonia cared for by physician assistants.
Several limitations should be noted. First, the study was a retrospective analysis of administrative data rather than a randomized trial, and although we employed a standard approach to adjust for a wide range of patient characteristics including severity of illness, there may have been undetected differences in the patient populations studied that may have confounded our results. Second, resident moonlighters admitted patients to the PACE service and, at other times, to the house staff services, and this may have diluted any differences between the groups. However, when we limited our analysis to the subgroup of patients admitted during the day, similar results were obtained, with the exception that the PACE service had a lower rate of 14‐day readmissions, an unexpected finding deserving of further study. Third, the study was conducted in a single academic institution and our findings may not be generalizable to others with different needs and resources; indeed, the costs associated with implementing such a service may be prohibitive for some institutions. Fourth, because of simultaneous changes that were taking place in our residency program, we are unable to accurately assess the impact of the PACE service on resident duty hours. However, resident duty hours did not increase over this time period on the general medicine service, and implementation of the service allowed for redistribution of house staff to other services and positions. Fifth, patient satisfaction data were obtained from responses to the mailed Press‐Ganey survey, to which there is a relatively low response rate. Also, we did not survey providers regarding their satisfaction with the service during the study period. Sixth, the study had limited power to detect clinically important differences in mortality and ICU transfers. Finally, this study is unable to compare this particular model of incorporating midlevel providers into general medical services with other models, only with traditional house staff services.
Future research should focus on determining the most effective and efficient ways to incorporate midlevel providers on academic general medicine services. One important question from the standpoint of house staff training is whether such services should be separate but equal, or should house staff gain experience during residency working with midlevel providers, since they are likely to encounter them in the future whether they stay in academics or not. Different models of care will likely have large implications for the quality and efficiency of patient care, house staff education and satisfaction, and physician assistant job satisfaction and turnover.
In summary, our study demonstrates that a geographically regionalized, multidisciplinary service staffed by hospitalists and physician assistants can be a safe alternative to house staff‐based services for the care of general medicine inpatients in an academic medical center.
- The physician's assistant as resident on surgical service. An example of creative problem solving in surgical manpower.Arch Surg.1980;115:310–314. , , , , , .
- Coronary arteriography performed by a physician assistant.Am J Cardiol.1987;60:784–787. , , , .
- The specialized physician assistant: an alternative to the clinical cardiology trainee.Am J Cardiol.1987;60:901–902. .
- One hospital's successful 20‐year experience with physician assistants in graduate medical education.Acad Med.1999;74:641–645. , , .
- Physicians assistants in cardiothoracic surgery: a 30‐year experience in a university center.Ann Thorac Surg.2006;81:195–199; discussion 199–200. , .
- Comparative review of use of physician assistants in a level I trauma center.Am Surg.2004;70:272–279. , , .
- Integrating midlevel practitioners into a teaching service.Am J Surg.2006;192:119–124. , , , , .
- Acute care nurse practitioners: creating and implementing a model of care for an inpatient general medical service.Am J Crit Care.2002;11:448–458. , .
- Improving resource utilization in a teaching hospital: development of a nonteaching service for chest pain admissions.Acad Med.2006;81:432–435. , , , , .
- Resource use by physician assistant services versus teaching services.JAAPA.2002;15:33–38. , , .
- for the ACGME Work Group on Resident Duty Hours, Accreditation Council for Graduate Medical Education.New requirements for resident duty hours.JAMA.2002;288:1112–1114. , , ,
- The substitution of physician assistants and nurse practitioners for physician residents in teaching hospitals.Health Aff.1995;14:181–191. , , .
- Challenges of the 80‐hour resident work rules: collaboration between surgeons and nonphysician practitioners.Surg Clin North Am.2004;84:1573–1586. , , , , .
- Adapting a clinical comorbidity index for use with ICD‐9‐CM administrative databases.J Clin Epidemiol.1992;45:613–619. , , .
Midlevel providers (physician assistants and nurse practitioners) have long been employed by academic medical centers, predominantly on surgical services, or on medical subspecialty services, where they have typically had a limited scope of practice, focused in a narrowly defined area or set of procedures.17 In contrast, there are relatively few reports of experiences deploying midlevel providers to replace house staff on inpatient general medicine services in academic centers,810 and few studies of the effect of midlevel providers on quality and efficiency of care in the academic setting. Despite this, reductions in house officer duty hours as mandated by the Accreditation Council on Graduate Medical Education (ACGME)11 have resulted in academic centers increasingly using midlevel providers to decrease house staff workload on inpatient services.12, 13 In general, midlevel practitioners on general medicine services have been deployed to: (1) care for a population of patients separate from and in parallel with house staff; this population may be narrowly defined (eg, patients with chest pain) or not; (2) assist with the management of patients cared for by house staff by performing certain tasks (eg, scheduling appointments, discharging patients). Even as midlevel providers become more prevalent on academic general medicine services, the best model of care incorporating them into clinical care remains unclear, and few studies have rigorously examined the care provided on services that use them.
We developed an inpatient general medicine service within a large academic medical center staffed by physician assistants and hospitalists to help our residency program meet ACGME duty hour requirements. We hypothesized that by creating a service that is geographically localized and supervised by full‐time hospitalists, by instituting multidisciplinary rounds, and by investing in the professional development of highly‐skilled physician assistants, we could provide care for medically complex, acutely ill general medicine inpatients with similar quality and efficiency as compared to house staff teams. We report our experience during the first year of implementing the service, and compare quality and efficiency of care on this service with that of our traditional house staff services. We also evaluate the effects of this service on patient satisfaction and self‐reported house staff workload.
PATIENTS AND METHODS
Study Setting
The study was conducted in a 747‐bed urban, academic medical center in the northeastern United States. The hospital's human research committee reviewed and approved the study design. The hospital has accredited residency and fellowship programs in all major specialties. Prior to July 2005, physician assistants were employed only on surgical and medical subspecialty services (ie, bone marrow transplant, interventional cardiology); none were employed on the inpatient general medicine service. There were approximately 44,000 inpatient admissions during the year of the study, with approximately 6500 of these to the general medicine service.
Description of the General Medicine Service
The General Medicine Service consisted of 8 traditional house staff teams, with 1 attending, 1 junior or senior resident, 2 interns, and 1 or 2 medical students. These teams admitted patients on a rotating basis every fourth day. On 4 of these teams, the attending was a hospitalist, with clinical responsibility for the majority of the patients admitted to the team. On the remaining 4 teams, the teaching attending was a primary care physician or medical subspecialist, responsible for the direct care of a small number of the team's patients, with the remainder cared for by private primary care physicians or subspecialists.
Description of the Physician Assistant/Hospitalist Service
The Physician Assistant/Clinician Educator (PACE) service opened in July 2005, and consisted of 15 beds localized to 2 adjacent inpatient pods, staffed by a single cadre of nurses and medically staffed by 1 hospitalist and 2 physician assistants from 7:00 AM to 7:00 PM on weekdays and by 1 hospitalist, 1 physician assistant, and 1 moonlighter (usually a senior medical resident or fellow) from 7:00 AM to 7:00 PM on weekends. A moonlighter, typically a senior resident or medical subspecialty fellow, admitted patients and covered nights on the service from 7:00 PM to 7:00 AM 7 days a week. The daily census goal for the service was 15 patients, limited by the number of available beds on the 2 pods, and the service accepted admissions 24 hours per day, 7 days per week, whenever beds were available. Daily morning rounds occurred at 8:00 AM and included the hospitalist, physician assistants, nurses, a care coordinator, and a pharmacist. The PACE service did not have triage guidelines related to diagnosis, complexity, or acuity, but only accepted patients via the emergency department or via a primary care physician's office, and did not accept patients transferred from outside hospitals or from the intensive care units.
Physician Assistants
All of the physician assistants on the PACE service had prior inpatient medicine experience, ranging from 6 months to 5 years. The physician assistants worked in 3‐day to 6‐day blocks of 12‐hour shifts. Their clinical responsibilities were similar to those of interns at the study hospital, and included taking histories and performing physical examinations, writing notes and orders, reviewing and assimilating data, creating and updating patient signouts, completing discharge summaries, consulting other services as needed, and communicating with nurses and family members.
Many physician assistants also had nonclinical responsibilities, taking on physician‐mentored roles in education, quality improvement, and administration. They were involved in several initiatives: (1) developing a physician assistant curriculum in hospital medicine, (2) presenting at hospital‐wide physician assistant grand rounds, (3) surveying and tracking patient and family satisfaction on the service, (4) reviewing all 72‐hour hospital readmissions, intensive care unit transfers, and deaths on the service, and (5) maintaining the service's compliance with state regulations regarding physician assistant scope of practice and prescribing.
Hospitalists
The 3 hospitalists on the PACE service worked in 7‐day blocks of 12‐hour shifts (7:00 AM to 7:00 PM). They directly supervised the physician assistants and had no competing responsibilities. The hospitalists were all recent graduates of the study hospital's internal medicine residency, with no prior clinical experience beyond residency. All were planning to work on the service for 1 to 2 years before beginning a subspecialty fellowship. In addition to supervising the clinical work of the physician assistants, the hospitalists were responsible for teaching the physician assistants on rounds and in weekly didactic sessions, guided by a curriculum in hospital medicine that focused on the most common general medicine diagnoses seen on the PACE service. The medical director of the PACE service periodically reviewed each physician assistant's clinical experience, skills and knowledge base, and held semiannual feedback sessions.
Study Patients
All general medicine patients admitted to the PACE service from July 1, 2005 to June 30, 2006 comprised the study population. The comparison group consisted of general medicine patients admitted to the 8 house staff general medicine teams; patients transferred from an intensive care unit (ICU) or another facility were excluded in order to match the admission criteria for the PACE service and improve comparability between the 2 study arms.
Data Collection and Study Outcomes
We obtained all patient data from the hospital's administrative databases. We identified patients assigned to the PACE service or to the comparison group based on the admitting service, team, and attending. We obtained patient demographics, insurance, admission source and discharge destination, admission and discharge times, dates, diagnoses, and diagnosis‐related groups (DRGs), as well as dates and times of transfers to other services, including to the intensive care unit. We also obtained the Medicare case‐mix index (CMI, based on DRG weight), and calculated a Charlson score based on billing diagnoses coded in the year prior to the index admission.14 Outcomes included length of stay (LOS) to the nearest hour, in‐hospital mortality, transfers to the intensive care unit, readmissions to the study hospital within 72 hours, 14 days, and 30 days, and total costs as derived from the hospital's cost accounting system (Transition Systems Inc., Boston, MA). Other outcomes included patient satisfaction as measured by responses to the Press‐Ganey survey routinely administered to a randomly selected 70% of recently discharged patients and effect on self‐reported resident work hours.
Statistical Analysis
Patient demographics, clinical characteristics, and study outcomes are presented using proportions, means with standard deviations, and medians with inter‐quartile ranges as appropriate. Unadjusted differences in outcomes between the two services were calculated using univariable regression techniques with service as the independent variable and each outcome as the dependent variable. We used logistic regression for dichotomous outcomes (readmissions, ICU transfers, and inpatient mortality), and linear regression for log‐transformed LOS and log‐transformed total costs of care. To adjust each outcome for potential confounders, we then built multivariable regression models. Each potential confounder was entered into the model one at a time as the independent variable. All variables found to be significant predictors of the outcome at the P < 0.10 level were then retained in the final model along with service as the predictor of interest. We used general estimating equations in all multivariable models to adjust for clustering of patients by attending physician. For logistic regression models, the effect size is presented as an odds ratio (OR); for log‐transformed linear regression models, the effect size is presented as the percent difference between groups. We also performed 2 subgroup analyses, limited to (1) the patients with the 10 most common discharge DRGs, and (2) patients admitted between the hours of 7:00 AM and 7:00 PM to remove the effects of moonlighters performing the initial admission. Except as noted above, 2‐sided P values < 0.05 were considered significant. SAS 9.1 (SAS Institute, Cary, NC) was used for all analyses.
RESULTS
Patient Demographics
Table 1 shows patient demographics and clinical characteristics of the PACE service and the comparison group. Patients in the comparison group were slightly older and tended to have slightly higher CMI and Charlson scores. Patients on the PACE service were more likely to be admitted at night (10:00 PM to 7:00 AM; 43.8% versus 30.3%; P < 0.0001). There were no significant differences in sex, race, insurance, or percentage of patients discharged to home. The 10 most common DRGs in the comparison group accounted for 37.0% of discharges, and these same DRGs accounted for 37.5% of discharges on the PACE service (Table 2).
Characteristic | PACE Service (n = 992) | House Staff Services (n = 4,202) | P value |
---|---|---|---|
| |||
Age (years) | |||
1844 | 19.1 | 18.2 | |
4564 | 35.5 | 31.9 | 0.04 |
65+ | 45.5 | 49.9 | |
Sex (% female) | 57.7 | 60.0 | NS |
Race/ethnicity | |||
White | 57.3 | 59.3 | |
Black | 24.0 | 23.5 | NS |
Hispanic | 14.1 | 13.3 | |
Other | 4.6 | 3.9 | |
Insurance | |||
Medicare | 41.9 | 43.8 | |
Commercial | 34.9 | 35.9 | |
Medicaid | 14.4 | 11.7 | NS |
Free care | 4.5 | 3.9 | |
Self pay | 1.1 | 0.8 | |
Median income by zip code of residence, USD (IQR) | 45,517 (32,49362,932) | 45,517 (35,88963,275) | NS |
Case‐mix index, median (IQR) | 1.1 (0.81.5) | 1.2 (0.91.8) | 0.001 |
Charlson score | |||
0 | 27.2 | 24.9 | |
1 | 22.6 | 21.1 | 0.02 |
2 | 16.2 | 16.5 | |
3+ | 34.0 | 37.6 | |
Admissions between 10:00 PM and 7:00 AM | 43.8 | 30.3 | <0.0001 |
Discharged to home | 81.1 | 80.5 | NS |
Diagnosis‐Related Group at Discharge | PACE Service (n = 992)* | House Staff Services (n = 4,202)* |
---|---|---|
| ||
Chest pain | 5.4 | 6.4 |
Esophagitis, gastroenteritis, and miscellaneous digestive disorders | 4.5 | 4.4 |
Heart failure and shock | 3.4 | 4.6 |
Simple pneumonia and pleurisy | 2.7 | 4.4 |
Kidney and urinary tract infections | 4.7 | 3.2 |
Chronic obstructive pulmonary disease | 4.0 | 3.3 |
Renal failure | 2.7 | 3.5 |
Gastrointestinal hemorrhage | 3.7 | 2.7 |
Nutritional and miscellaneous metabolic disorders | 3.3 | 2.4 |
Disorders of the pancreas except malignancy | 3.1 | 2.1 |
Cumulative percent | 37.5 | 37.0 |
Efficiency and Quality of Care
Table 3 compares the performance of the PACE service and the comparison group on several efficiency and quality measures. Unadjusted LOS was not significantly different, and adjusted LOS was slightly but not statistically significantly higher on the study service (adjusted LOS 5.0% higher; 95% confidence interval [CI], 0.4% to +10%). Unadjusted and adjusted total costs of care were marginally lower on the study service (adjusted total cost of care 3.9% lower; 95% CI, 7.5% to 0.3%).
PACE Service | House Staff Services | Unadjusted % Difference (95%CI) | Adjusted % Difference (95%CI)* | |
---|---|---|---|---|
PACE Service | House Staff Services | Unadjusted OR (95% CI) | Adjusted OR (95% CI) | |
| ||||
Efficiency measure | ||||
Length of stay, days, median (IQR) | 2.6 (1.6, 4.4) | 2.6 (1.4, 4.6) | +0.1% (5.6% to +6.1%) | +5.0% (0.4% to +10.0%) |
Total costs, USD, median (IQR) | 4,536 (2,848, 7,201) | 4,749 (3,046, 8,161) | 9.1% (14.0% to 3.8%) | 3.9% (7.5% to 0.3%)‖ |
Quality measure | ||||
72‐hour readmissions/100 discharges | 0.8 | 1.3 | 0.6 (0.31.3) | 0.7 (0.21.8) |
14‐day readmissions/100 discharges | 5.4 | 5.4 | 1.0 (0.71.4) | 1.1 (0.81.4) |
30‐day readmissions/100 discharges | 8.0 | 8.1 | 1.0 (0.81.3) | 1.1 (0.91.3) |
ICU transfers/100 discharges | 2.0 | 2.3 | 0.9 (0.51.4) | 1.4 (0.82.4)# |
Inpatient mortality/100 discharges | 0.7 | 1.2 | 0.6 (0.31.3) | 0.8 (0.31.8)** |
We found no differences between the PACE service and comparison group in unadjusted rates of hospital readmissions within 72 hours, 14 days, and 30 days, transfer to the intensive care units, or inpatient mortality (Table 3). The associated ORs for each outcome were similar after adjusting for patient demographics and clinical characteristics including severity of illness, as well as for clustering by attending physician.
Subgroup Analyses
When the analysis was limited to the subset of patients with the 10 most common discharge DRGs, the difference in adjusted total cost of care was similar but lost statistical significance (4.0% lower on PACE service; 95% CI, 11.0% to +3.3%). In this subgroup, LOS, readmission rates, and ICU transfer rates were not different. ORs for mortality could not be calculated because there were no deaths in this subgroup on the PACE service (data not shown). When analysis was limited to daytime admissions (to remove any potential effect of admitting by a moonlighter), the difference in total cost of care was attenuated and lost statistical significance (0.2% lower on PACE service; 95%CI, 5.9% to +5.5%). No differences were seen in LOS, mortality, and ICU transfers (data not shown). However, 14‐day readmissions (but not 72‐hour or 30‐day readmissions) were lower on the PACE service (OR, 0.49; 95% CI, 0.25‐0.93).
Patient Satisfaction
Patients were similarly satisfied with their care on the PACE service and on the house staff services. In specific areas and globally, percentages of patients satisfied with their physicians and with the discharge process were not different, as measured by the Press‐Ganey survey (Press‐Ganey Associates, South Bend, IN; Figures 1 and 2). The survey distinguishes between attendings and residents, but not physician assistants; therefore, Figure 1 only includes responses to the attending questions. Given the sampling procedure of the Press‐Ganey survey, exact response rates cannot be calculated, but Press‐Ganey reports a response rate of about 40% for the English survey and about 20% for the Spanish survey.


Resident Duty Hours
Comparing the same month 1 year prior to implementation of the PACE service, mean self‐reported resident duty hours on the general medicine service were unchanged; however, self‐reported data were incomplete, and multiple changes took place in the residency program during the study period. For example, implementation of the PACE service allowed for the dissolution of one full house staff general medicine team and redistribution of these house staff to night float positions and an expanded medical intensive care unit.
Costs of Implementation
The costs associated with implementing the PACE service included physician and physician assistant salaries (2.5 full‐time physicians, 5 full‐time physician assistants, plus fringe) and night coverage by resident and fellow moonlighters (without fringe, and estimated at 50% effort given other moonlighter coverage responsibilities on subspecialty services). We estimated these costs at $257.50/patient‐day ($115/patient‐day for attending physician compensation, $110/patient‐day for physician assistant compensation, and $32.50/patient‐day for moonlighting coverage).
DISCUSSION
As academic centers struggle with developing a workforce to provide patient care no longer provided by residents, questions about the ideal structure of nonhouse staff inpatient services abound. Although solutions to this problem will be determined to some extent by local factors such as institutional culture and resources, some lessons learned in developing such services will be more widely applicable. We found that by implementing a geographically localized, physician assistant‐staffed hospitalist service, we were able to provide care of similar quality and efficiency to that of traditional house staff services, despite inexperienced hospitalists staffing the service and a medical residency program commonly recognized as one of the best in the country. Adjusted total costs were slightly lower on the PACE service, but this difference was small and of borderline statistical significance. Likewise, no significant differences were seen in any of several quality measures or in patient satisfaction.
Our findings add to the available evidence supporting the use of physician assistants on academic general medicine services, and are germane to academic centers facing reductions in house staff availability and seeking alternative models of care for inpatients. Several specific characteristics of the PACE service and the implications of these should be considered:
The service accepted all patients, regardless of diagnosis, acuity, or complexity of illness. This was unlike many previously described nonhouse staff services which were more limited in scope, and allowed more flexibility with patient flow. However, in the end, patients on the PACE service did have a modestly lower case mix index and Charlson score, suggesting that, despite a lack of triage guidelines, there was some bias in the triage of admissions, possibly due to a perception that physician assistants should take care of lower complexity patients. If it is desirable to have a similar distribution of higher complexity patients across house staff and nonhouse staff services, extra efforts may be necessary to overcome this perception.
The service was geographically regionalized. Geographic regionalization offered many important advantages, especially with regards to communication among staff, nursing, and consultants, and allowed for multidisciplinary rounds. However, it is possible that the modest, but not statistically significant, trend toward an increased LOS seen on the PACE service might be a reflection of geographic admitting (less incentive to discharge since discharging a patient means taking a new admission).
The education and professional development of the physician assistants was a priority. Physician assistants had considerable autonomy and responsibility, and rather than being assigned only lower level administrative tasks, performed all aspects of patient care. They also received regular teaching from the hospitalists, attended house staff teaching conferences, and developed nonclinical roles in education and quality improvement. The higher standards expected of the physician assistants were quite possibly a factor in the quality of care delivered, and almost certainly contributed to physician assistant satisfaction and retention.
Our findings contrast with those of Myers et al.,9 who found that a nonteaching service staffed by hospitalists and nurse practitioners had a significantly lower median LOS and hospital charges compared to similar patients on resident‐based services. However, unlike ours, their service cared for a select patient population, and only accepted patients with chest pain at low risk for acute coronary syndrome. Van Rhee et al.10 found that physician assistants on a general medicine service used fewer resources for patients with pneumonia, stroke, and congestive heart failure than resident physicians, and did not exceed the resources used by residents in other diagnoses. The authors did not find a difference in LOS, but did find a significantly higher mortality among patients with pneumonia cared for by physician assistants.
Several limitations should be noted. First, the study was a retrospective analysis of administrative data rather than a randomized trial, and although we employed a standard approach to adjust for a wide range of patient characteristics including severity of illness, there may have been undetected differences in the patient populations studied that may have confounded our results. Second, resident moonlighters admitted patients to the PACE service and, at other times, to the house staff services, and this may have diluted any differences between the groups. However, when we limited our analysis to the subgroup of patients admitted during the day, similar results were obtained, with the exception that the PACE service had a lower rate of 14‐day readmissions, an unexpected finding deserving of further study. Third, the study was conducted in a single academic institution and our findings may not be generalizable to others with different needs and resources; indeed, the costs associated with implementing such a service may be prohibitive for some institutions. Fourth, because of simultaneous changes that were taking place in our residency program, we are unable to accurately assess the impact of the PACE service on resident duty hours. However, resident duty hours did not increase over this time period on the general medicine service, and implementation of the service allowed for redistribution of house staff to other services and positions. Fifth, patient satisfaction data were obtained from responses to the mailed Press‐Ganey survey, to which there is a relatively low response rate. Also, we did not survey providers regarding their satisfaction with the service during the study period. Sixth, the study had limited power to detect clinically important differences in mortality and ICU transfers. Finally, this study is unable to compare this particular model of incorporating midlevel providers into general medical services with other models, only with traditional house staff services.
Future research should focus on determining the most effective and efficient ways to incorporate midlevel providers on academic general medicine services. One important question from the standpoint of house staff training is whether such services should be separate but equal, or should house staff gain experience during residency working with midlevel providers, since they are likely to encounter them in the future whether they stay in academics or not. Different models of care will likely have large implications for the quality and efficiency of patient care, house staff education and satisfaction, and physician assistant job satisfaction and turnover.
In summary, our study demonstrates that a geographically regionalized, multidisciplinary service staffed by hospitalists and physician assistants can be a safe alternative to house staff‐based services for the care of general medicine inpatients in an academic medical center.
Midlevel providers (physician assistants and nurse practitioners) have long been employed by academic medical centers, predominantly on surgical services, or on medical subspecialty services, where they have typically had a limited scope of practice, focused in a narrowly defined area or set of procedures.17 In contrast, there are relatively few reports of experiences deploying midlevel providers to replace house staff on inpatient general medicine services in academic centers,810 and few studies of the effect of midlevel providers on quality and efficiency of care in the academic setting. Despite this, reductions in house officer duty hours as mandated by the Accreditation Council on Graduate Medical Education (ACGME)11 have resulted in academic centers increasingly using midlevel providers to decrease house staff workload on inpatient services.12, 13 In general, midlevel practitioners on general medicine services have been deployed to: (1) care for a population of patients separate from and in parallel with house staff; this population may be narrowly defined (eg, patients with chest pain) or not; (2) assist with the management of patients cared for by house staff by performing certain tasks (eg, scheduling appointments, discharging patients). Even as midlevel providers become more prevalent on academic general medicine services, the best model of care incorporating them into clinical care remains unclear, and few studies have rigorously examined the care provided on services that use them.
We developed an inpatient general medicine service within a large academic medical center staffed by physician assistants and hospitalists to help our residency program meet ACGME duty hour requirements. We hypothesized that by creating a service that is geographically localized and supervised by full‐time hospitalists, by instituting multidisciplinary rounds, and by investing in the professional development of highly‐skilled physician assistants, we could provide care for medically complex, acutely ill general medicine inpatients with similar quality and efficiency as compared to house staff teams. We report our experience during the first year of implementing the service, and compare quality and efficiency of care on this service with that of our traditional house staff services. We also evaluate the effects of this service on patient satisfaction and self‐reported house staff workload.
PATIENTS AND METHODS
Study Setting
The study was conducted in a 747‐bed urban, academic medical center in the northeastern United States. The hospital's human research committee reviewed and approved the study design. The hospital has accredited residency and fellowship programs in all major specialties. Prior to July 2005, physician assistants were employed only on surgical and medical subspecialty services (ie, bone marrow transplant, interventional cardiology); none were employed on the inpatient general medicine service. There were approximately 44,000 inpatient admissions during the year of the study, with approximately 6500 of these to the general medicine service.
Description of the General Medicine Service
The General Medicine Service consisted of 8 traditional house staff teams, with 1 attending, 1 junior or senior resident, 2 interns, and 1 or 2 medical students. These teams admitted patients on a rotating basis every fourth day. On 4 of these teams, the attending was a hospitalist, with clinical responsibility for the majority of the patients admitted to the team. On the remaining 4 teams, the teaching attending was a primary care physician or medical subspecialist, responsible for the direct care of a small number of the team's patients, with the remainder cared for by private primary care physicians or subspecialists.
Description of the Physician Assistant/Hospitalist Service
The Physician Assistant/Clinician Educator (PACE) service opened in July 2005, and consisted of 15 beds localized to 2 adjacent inpatient pods, staffed by a single cadre of nurses and medically staffed by 1 hospitalist and 2 physician assistants from 7:00 AM to 7:00 PM on weekdays and by 1 hospitalist, 1 physician assistant, and 1 moonlighter (usually a senior medical resident or fellow) from 7:00 AM to 7:00 PM on weekends. A moonlighter, typically a senior resident or medical subspecialty fellow, admitted patients and covered nights on the service from 7:00 PM to 7:00 AM 7 days a week. The daily census goal for the service was 15 patients, limited by the number of available beds on the 2 pods, and the service accepted admissions 24 hours per day, 7 days per week, whenever beds were available. Daily morning rounds occurred at 8:00 AM and included the hospitalist, physician assistants, nurses, a care coordinator, and a pharmacist. The PACE service did not have triage guidelines related to diagnosis, complexity, or acuity, but only accepted patients via the emergency department or via a primary care physician's office, and did not accept patients transferred from outside hospitals or from the intensive care units.
Physician Assistants
All of the physician assistants on the PACE service had prior inpatient medicine experience, ranging from 6 months to 5 years. The physician assistants worked in 3‐day to 6‐day blocks of 12‐hour shifts. Their clinical responsibilities were similar to those of interns at the study hospital, and included taking histories and performing physical examinations, writing notes and orders, reviewing and assimilating data, creating and updating patient signouts, completing discharge summaries, consulting other services as needed, and communicating with nurses and family members.
Many physician assistants also had nonclinical responsibilities, taking on physician‐mentored roles in education, quality improvement, and administration. They were involved in several initiatives: (1) developing a physician assistant curriculum in hospital medicine, (2) presenting at hospital‐wide physician assistant grand rounds, (3) surveying and tracking patient and family satisfaction on the service, (4) reviewing all 72‐hour hospital readmissions, intensive care unit transfers, and deaths on the service, and (5) maintaining the service's compliance with state regulations regarding physician assistant scope of practice and prescribing.
Hospitalists
The 3 hospitalists on the PACE service worked in 7‐day blocks of 12‐hour shifts (7:00 AM to 7:00 PM). They directly supervised the physician assistants and had no competing responsibilities. The hospitalists were all recent graduates of the study hospital's internal medicine residency, with no prior clinical experience beyond residency. All were planning to work on the service for 1 to 2 years before beginning a subspecialty fellowship. In addition to supervising the clinical work of the physician assistants, the hospitalists were responsible for teaching the physician assistants on rounds and in weekly didactic sessions, guided by a curriculum in hospital medicine that focused on the most common general medicine diagnoses seen on the PACE service. The medical director of the PACE service periodically reviewed each physician assistant's clinical experience, skills and knowledge base, and held semiannual feedback sessions.
Study Patients
All general medicine patients admitted to the PACE service from July 1, 2005 to June 30, 2006 comprised the study population. The comparison group consisted of general medicine patients admitted to the 8 house staff general medicine teams; patients transferred from an intensive care unit (ICU) or another facility were excluded in order to match the admission criteria for the PACE service and improve comparability between the 2 study arms.
Data Collection and Study Outcomes
We obtained all patient data from the hospital's administrative databases. We identified patients assigned to the PACE service or to the comparison group based on the admitting service, team, and attending. We obtained patient demographics, insurance, admission source and discharge destination, admission and discharge times, dates, diagnoses, and diagnosis‐related groups (DRGs), as well as dates and times of transfers to other services, including to the intensive care unit. We also obtained the Medicare case‐mix index (CMI, based on DRG weight), and calculated a Charlson score based on billing diagnoses coded in the year prior to the index admission.14 Outcomes included length of stay (LOS) to the nearest hour, in‐hospital mortality, transfers to the intensive care unit, readmissions to the study hospital within 72 hours, 14 days, and 30 days, and total costs as derived from the hospital's cost accounting system (Transition Systems Inc., Boston, MA). Other outcomes included patient satisfaction as measured by responses to the Press‐Ganey survey routinely administered to a randomly selected 70% of recently discharged patients and effect on self‐reported resident work hours.
Statistical Analysis
Patient demographics, clinical characteristics, and study outcomes are presented using proportions, means with standard deviations, and medians with inter‐quartile ranges as appropriate. Unadjusted differences in outcomes between the two services were calculated using univariable regression techniques with service as the independent variable and each outcome as the dependent variable. We used logistic regression for dichotomous outcomes (readmissions, ICU transfers, and inpatient mortality), and linear regression for log‐transformed LOS and log‐transformed total costs of care. To adjust each outcome for potential confounders, we then built multivariable regression models. Each potential confounder was entered into the model one at a time as the independent variable. All variables found to be significant predictors of the outcome at the P < 0.10 level were then retained in the final model along with service as the predictor of interest. We used general estimating equations in all multivariable models to adjust for clustering of patients by attending physician. For logistic regression models, the effect size is presented as an odds ratio (OR); for log‐transformed linear regression models, the effect size is presented as the percent difference between groups. We also performed 2 subgroup analyses, limited to (1) the patients with the 10 most common discharge DRGs, and (2) patients admitted between the hours of 7:00 AM and 7:00 PM to remove the effects of moonlighters performing the initial admission. Except as noted above, 2‐sided P values < 0.05 were considered significant. SAS 9.1 (SAS Institute, Cary, NC) was used for all analyses.
RESULTS
Patient Demographics
Table 1 shows patient demographics and clinical characteristics of the PACE service and the comparison group. Patients in the comparison group were slightly older and tended to have slightly higher CMI and Charlson scores. Patients on the PACE service were more likely to be admitted at night (10:00 PM to 7:00 AM; 43.8% versus 30.3%; P < 0.0001). There were no significant differences in sex, race, insurance, or percentage of patients discharged to home. The 10 most common DRGs in the comparison group accounted for 37.0% of discharges, and these same DRGs accounted for 37.5% of discharges on the PACE service (Table 2).
Characteristic | PACE Service (n = 992) | House Staff Services (n = 4,202) | P value |
---|---|---|---|
| |||
Age (years) | |||
1844 | 19.1 | 18.2 | |
4564 | 35.5 | 31.9 | 0.04 |
65+ | 45.5 | 49.9 | |
Sex (% female) | 57.7 | 60.0 | NS |
Race/ethnicity | |||
White | 57.3 | 59.3 | |
Black | 24.0 | 23.5 | NS |
Hispanic | 14.1 | 13.3 | |
Other | 4.6 | 3.9 | |
Insurance | |||
Medicare | 41.9 | 43.8 | |
Commercial | 34.9 | 35.9 | |
Medicaid | 14.4 | 11.7 | NS |
Free care | 4.5 | 3.9 | |
Self pay | 1.1 | 0.8 | |
Median income by zip code of residence, USD (IQR) | 45,517 (32,49362,932) | 45,517 (35,88963,275) | NS |
Case‐mix index, median (IQR) | 1.1 (0.81.5) | 1.2 (0.91.8) | 0.001 |
Charlson score | |||
0 | 27.2 | 24.9 | |
1 | 22.6 | 21.1 | 0.02 |
2 | 16.2 | 16.5 | |
3+ | 34.0 | 37.6 | |
Admissions between 10:00 PM and 7:00 AM | 43.8 | 30.3 | <0.0001 |
Discharged to home | 81.1 | 80.5 | NS |
Diagnosis‐Related Group at Discharge | PACE Service (n = 992)* | House Staff Services (n = 4,202)* |
---|---|---|
| ||
Chest pain | 5.4 | 6.4 |
Esophagitis, gastroenteritis, and miscellaneous digestive disorders | 4.5 | 4.4 |
Heart failure and shock | 3.4 | 4.6 |
Simple pneumonia and pleurisy | 2.7 | 4.4 |
Kidney and urinary tract infections | 4.7 | 3.2 |
Chronic obstructive pulmonary disease | 4.0 | 3.3 |
Renal failure | 2.7 | 3.5 |
Gastrointestinal hemorrhage | 3.7 | 2.7 |
Nutritional and miscellaneous metabolic disorders | 3.3 | 2.4 |
Disorders of the pancreas except malignancy | 3.1 | 2.1 |
Cumulative percent | 37.5 | 37.0 |
Efficiency and Quality of Care
Table 3 compares the performance of the PACE service and the comparison group on several efficiency and quality measures. Unadjusted LOS was not significantly different, and adjusted LOS was slightly but not statistically significantly higher on the study service (adjusted LOS 5.0% higher; 95% confidence interval [CI], 0.4% to +10%). Unadjusted and adjusted total costs of care were marginally lower on the study service (adjusted total cost of care 3.9% lower; 95% CI, 7.5% to 0.3%).
PACE Service | House Staff Services | Unadjusted % Difference (95%CI) | Adjusted % Difference (95%CI)* | |
---|---|---|---|---|
PACE Service | House Staff Services | Unadjusted OR (95% CI) | Adjusted OR (95% CI) | |
| ||||
Efficiency measure | ||||
Length of stay, days, median (IQR) | 2.6 (1.6, 4.4) | 2.6 (1.4, 4.6) | +0.1% (5.6% to +6.1%) | +5.0% (0.4% to +10.0%) |
Total costs, USD, median (IQR) | 4,536 (2,848, 7,201) | 4,749 (3,046, 8,161) | 9.1% (14.0% to 3.8%) | 3.9% (7.5% to 0.3%)‖ |
Quality measure | ||||
72‐hour readmissions/100 discharges | 0.8 | 1.3 | 0.6 (0.31.3) | 0.7 (0.21.8) |
14‐day readmissions/100 discharges | 5.4 | 5.4 | 1.0 (0.71.4) | 1.1 (0.81.4) |
30‐day readmissions/100 discharges | 8.0 | 8.1 | 1.0 (0.81.3) | 1.1 (0.91.3) |
ICU transfers/100 discharges | 2.0 | 2.3 | 0.9 (0.51.4) | 1.4 (0.82.4)# |
Inpatient mortality/100 discharges | 0.7 | 1.2 | 0.6 (0.31.3) | 0.8 (0.31.8)** |
We found no differences between the PACE service and comparison group in unadjusted rates of hospital readmissions within 72 hours, 14 days, and 30 days, transfer to the intensive care units, or inpatient mortality (Table 3). The associated ORs for each outcome were similar after adjusting for patient demographics and clinical characteristics including severity of illness, as well as for clustering by attending physician.
Subgroup Analyses
When the analysis was limited to the subset of patients with the 10 most common discharge DRGs, the difference in adjusted total cost of care was similar but lost statistical significance (4.0% lower on PACE service; 95% CI, 11.0% to +3.3%). In this subgroup, LOS, readmission rates, and ICU transfer rates were not different. ORs for mortality could not be calculated because there were no deaths in this subgroup on the PACE service (data not shown). When analysis was limited to daytime admissions (to remove any potential effect of admitting by a moonlighter), the difference in total cost of care was attenuated and lost statistical significance (0.2% lower on PACE service; 95%CI, 5.9% to +5.5%). No differences were seen in LOS, mortality, and ICU transfers (data not shown). However, 14‐day readmissions (but not 72‐hour or 30‐day readmissions) were lower on the PACE service (OR, 0.49; 95% CI, 0.25‐0.93).
Patient Satisfaction
Patients were similarly satisfied with their care on the PACE service and on the house staff services. In specific areas and globally, percentages of patients satisfied with their physicians and with the discharge process were not different, as measured by the Press‐Ganey survey (Press‐Ganey Associates, South Bend, IN; Figures 1 and 2). The survey distinguishes between attendings and residents, but not physician assistants; therefore, Figure 1 only includes responses to the attending questions. Given the sampling procedure of the Press‐Ganey survey, exact response rates cannot be calculated, but Press‐Ganey reports a response rate of about 40% for the English survey and about 20% for the Spanish survey.


Resident Duty Hours
Comparing the same month 1 year prior to implementation of the PACE service, mean self‐reported resident duty hours on the general medicine service were unchanged; however, self‐reported data were incomplete, and multiple changes took place in the residency program during the study period. For example, implementation of the PACE service allowed for the dissolution of one full house staff general medicine team and redistribution of these house staff to night float positions and an expanded medical intensive care unit.
Costs of Implementation
The costs associated with implementing the PACE service included physician and physician assistant salaries (2.5 full‐time physicians, 5 full‐time physician assistants, plus fringe) and night coverage by resident and fellow moonlighters (without fringe, and estimated at 50% effort given other moonlighter coverage responsibilities on subspecialty services). We estimated these costs at $257.50/patient‐day ($115/patient‐day for attending physician compensation, $110/patient‐day for physician assistant compensation, and $32.50/patient‐day for moonlighting coverage).
DISCUSSION
As academic centers struggle with developing a workforce to provide patient care no longer provided by residents, questions about the ideal structure of nonhouse staff inpatient services abound. Although solutions to this problem will be determined to some extent by local factors such as institutional culture and resources, some lessons learned in developing such services will be more widely applicable. We found that by implementing a geographically localized, physician assistant‐staffed hospitalist service, we were able to provide care of similar quality and efficiency to that of traditional house staff services, despite inexperienced hospitalists staffing the service and a medical residency program commonly recognized as one of the best in the country. Adjusted total costs were slightly lower on the PACE service, but this difference was small and of borderline statistical significance. Likewise, no significant differences were seen in any of several quality measures or in patient satisfaction.
Our findings add to the available evidence supporting the use of physician assistants on academic general medicine services, and are germane to academic centers facing reductions in house staff availability and seeking alternative models of care for inpatients. Several specific characteristics of the PACE service and the implications of these should be considered:
The service accepted all patients, regardless of diagnosis, acuity, or complexity of illness. This was unlike many previously described nonhouse staff services which were more limited in scope, and allowed more flexibility with patient flow. However, in the end, patients on the PACE service did have a modestly lower case mix index and Charlson score, suggesting that, despite a lack of triage guidelines, there was some bias in the triage of admissions, possibly due to a perception that physician assistants should take care of lower complexity patients. If it is desirable to have a similar distribution of higher complexity patients across house staff and nonhouse staff services, extra efforts may be necessary to overcome this perception.
The service was geographically regionalized. Geographic regionalization offered many important advantages, especially with regards to communication among staff, nursing, and consultants, and allowed for multidisciplinary rounds. However, it is possible that the modest, but not statistically significant, trend toward an increased LOS seen on the PACE service might be a reflection of geographic admitting (less incentive to discharge since discharging a patient means taking a new admission).
The education and professional development of the physician assistants was a priority. Physician assistants had considerable autonomy and responsibility, and rather than being assigned only lower level administrative tasks, performed all aspects of patient care. They also received regular teaching from the hospitalists, attended house staff teaching conferences, and developed nonclinical roles in education and quality improvement. The higher standards expected of the physician assistants were quite possibly a factor in the quality of care delivered, and almost certainly contributed to physician assistant satisfaction and retention.
Our findings contrast with those of Myers et al.,9 who found that a nonteaching service staffed by hospitalists and nurse practitioners had a significantly lower median LOS and hospital charges compared to similar patients on resident‐based services. However, unlike ours, their service cared for a select patient population, and only accepted patients with chest pain at low risk for acute coronary syndrome. Van Rhee et al.10 found that physician assistants on a general medicine service used fewer resources for patients with pneumonia, stroke, and congestive heart failure than resident physicians, and did not exceed the resources used by residents in other diagnoses. The authors did not find a difference in LOS, but did find a significantly higher mortality among patients with pneumonia cared for by physician assistants.
Several limitations should be noted. First, the study was a retrospective analysis of administrative data rather than a randomized trial, and although we employed a standard approach to adjust for a wide range of patient characteristics including severity of illness, there may have been undetected differences in the patient populations studied that may have confounded our results. Second, resident moonlighters admitted patients to the PACE service and, at other times, to the house staff services, and this may have diluted any differences between the groups. However, when we limited our analysis to the subgroup of patients admitted during the day, similar results were obtained, with the exception that the PACE service had a lower rate of 14‐day readmissions, an unexpected finding deserving of further study. Third, the study was conducted in a single academic institution and our findings may not be generalizable to others with different needs and resources; indeed, the costs associated with implementing such a service may be prohibitive for some institutions. Fourth, because of simultaneous changes that were taking place in our residency program, we are unable to accurately assess the impact of the PACE service on resident duty hours. However, resident duty hours did not increase over this time period on the general medicine service, and implementation of the service allowed for redistribution of house staff to other services and positions. Fifth, patient satisfaction data were obtained from responses to the mailed Press‐Ganey survey, to which there is a relatively low response rate. Also, we did not survey providers regarding their satisfaction with the service during the study period. Sixth, the study had limited power to detect clinically important differences in mortality and ICU transfers. Finally, this study is unable to compare this particular model of incorporating midlevel providers into general medical services with other models, only with traditional house staff services.
Future research should focus on determining the most effective and efficient ways to incorporate midlevel providers on academic general medicine services. One important question from the standpoint of house staff training is whether such services should be separate but equal, or should house staff gain experience during residency working with midlevel providers, since they are likely to encounter them in the future whether they stay in academics or not. Different models of care will likely have large implications for the quality and efficiency of patient care, house staff education and satisfaction, and physician assistant job satisfaction and turnover.
In summary, our study demonstrates that a geographically regionalized, multidisciplinary service staffed by hospitalists and physician assistants can be a safe alternative to house staff‐based services for the care of general medicine inpatients in an academic medical center.
- The physician's assistant as resident on surgical service. An example of creative problem solving in surgical manpower.Arch Surg.1980;115:310–314. , , , , , .
- Coronary arteriography performed by a physician assistant.Am J Cardiol.1987;60:784–787. , , , .
- The specialized physician assistant: an alternative to the clinical cardiology trainee.Am J Cardiol.1987;60:901–902. .
- One hospital's successful 20‐year experience with physician assistants in graduate medical education.Acad Med.1999;74:641–645. , , .
- Physicians assistants in cardiothoracic surgery: a 30‐year experience in a university center.Ann Thorac Surg.2006;81:195–199; discussion 199–200. , .
- Comparative review of use of physician assistants in a level I trauma center.Am Surg.2004;70:272–279. , , .
- Integrating midlevel practitioners into a teaching service.Am J Surg.2006;192:119–124. , , , , .
- Acute care nurse practitioners: creating and implementing a model of care for an inpatient general medical service.Am J Crit Care.2002;11:448–458. , .
- Improving resource utilization in a teaching hospital: development of a nonteaching service for chest pain admissions.Acad Med.2006;81:432–435. , , , , .
- Resource use by physician assistant services versus teaching services.JAAPA.2002;15:33–38. , , .
- for the ACGME Work Group on Resident Duty Hours, Accreditation Council for Graduate Medical Education.New requirements for resident duty hours.JAMA.2002;288:1112–1114. , , ,
- The substitution of physician assistants and nurse practitioners for physician residents in teaching hospitals.Health Aff.1995;14:181–191. , , .
- Challenges of the 80‐hour resident work rules: collaboration between surgeons and nonphysician practitioners.Surg Clin North Am.2004;84:1573–1586. , , , , .
- Adapting a clinical comorbidity index for use with ICD‐9‐CM administrative databases.J Clin Epidemiol.1992;45:613–619. , , .
- The physician's assistant as resident on surgical service. An example of creative problem solving in surgical manpower.Arch Surg.1980;115:310–314. , , , , , .
- Coronary arteriography performed by a physician assistant.Am J Cardiol.1987;60:784–787. , , , .
- The specialized physician assistant: an alternative to the clinical cardiology trainee.Am J Cardiol.1987;60:901–902. .
- One hospital's successful 20‐year experience with physician assistants in graduate medical education.Acad Med.1999;74:641–645. , , .
- Physicians assistants in cardiothoracic surgery: a 30‐year experience in a university center.Ann Thorac Surg.2006;81:195–199; discussion 199–200. , .
- Comparative review of use of physician assistants in a level I trauma center.Am Surg.2004;70:272–279. , , .
- Integrating midlevel practitioners into a teaching service.Am J Surg.2006;192:119–124. , , , , .
- Acute care nurse practitioners: creating and implementing a model of care for an inpatient general medical service.Am J Crit Care.2002;11:448–458. , .
- Improving resource utilization in a teaching hospital: development of a nonteaching service for chest pain admissions.Acad Med.2006;81:432–435. , , , , .
- Resource use by physician assistant services versus teaching services.JAAPA.2002;15:33–38. , , .
- for the ACGME Work Group on Resident Duty Hours, Accreditation Council for Graduate Medical Education.New requirements for resident duty hours.JAMA.2002;288:1112–1114. , , ,
- The substitution of physician assistants and nurse practitioners for physician residents in teaching hospitals.Health Aff.1995;14:181–191. , , .
- Challenges of the 80‐hour resident work rules: collaboration between surgeons and nonphysician practitioners.Surg Clin North Am.2004;84:1573–1586. , , , , .
- Adapting a clinical comorbidity index for use with ICD‐9‐CM administrative databases.J Clin Epidemiol.1992;45:613–619. , , .
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