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Program meets social needs of 90% of patients
WASHINGTON – An innovative screening and referral model using electronic health records (EHRs) helped patients overcome social determinants of health (SDOH) by providing them with resources they had requested, according to a study.
“Our goal was to find whether this pilot program is feasible to systematically screen and refer patients for social needs in ambulatory care,” said Pablo Buitron de la Vega, MD, of Boston Medical Center (BMC) at the annual meeting of the Society of General Internal Medicine.
The program, called THRIVE, helps clinicians better understand patients’ social needs through a screening process to improve their health. THRIVE uses EHRs to document patient needs related to SDOH by using ICD-10 codes. This facilitates accurate data reporting and provides insight into social impacts on a patient. This component also matches SDOH needs to referral resources. In this pilot program, patients were screened during their primary care visits.
As of December 2018, THRIVE has demonstrated feasibility across all of its clinics. Eighty-two percent of patients were screened for social needs; 86% of patients received an ICD-10 code to document their social needs in their medical files for diagnosis and billing; and
The observational survey screened 50,532 unique patients seeking care at BMC between July 2017 and December 2018. In this population, 70% were underserved minorities (with 60% black patients and 10% Hispanic patients), 50% were below the federal poverty level, and 30% did not speak English as their primary language.
Of the screened population, 28% (13,975) of the patients identified having one or more social need. In addition, 19% (9,714) of patients requested help with one or more of their needs. The most prevalent needs were food insecurity, housing/shelter, and education, with 11% of patients listing each of these as a need.
The pilot program has been scaled up to include all patients presenting to 13 ambulatory clinics in family medicine, obstetrics and gynecology, infectious diseases, and pediatrics at Boston Medical Center.
WASHINGTON – An innovative screening and referral model using electronic health records (EHRs) helped patients overcome social determinants of health (SDOH) by providing them with resources they had requested, according to a study.
“Our goal was to find whether this pilot program is feasible to systematically screen and refer patients for social needs in ambulatory care,” said Pablo Buitron de la Vega, MD, of Boston Medical Center (BMC) at the annual meeting of the Society of General Internal Medicine.
The program, called THRIVE, helps clinicians better understand patients’ social needs through a screening process to improve their health. THRIVE uses EHRs to document patient needs related to SDOH by using ICD-10 codes. This facilitates accurate data reporting and provides insight into social impacts on a patient. This component also matches SDOH needs to referral resources. In this pilot program, patients were screened during their primary care visits.
As of December 2018, THRIVE has demonstrated feasibility across all of its clinics. Eighty-two percent of patients were screened for social needs; 86% of patients received an ICD-10 code to document their social needs in their medical files for diagnosis and billing; and
The observational survey screened 50,532 unique patients seeking care at BMC between July 2017 and December 2018. In this population, 70% were underserved minorities (with 60% black patients and 10% Hispanic patients), 50% were below the federal poverty level, and 30% did not speak English as their primary language.
Of the screened population, 28% (13,975) of the patients identified having one or more social need. In addition, 19% (9,714) of patients requested help with one or more of their needs. The most prevalent needs were food insecurity, housing/shelter, and education, with 11% of patients listing each of these as a need.
The pilot program has been scaled up to include all patients presenting to 13 ambulatory clinics in family medicine, obstetrics and gynecology, infectious diseases, and pediatrics at Boston Medical Center.
WASHINGTON – An innovative screening and referral model using electronic health records (EHRs) helped patients overcome social determinants of health (SDOH) by providing them with resources they had requested, according to a study.
“Our goal was to find whether this pilot program is feasible to systematically screen and refer patients for social needs in ambulatory care,” said Pablo Buitron de la Vega, MD, of Boston Medical Center (BMC) at the annual meeting of the Society of General Internal Medicine.
The program, called THRIVE, helps clinicians better understand patients’ social needs through a screening process to improve their health. THRIVE uses EHRs to document patient needs related to SDOH by using ICD-10 codes. This facilitates accurate data reporting and provides insight into social impacts on a patient. This component also matches SDOH needs to referral resources. In this pilot program, patients were screened during their primary care visits.
As of December 2018, THRIVE has demonstrated feasibility across all of its clinics. Eighty-two percent of patients were screened for social needs; 86% of patients received an ICD-10 code to document their social needs in their medical files for diagnosis and billing; and
The observational survey screened 50,532 unique patients seeking care at BMC between July 2017 and December 2018. In this population, 70% were underserved minorities (with 60% black patients and 10% Hispanic patients), 50% were below the federal poverty level, and 30% did not speak English as their primary language.
Of the screened population, 28% (13,975) of the patients identified having one or more social need. In addition, 19% (9,714) of patients requested help with one or more of their needs. The most prevalent needs were food insecurity, housing/shelter, and education, with 11% of patients listing each of these as a need.
The pilot program has been scaled up to include all patients presenting to 13 ambulatory clinics in family medicine, obstetrics and gynecology, infectious diseases, and pediatrics at Boston Medical Center.
REPORTING FROM SGIM 2019
Key clinical point: It is feasible to identify and help those affected by the social determinants of health within the primary care setting.
Major finding: 90% of the patients who reported having a social need received resources for all of their needs.
Study details: Observational survey. 13,975 identified one or more social needs, 9,714 patients requested help with one or more needs.
Disclosures: Study sponsored by Boston Medical Center.
Surgical Dermatoethics for the Trainee
It is an uncomfortable and unavoidable reality as physicians that for every procedure we learn, there must be a first time we perform it. As with any type of skill, it takes practice to become proficient. The unique challenge in medicine is that the practice involves performing procedures on real patients. We cannot avoid the hands-on nature of the training process; we can, however, approach its ethical challenges mindfully. Herein, I will discuss some of the ethical considerations in providing care as a trainee and identify potential barriers to best practices, particularly as they relate to procedural dermatology.
Tell Patients You Are in Training
In every patient encounter, we must introduce ourselves as a trainee. The principle of right to the truth dictates that we are transparent about our level of training and do not misrepresent ourselves to our patients. A statement released by the American Medical Association (AMA) Council on Ethical and Judicial Affairs asserts that “[p]atients should be informed of the identity and training status of individuals involved in their care.”1
Although straightforward in theory, this mandate is not always simple in practice. With patients unfamiliar with the health care system, it could be more onerous to clearly communicate training status than simply introducing oneself as a resident. A study conducted in the emergency department at Vanderbilt University Hospital (Nashville, Tennessee) found that many patients and their family members (N=430) did not understand the various roles and responsibilities of physicians in the teaching hospital setting. For example, 30% believed an attending physician requires supervision by a resident, and an additional 17% of those surveyed were not sure.2 The AMA requests we “refrain from using terms that may be confusing when describing the training status of the students,”1 which evidently is audience specific. Thus, as with any type of patient education, a thorough introduction may require assessment of understanding.
Disclosure of Experience Level With a Particular Procedure
There is a clear professional expectation that we disclose to patients that we are in training; however, a universal standard does not exist for disclosure of our exact level of experience in a particular procedure. Do we need to tell patients if it is our first time performing a given procedure? What if it is our tenth? Multiple studies have found that patients want specifics. In one study of bariatric surgery patients (N=108), 93% felt that they should always be informed if it was the first time a trainee was performing a particular procedure.3 A study conducted in the emergency department setting (N=202) also found that the majority of patients thought they should be informed if a resident was performing a procedure for the first time, but the distribution differed by procedure (66% for suturing vs 82% for lumbar puncture).4
Despite these findings, this degree of specificity is not always discussed with patients and perhaps does not need to be. LaRosa and Grant-Kels5 analyzed a hypothetical scenario in which a dermatology resident is to perform his first excision under attending supervision and concluded that broad disclosure of training status would suffice in the given scenario, as it would not be necessary to state that it was his first time performing an excision. It is unclear if the same conclusion could be drawn for all procedures and levels of experience. Outcome data would help inform the analysis, but the available data are from other specialties including general surgery, gynecology, and urology. Some studies demonstrate an increased risk of adverse outcomes with trainee involvement in procedures such as bariatric surgery and emergency general surgery, but the data are mixed and may not be generalizable to dermatologic procedures.6-8
The appropriate level of detail to disclose regarding a physician’s experience may need to be assessed on a case-by-case basis, and the principles of informed consent can help. Informed consent requires understanding of the diagnosis, the treatment options including nonintervention, and the risks and benefits of each alternative. In obtaining informed consent, we must disclose “any facts which are necessary to form the basis of an intelligent consent by the patient to the proposed treatment.”9 Providers must determine what aspects of a trainee’s experience level are relevant to the risk-benefit analysis in a given set of circumstances. Surely, there is a large degree of subjectivity in this determination as data are limited, but information deemed relevant must be shared. Information that is inconsequential, on the other hand, may be omitted. It could even be argued that more detailed information, especially if it may cause anxiety, would be detrimental to share. For example, we would not list the chemical name of every preservative in every vaccine we recommend for children if there is no evidence of inflicting harm. If the information has not been shown to have clinical impact or affect safety concerns, the anxiety may be undue.
Withholding Information Can Violate Ethical Principles
We must be careful not to withhold details of our experience level with a particular procedure for the wrong reasons. It would be wrong, for example, to withhold information simply to avoid causing anxiety, which could be seen as an invocation of therapeutic privilege, a controversial practice of withholding important information that poses a psychological threat to the patient. A classic example is the physician who defers disclosure of a terminal diagnosis to preserve hope. Although therapeutic privilege theoretically promotes the principle of beneficence, it violates the principles of autonomy and right to truth and therefore generally is regarded as unethically paternalistic in modern medical ethics.9
Patients Can Refuse Trainee Participation
It also is unethical to withhold information to obtain consent and avoid refusal of our care. Refusal of trainee participation is not uncommon. In the aforementioned study of bariatric surgery patients, 92.4% supported their procedure being performed at a teaching hospital, but only 56% would consent to a resident assisting staff during the procedure. A mere 33% of those patients would consent to a resident primarily performing with staff assisting.3 Although the proportion of patients who refuse certainly depends on the type of procedure among other factors, it is a reality in any teaching environment. The training paradigm in medicine depends on being able to practice procedures with supervision before we are independent providers. If patients refuse our care, our training suffers. However, the AMA maintains that “[p]atients are free to choose from whom they receive treatment,”1 and we must respect this aspect of patient autonomy.
Final Thoughts
When it comes to the performance of procedures, there are a few basic principles to keep in mind to provide ethical care to our patients while we are in training. Although we must accept that a crucial part of learning dermatologic procedures is hands on with real patients, we also need to come prepared having learned what we can through reading and practice with cadavers or skin substitutes. Procedures we execute as residents should be performed with adequate supervision, and as we progress through residency, we should be given increased autonomy and graded responsibility to prepare us for independent practice at graduation. Although it is the responsibility of the attending physician to provide appropriate oversight for the resident’s level of training, we should feel empowered to ask for help and have the humility to know when we need it.
- Medical student involvement in patient care: report of the council on ethical and judicial affairs. Virtual Mentor. 2001;3. doi:10.1001/virtualmentor.2001.3.3.code1-0103.
- Santen S, Hemphill RR, Prough E, et al. Do patients understand their physician’s level of training? a survey of emergency department patients. Acad Med. 2004;79:139-143.
- McClellan JM, Nelson D, Porta CR, et al. Bariatric surgery patient perceptions and willingness to consent to resident participation. Surg Obes Relat Dis. 2016;12:1065-1071.
- Santen SA, Hemphill RR, McDonald MF, et al. Patients’ willingness to allow residents to learn to practice medical procedures. Acad Med. 2004;79:144-147.
- LaRosa C, Grant-Kels JM. See one, do one, teach one: the ethical dilemma of residents performing their first procedure on patients. J Am Acad Dermatol. 2016;75:845-848.
- Can MF. The trainee effect on early postoperative surgical outcomes: reflects the effect of resident involvement or hospital capacity to overcome complications? J Invest Surg. 2017;31:67-68.
- Goldberg I, Yang J, Park J, et al. Surgical trainee impact on bariatric surgery safety [published online November 13, 2018]. Surg Endosc. doi:10.1007/s00464-018-6587-0.
- Kasotakis G, Lakha A, Sarkar B, et al. Trainee participation is associated with adverse outcomes in emergency general surgery: an analysis of the National Surgical Quality Improvement Program database. Ann Surg. 2014;3:483-490.
- Richard C, Lajeunesse Y, Lussier MT. Therapeutic privilege: between the ethics of lying and the practice of truth. J Med Ethics. 2010;36:353-357.
It is an uncomfortable and unavoidable reality as physicians that for every procedure we learn, there must be a first time we perform it. As with any type of skill, it takes practice to become proficient. The unique challenge in medicine is that the practice involves performing procedures on real patients. We cannot avoid the hands-on nature of the training process; we can, however, approach its ethical challenges mindfully. Herein, I will discuss some of the ethical considerations in providing care as a trainee and identify potential barriers to best practices, particularly as they relate to procedural dermatology.
Tell Patients You Are in Training
In every patient encounter, we must introduce ourselves as a trainee. The principle of right to the truth dictates that we are transparent about our level of training and do not misrepresent ourselves to our patients. A statement released by the American Medical Association (AMA) Council on Ethical and Judicial Affairs asserts that “[p]atients should be informed of the identity and training status of individuals involved in their care.”1
Although straightforward in theory, this mandate is not always simple in practice. With patients unfamiliar with the health care system, it could be more onerous to clearly communicate training status than simply introducing oneself as a resident. A study conducted in the emergency department at Vanderbilt University Hospital (Nashville, Tennessee) found that many patients and their family members (N=430) did not understand the various roles and responsibilities of physicians in the teaching hospital setting. For example, 30% believed an attending physician requires supervision by a resident, and an additional 17% of those surveyed were not sure.2 The AMA requests we “refrain from using terms that may be confusing when describing the training status of the students,”1 which evidently is audience specific. Thus, as with any type of patient education, a thorough introduction may require assessment of understanding.
Disclosure of Experience Level With a Particular Procedure
There is a clear professional expectation that we disclose to patients that we are in training; however, a universal standard does not exist for disclosure of our exact level of experience in a particular procedure. Do we need to tell patients if it is our first time performing a given procedure? What if it is our tenth? Multiple studies have found that patients want specifics. In one study of bariatric surgery patients (N=108), 93% felt that they should always be informed if it was the first time a trainee was performing a particular procedure.3 A study conducted in the emergency department setting (N=202) also found that the majority of patients thought they should be informed if a resident was performing a procedure for the first time, but the distribution differed by procedure (66% for suturing vs 82% for lumbar puncture).4
Despite these findings, this degree of specificity is not always discussed with patients and perhaps does not need to be. LaRosa and Grant-Kels5 analyzed a hypothetical scenario in which a dermatology resident is to perform his first excision under attending supervision and concluded that broad disclosure of training status would suffice in the given scenario, as it would not be necessary to state that it was his first time performing an excision. It is unclear if the same conclusion could be drawn for all procedures and levels of experience. Outcome data would help inform the analysis, but the available data are from other specialties including general surgery, gynecology, and urology. Some studies demonstrate an increased risk of adverse outcomes with trainee involvement in procedures such as bariatric surgery and emergency general surgery, but the data are mixed and may not be generalizable to dermatologic procedures.6-8
The appropriate level of detail to disclose regarding a physician’s experience may need to be assessed on a case-by-case basis, and the principles of informed consent can help. Informed consent requires understanding of the diagnosis, the treatment options including nonintervention, and the risks and benefits of each alternative. In obtaining informed consent, we must disclose “any facts which are necessary to form the basis of an intelligent consent by the patient to the proposed treatment.”9 Providers must determine what aspects of a trainee’s experience level are relevant to the risk-benefit analysis in a given set of circumstances. Surely, there is a large degree of subjectivity in this determination as data are limited, but information deemed relevant must be shared. Information that is inconsequential, on the other hand, may be omitted. It could even be argued that more detailed information, especially if it may cause anxiety, would be detrimental to share. For example, we would not list the chemical name of every preservative in every vaccine we recommend for children if there is no evidence of inflicting harm. If the information has not been shown to have clinical impact or affect safety concerns, the anxiety may be undue.
Withholding Information Can Violate Ethical Principles
We must be careful not to withhold details of our experience level with a particular procedure for the wrong reasons. It would be wrong, for example, to withhold information simply to avoid causing anxiety, which could be seen as an invocation of therapeutic privilege, a controversial practice of withholding important information that poses a psychological threat to the patient. A classic example is the physician who defers disclosure of a terminal diagnosis to preserve hope. Although therapeutic privilege theoretically promotes the principle of beneficence, it violates the principles of autonomy and right to truth and therefore generally is regarded as unethically paternalistic in modern medical ethics.9
Patients Can Refuse Trainee Participation
It also is unethical to withhold information to obtain consent and avoid refusal of our care. Refusal of trainee participation is not uncommon. In the aforementioned study of bariatric surgery patients, 92.4% supported their procedure being performed at a teaching hospital, but only 56% would consent to a resident assisting staff during the procedure. A mere 33% of those patients would consent to a resident primarily performing with staff assisting.3 Although the proportion of patients who refuse certainly depends on the type of procedure among other factors, it is a reality in any teaching environment. The training paradigm in medicine depends on being able to practice procedures with supervision before we are independent providers. If patients refuse our care, our training suffers. However, the AMA maintains that “[p]atients are free to choose from whom they receive treatment,”1 and we must respect this aspect of patient autonomy.
Final Thoughts
When it comes to the performance of procedures, there are a few basic principles to keep in mind to provide ethical care to our patients while we are in training. Although we must accept that a crucial part of learning dermatologic procedures is hands on with real patients, we also need to come prepared having learned what we can through reading and practice with cadavers or skin substitutes. Procedures we execute as residents should be performed with adequate supervision, and as we progress through residency, we should be given increased autonomy and graded responsibility to prepare us for independent practice at graduation. Although it is the responsibility of the attending physician to provide appropriate oversight for the resident’s level of training, we should feel empowered to ask for help and have the humility to know when we need it.
It is an uncomfortable and unavoidable reality as physicians that for every procedure we learn, there must be a first time we perform it. As with any type of skill, it takes practice to become proficient. The unique challenge in medicine is that the practice involves performing procedures on real patients. We cannot avoid the hands-on nature of the training process; we can, however, approach its ethical challenges mindfully. Herein, I will discuss some of the ethical considerations in providing care as a trainee and identify potential barriers to best practices, particularly as they relate to procedural dermatology.
Tell Patients You Are in Training
In every patient encounter, we must introduce ourselves as a trainee. The principle of right to the truth dictates that we are transparent about our level of training and do not misrepresent ourselves to our patients. A statement released by the American Medical Association (AMA) Council on Ethical and Judicial Affairs asserts that “[p]atients should be informed of the identity and training status of individuals involved in their care.”1
Although straightforward in theory, this mandate is not always simple in practice. With patients unfamiliar with the health care system, it could be more onerous to clearly communicate training status than simply introducing oneself as a resident. A study conducted in the emergency department at Vanderbilt University Hospital (Nashville, Tennessee) found that many patients and their family members (N=430) did not understand the various roles and responsibilities of physicians in the teaching hospital setting. For example, 30% believed an attending physician requires supervision by a resident, and an additional 17% of those surveyed were not sure.2 The AMA requests we “refrain from using terms that may be confusing when describing the training status of the students,”1 which evidently is audience specific. Thus, as with any type of patient education, a thorough introduction may require assessment of understanding.
Disclosure of Experience Level With a Particular Procedure
There is a clear professional expectation that we disclose to patients that we are in training; however, a universal standard does not exist for disclosure of our exact level of experience in a particular procedure. Do we need to tell patients if it is our first time performing a given procedure? What if it is our tenth? Multiple studies have found that patients want specifics. In one study of bariatric surgery patients (N=108), 93% felt that they should always be informed if it was the first time a trainee was performing a particular procedure.3 A study conducted in the emergency department setting (N=202) also found that the majority of patients thought they should be informed if a resident was performing a procedure for the first time, but the distribution differed by procedure (66% for suturing vs 82% for lumbar puncture).4
Despite these findings, this degree of specificity is not always discussed with patients and perhaps does not need to be. LaRosa and Grant-Kels5 analyzed a hypothetical scenario in which a dermatology resident is to perform his first excision under attending supervision and concluded that broad disclosure of training status would suffice in the given scenario, as it would not be necessary to state that it was his first time performing an excision. It is unclear if the same conclusion could be drawn for all procedures and levels of experience. Outcome data would help inform the analysis, but the available data are from other specialties including general surgery, gynecology, and urology. Some studies demonstrate an increased risk of adverse outcomes with trainee involvement in procedures such as bariatric surgery and emergency general surgery, but the data are mixed and may not be generalizable to dermatologic procedures.6-8
The appropriate level of detail to disclose regarding a physician’s experience may need to be assessed on a case-by-case basis, and the principles of informed consent can help. Informed consent requires understanding of the diagnosis, the treatment options including nonintervention, and the risks and benefits of each alternative. In obtaining informed consent, we must disclose “any facts which are necessary to form the basis of an intelligent consent by the patient to the proposed treatment.”9 Providers must determine what aspects of a trainee’s experience level are relevant to the risk-benefit analysis in a given set of circumstances. Surely, there is a large degree of subjectivity in this determination as data are limited, but information deemed relevant must be shared. Information that is inconsequential, on the other hand, may be omitted. It could even be argued that more detailed information, especially if it may cause anxiety, would be detrimental to share. For example, we would not list the chemical name of every preservative in every vaccine we recommend for children if there is no evidence of inflicting harm. If the information has not been shown to have clinical impact or affect safety concerns, the anxiety may be undue.
Withholding Information Can Violate Ethical Principles
We must be careful not to withhold details of our experience level with a particular procedure for the wrong reasons. It would be wrong, for example, to withhold information simply to avoid causing anxiety, which could be seen as an invocation of therapeutic privilege, a controversial practice of withholding important information that poses a psychological threat to the patient. A classic example is the physician who defers disclosure of a terminal diagnosis to preserve hope. Although therapeutic privilege theoretically promotes the principle of beneficence, it violates the principles of autonomy and right to truth and therefore generally is regarded as unethically paternalistic in modern medical ethics.9
Patients Can Refuse Trainee Participation
It also is unethical to withhold information to obtain consent and avoid refusal of our care. Refusal of trainee participation is not uncommon. In the aforementioned study of bariatric surgery patients, 92.4% supported their procedure being performed at a teaching hospital, but only 56% would consent to a resident assisting staff during the procedure. A mere 33% of those patients would consent to a resident primarily performing with staff assisting.3 Although the proportion of patients who refuse certainly depends on the type of procedure among other factors, it is a reality in any teaching environment. The training paradigm in medicine depends on being able to practice procedures with supervision before we are independent providers. If patients refuse our care, our training suffers. However, the AMA maintains that “[p]atients are free to choose from whom they receive treatment,”1 and we must respect this aspect of patient autonomy.
Final Thoughts
When it comes to the performance of procedures, there are a few basic principles to keep in mind to provide ethical care to our patients while we are in training. Although we must accept that a crucial part of learning dermatologic procedures is hands on with real patients, we also need to come prepared having learned what we can through reading and practice with cadavers or skin substitutes. Procedures we execute as residents should be performed with adequate supervision, and as we progress through residency, we should be given increased autonomy and graded responsibility to prepare us for independent practice at graduation. Although it is the responsibility of the attending physician to provide appropriate oversight for the resident’s level of training, we should feel empowered to ask for help and have the humility to know when we need it.
- Medical student involvement in patient care: report of the council on ethical and judicial affairs. Virtual Mentor. 2001;3. doi:10.1001/virtualmentor.2001.3.3.code1-0103.
- Santen S, Hemphill RR, Prough E, et al. Do patients understand their physician’s level of training? a survey of emergency department patients. Acad Med. 2004;79:139-143.
- McClellan JM, Nelson D, Porta CR, et al. Bariatric surgery patient perceptions and willingness to consent to resident participation. Surg Obes Relat Dis. 2016;12:1065-1071.
- Santen SA, Hemphill RR, McDonald MF, et al. Patients’ willingness to allow residents to learn to practice medical procedures. Acad Med. 2004;79:144-147.
- LaRosa C, Grant-Kels JM. See one, do one, teach one: the ethical dilemma of residents performing their first procedure on patients. J Am Acad Dermatol. 2016;75:845-848.
- Can MF. The trainee effect on early postoperative surgical outcomes: reflects the effect of resident involvement or hospital capacity to overcome complications? J Invest Surg. 2017;31:67-68.
- Goldberg I, Yang J, Park J, et al. Surgical trainee impact on bariatric surgery safety [published online November 13, 2018]. Surg Endosc. doi:10.1007/s00464-018-6587-0.
- Kasotakis G, Lakha A, Sarkar B, et al. Trainee participation is associated with adverse outcomes in emergency general surgery: an analysis of the National Surgical Quality Improvement Program database. Ann Surg. 2014;3:483-490.
- Richard C, Lajeunesse Y, Lussier MT. Therapeutic privilege: between the ethics of lying and the practice of truth. J Med Ethics. 2010;36:353-357.
- Medical student involvement in patient care: report of the council on ethical and judicial affairs. Virtual Mentor. 2001;3. doi:10.1001/virtualmentor.2001.3.3.code1-0103.
- Santen S, Hemphill RR, Prough E, et al. Do patients understand their physician’s level of training? a survey of emergency department patients. Acad Med. 2004;79:139-143.
- McClellan JM, Nelson D, Porta CR, et al. Bariatric surgery patient perceptions and willingness to consent to resident participation. Surg Obes Relat Dis. 2016;12:1065-1071.
- Santen SA, Hemphill RR, McDonald MF, et al. Patients’ willingness to allow residents to learn to practice medical procedures. Acad Med. 2004;79:144-147.
- LaRosa C, Grant-Kels JM. See one, do one, teach one: the ethical dilemma of residents performing their first procedure on patients. J Am Acad Dermatol. 2016;75:845-848.
- Can MF. The trainee effect on early postoperative surgical outcomes: reflects the effect of resident involvement or hospital capacity to overcome complications? J Invest Surg. 2017;31:67-68.
- Goldberg I, Yang J, Park J, et al. Surgical trainee impact on bariatric surgery safety [published online November 13, 2018]. Surg Endosc. doi:10.1007/s00464-018-6587-0.
- Kasotakis G, Lakha A, Sarkar B, et al. Trainee participation is associated with adverse outcomes in emergency general surgery: an analysis of the National Surgical Quality Improvement Program database. Ann Surg. 2014;3:483-490.
- Richard C, Lajeunesse Y, Lussier MT. Therapeutic privilege: between the ethics of lying and the practice of truth. J Med Ethics. 2010;36:353-357.
Resident Pearl
- As residents, we must gain experience performing procedures on real patients to enter independent practice as proficient dermatologists. It is important to be mindful of the ethical challenges inherent to the hands-on training process and to understand the ethical principles that guide best practices.
Fewer antibiotics prescribed with PCR than conventional stool testing
SAN DIEGO – However, antibiotics were still prescribed for more than one in three patients tested by any method.
“A positive test by any modality did result in decreased utilization of endoscopy, radiology, and antibiotic prescribing, but this effect appeared to be much greater for the GI PCR assay,” said Jordan Axelrad, MD, speaking at the annual Digestive Disease Week.
“Overall, patients who received GI PCR were 12% less likely to undergo endoscopy, 7% less likely to undergo abdominal radiography, and 11% less likely to be prescribed any antibiotic,” compared with patients who were tested by conventional stool culture, said Dr. Axelrad, a gastroenterologist at New York University.
In a cross-sectional study, Dr. Axelrad and his coauthors looked at patients who underwent stool testing for the 26 months before (n = 5,986) and after (n = 9,402) March 2015, when Dr. Axelrad’s home institution switched from conventional stool culture to the GI PCR panel. For the earlier time period, the investigators included patients who received stool culture both with and without an ova and parasites exam, as well as those who underwent enzyme-linked immunosorbent assay viral testing for rotavirus and adenovirus.
Patient demographic data were included as study variables; additionally, the study tracked utilization of endoscopy, abdominal, or other radiology studies, and ED visits for 30 days after testing. They also included any antibiotic prescribing within the 14 days post testing.
Roughly one-third of patients were tested as outpatients, 1 in 10 in the ED, and the remainder as inpatients. Patient age was a mean 46.7 years for the culture group, and 45.5 years for the GI PCR group.
The multiplex PCR test used in the study tested for 12 gastrointestinal pathogenic bacteria, 4 parasites, and 5 viruses.
As expected, PCR testing yielded a higher positive test rate than conventional stool testing, even when EIA tests were included (29.2% vs. 4.1%). In the 2,746 patients with a positive GI PCR test, a total of 3,804 pathogens were identified. Adenovirus accounted for 39% of these positive results. Positive bacterial results were seen in about 65.0% of the positive subgroup, with Escherichia coli subtypes seen in 51.7% of the positive tests.
Overall, positive results for viruses, bacteria, and multiple pathogens were more likely with GI PCR testing, compared with conventional testing (P = .001 for all). Parasites accounted for only 8.2% of the positive PCR test results, but this was significantly more than the 3.7% seen with conventional testing (P = .011).
At the 14-day mark post testing, “Patients who underwent a GI panel were less likely to be prescribed any antibiotic. But overall, antibiotics were fairly common in both groups,” said Dr. Axelrad, noting that 41% of patients who underwent stool culture received an antibiotic by 14 days, compared with 36% for patients who underwent a GI PCR panel (P = .001).
By the end of 30 days, most patients in each group had not received an endoscopic procedure, with significantly more procedure-free patients in the PCR group (91.6% vs. 90.4%; P = .008).
Against a backdrop of slightly higher overall radiology utilization in the PCR group – potentially attributable to practice trends over time – abdominal radiology was less likely for these patients than for the culture group (11.4% vs. 12.8%; P = .011).
The 30-day ED visit rate was low and similar between groups (11.4% for PCR vs. 12.8% for culture; P = .116).
The much quicker turnaround for the GI PCR panel didn’t translate into a shorter length of stay, though: Inpatient length of stay was a median 5 days in both groups.
“We feel that the outcomes that we noted were likely due to the increased sensitivity and specificity” of the PCR-based testing, said Dr. Axelrad. “Obviously, if you have more pathogen-positive findings, you may be less likely to order extensive testing. And if you’ve identified something like norovirus, you may feel reassured, and not order further testing.”
Dr. Axelrad pointed out that his institution’s overall PCR positivity rates were lower than the 70% rates some other studies have reported. “We feel that, given our large sample size, our results may more accurately reflect clinical practice, and perhaps that lower positivity rate may reflect increased use of this test in an inpatient setting,” he said. “We’re looking at that.”
Study limitations included the retrospective nature of the study. “Also, as we all know, PCR testing fails to discriminate between active infection and asymptomatic colonization,” raising questions about whether a positive PCR test really indicates true infection, noted Dr. Axelrad.
“Coupled with a high-sensitivity rapid turnaround, there’s the potential to reduce costs, but the cost-effectiveness of these assays has not been fully determined. There are several studies looking at this,” with results still to come, he said.
The notable reduction in antibiotic prescribing for those patients who received PCR-based testing means that GI PCR panels could be a useful tool to promote antibiotic stewardship, though Dr. Axelrad also noted that “antibiotics were still used in about a third of all patients.”
Dr. Axelrad reported no outside sources of funding. He has performed consulting services for and received research funding from BioFire, which manufactured the GI PCR assay used in the study, but BioFire did not fund this research.
SOURCE: Axelrad J et al. DDW 2019, Presentation 978.
SAN DIEGO – However, antibiotics were still prescribed for more than one in three patients tested by any method.
“A positive test by any modality did result in decreased utilization of endoscopy, radiology, and antibiotic prescribing, but this effect appeared to be much greater for the GI PCR assay,” said Jordan Axelrad, MD, speaking at the annual Digestive Disease Week.
“Overall, patients who received GI PCR were 12% less likely to undergo endoscopy, 7% less likely to undergo abdominal radiography, and 11% less likely to be prescribed any antibiotic,” compared with patients who were tested by conventional stool culture, said Dr. Axelrad, a gastroenterologist at New York University.
In a cross-sectional study, Dr. Axelrad and his coauthors looked at patients who underwent stool testing for the 26 months before (n = 5,986) and after (n = 9,402) March 2015, when Dr. Axelrad’s home institution switched from conventional stool culture to the GI PCR panel. For the earlier time period, the investigators included patients who received stool culture both with and without an ova and parasites exam, as well as those who underwent enzyme-linked immunosorbent assay viral testing for rotavirus and adenovirus.
Patient demographic data were included as study variables; additionally, the study tracked utilization of endoscopy, abdominal, or other radiology studies, and ED visits for 30 days after testing. They also included any antibiotic prescribing within the 14 days post testing.
Roughly one-third of patients were tested as outpatients, 1 in 10 in the ED, and the remainder as inpatients. Patient age was a mean 46.7 years for the culture group, and 45.5 years for the GI PCR group.
The multiplex PCR test used in the study tested for 12 gastrointestinal pathogenic bacteria, 4 parasites, and 5 viruses.
As expected, PCR testing yielded a higher positive test rate than conventional stool testing, even when EIA tests were included (29.2% vs. 4.1%). In the 2,746 patients with a positive GI PCR test, a total of 3,804 pathogens were identified. Adenovirus accounted for 39% of these positive results. Positive bacterial results were seen in about 65.0% of the positive subgroup, with Escherichia coli subtypes seen in 51.7% of the positive tests.
Overall, positive results for viruses, bacteria, and multiple pathogens were more likely with GI PCR testing, compared with conventional testing (P = .001 for all). Parasites accounted for only 8.2% of the positive PCR test results, but this was significantly more than the 3.7% seen with conventional testing (P = .011).
At the 14-day mark post testing, “Patients who underwent a GI panel were less likely to be prescribed any antibiotic. But overall, antibiotics were fairly common in both groups,” said Dr. Axelrad, noting that 41% of patients who underwent stool culture received an antibiotic by 14 days, compared with 36% for patients who underwent a GI PCR panel (P = .001).
By the end of 30 days, most patients in each group had not received an endoscopic procedure, with significantly more procedure-free patients in the PCR group (91.6% vs. 90.4%; P = .008).
Against a backdrop of slightly higher overall radiology utilization in the PCR group – potentially attributable to practice trends over time – abdominal radiology was less likely for these patients than for the culture group (11.4% vs. 12.8%; P = .011).
The 30-day ED visit rate was low and similar between groups (11.4% for PCR vs. 12.8% for culture; P = .116).
The much quicker turnaround for the GI PCR panel didn’t translate into a shorter length of stay, though: Inpatient length of stay was a median 5 days in both groups.
“We feel that the outcomes that we noted were likely due to the increased sensitivity and specificity” of the PCR-based testing, said Dr. Axelrad. “Obviously, if you have more pathogen-positive findings, you may be less likely to order extensive testing. And if you’ve identified something like norovirus, you may feel reassured, and not order further testing.”
Dr. Axelrad pointed out that his institution’s overall PCR positivity rates were lower than the 70% rates some other studies have reported. “We feel that, given our large sample size, our results may more accurately reflect clinical practice, and perhaps that lower positivity rate may reflect increased use of this test in an inpatient setting,” he said. “We’re looking at that.”
Study limitations included the retrospective nature of the study. “Also, as we all know, PCR testing fails to discriminate between active infection and asymptomatic colonization,” raising questions about whether a positive PCR test really indicates true infection, noted Dr. Axelrad.
“Coupled with a high-sensitivity rapid turnaround, there’s the potential to reduce costs, but the cost-effectiveness of these assays has not been fully determined. There are several studies looking at this,” with results still to come, he said.
The notable reduction in antibiotic prescribing for those patients who received PCR-based testing means that GI PCR panels could be a useful tool to promote antibiotic stewardship, though Dr. Axelrad also noted that “antibiotics were still used in about a third of all patients.”
Dr. Axelrad reported no outside sources of funding. He has performed consulting services for and received research funding from BioFire, which manufactured the GI PCR assay used in the study, but BioFire did not fund this research.
SOURCE: Axelrad J et al. DDW 2019, Presentation 978.
SAN DIEGO – However, antibiotics were still prescribed for more than one in three patients tested by any method.
“A positive test by any modality did result in decreased utilization of endoscopy, radiology, and antibiotic prescribing, but this effect appeared to be much greater for the GI PCR assay,” said Jordan Axelrad, MD, speaking at the annual Digestive Disease Week.
“Overall, patients who received GI PCR were 12% less likely to undergo endoscopy, 7% less likely to undergo abdominal radiography, and 11% less likely to be prescribed any antibiotic,” compared with patients who were tested by conventional stool culture, said Dr. Axelrad, a gastroenterologist at New York University.
In a cross-sectional study, Dr. Axelrad and his coauthors looked at patients who underwent stool testing for the 26 months before (n = 5,986) and after (n = 9,402) March 2015, when Dr. Axelrad’s home institution switched from conventional stool culture to the GI PCR panel. For the earlier time period, the investigators included patients who received stool culture both with and without an ova and parasites exam, as well as those who underwent enzyme-linked immunosorbent assay viral testing for rotavirus and adenovirus.
Patient demographic data were included as study variables; additionally, the study tracked utilization of endoscopy, abdominal, or other radiology studies, and ED visits for 30 days after testing. They also included any antibiotic prescribing within the 14 days post testing.
Roughly one-third of patients were tested as outpatients, 1 in 10 in the ED, and the remainder as inpatients. Patient age was a mean 46.7 years for the culture group, and 45.5 years for the GI PCR group.
The multiplex PCR test used in the study tested for 12 gastrointestinal pathogenic bacteria, 4 parasites, and 5 viruses.
As expected, PCR testing yielded a higher positive test rate than conventional stool testing, even when EIA tests were included (29.2% vs. 4.1%). In the 2,746 patients with a positive GI PCR test, a total of 3,804 pathogens were identified. Adenovirus accounted for 39% of these positive results. Positive bacterial results were seen in about 65.0% of the positive subgroup, with Escherichia coli subtypes seen in 51.7% of the positive tests.
Overall, positive results for viruses, bacteria, and multiple pathogens were more likely with GI PCR testing, compared with conventional testing (P = .001 for all). Parasites accounted for only 8.2% of the positive PCR test results, but this was significantly more than the 3.7% seen with conventional testing (P = .011).
At the 14-day mark post testing, “Patients who underwent a GI panel were less likely to be prescribed any antibiotic. But overall, antibiotics were fairly common in both groups,” said Dr. Axelrad, noting that 41% of patients who underwent stool culture received an antibiotic by 14 days, compared with 36% for patients who underwent a GI PCR panel (P = .001).
By the end of 30 days, most patients in each group had not received an endoscopic procedure, with significantly more procedure-free patients in the PCR group (91.6% vs. 90.4%; P = .008).
Against a backdrop of slightly higher overall radiology utilization in the PCR group – potentially attributable to practice trends over time – abdominal radiology was less likely for these patients than for the culture group (11.4% vs. 12.8%; P = .011).
The 30-day ED visit rate was low and similar between groups (11.4% for PCR vs. 12.8% for culture; P = .116).
The much quicker turnaround for the GI PCR panel didn’t translate into a shorter length of stay, though: Inpatient length of stay was a median 5 days in both groups.
“We feel that the outcomes that we noted were likely due to the increased sensitivity and specificity” of the PCR-based testing, said Dr. Axelrad. “Obviously, if you have more pathogen-positive findings, you may be less likely to order extensive testing. And if you’ve identified something like norovirus, you may feel reassured, and not order further testing.”
Dr. Axelrad pointed out that his institution’s overall PCR positivity rates were lower than the 70% rates some other studies have reported. “We feel that, given our large sample size, our results may more accurately reflect clinical practice, and perhaps that lower positivity rate may reflect increased use of this test in an inpatient setting,” he said. “We’re looking at that.”
Study limitations included the retrospective nature of the study. “Also, as we all know, PCR testing fails to discriminate between active infection and asymptomatic colonization,” raising questions about whether a positive PCR test really indicates true infection, noted Dr. Axelrad.
“Coupled with a high-sensitivity rapid turnaround, there’s the potential to reduce costs, but the cost-effectiveness of these assays has not been fully determined. There are several studies looking at this,” with results still to come, he said.
The notable reduction in antibiotic prescribing for those patients who received PCR-based testing means that GI PCR panels could be a useful tool to promote antibiotic stewardship, though Dr. Axelrad also noted that “antibiotics were still used in about a third of all patients.”
Dr. Axelrad reported no outside sources of funding. He has performed consulting services for and received research funding from BioFire, which manufactured the GI PCR assay used in the study, but BioFire did not fund this research.
SOURCE: Axelrad J et al. DDW 2019, Presentation 978.
REPORTING FROM DDW 2019
USPSTF recommends PrEP combo for adults at high risk of HIV infection
Pre-exposure prophylaxis (PrEP) plus effective antiretroviral therapy should be offered to people at high risk of HIV acquisition, according to a new recommendation from the U.S. Preventive Services Task Force (USPSTF).
“The USPSTF concludes with high certainty that the net benefit of the use of PrEP to reduce the risk of acquisition of HIV infection in persons at high risk of HIV infection is substantial,” wrote first author Douglas K. Owens, MD, of Stanford (Calif.) University and fellow members of the USPSTF. The recommendation was published in JAMA.
In various at-risk groups – including men who have sex with men, people at risk through heterosexual contact, and people who inject drugs – the USPSTF recommends a Food and Drug Adminstration–approved, once-daily oral treatment with combined tenofovir disoproxil fumarate and emtricitabine.
This recommendation was developed after a systematic review of PrEP’s effects on HIV, adherence to the treatment, and accuracy in identifying potential treatment candidates. “The findings of this review are generally consistent with those from other recent meta-analyses that found PrEP to be effective at reducing risk of HIV infection and found greater effectiveness in trials reporting higher adherence,” wrote Roger Chou, MD, of Oregon Health & Science University in Portland and coauthors. Their study was also published in JAMA.
To comprehensively assess PrEP and thus inform the USPSTF’s HIV prevention recommendations, the researchers reviewed criteria-meeting studies on oral PrEP with tenofovir disoproxil fumarate/emtricitabine or tenofovir disoproxil fumarate monotherapy; on the diagnostic accuracy of instruments to predict HIV infection; and on PrEP adherence. The final analysis included 14 randomized clinical trials, 8 observational studies, and 7 studies of diagnostic accuracy.
In 11 of the trials, PrEP was associated with reduced risk of HIV infection versus placebo or no PrEP (relative risk, 0.46; 95% confidence interval, 0.33-0.66). In 6 trials with adherence 70% or greater, the relative risk was 0.27 (95% CI, 0.19-0.39). In 7 studies on risk assessment tools for HIV infection, the instruments had moderate discrimination, though several of the studies had methodological shortcomings. As for serious adverse events, an analysis of 12 trials found no significant difference between PrEP and placebo (RR, 0.93; 95% CI, 0.77-1.12).
Dr. Chou and coauthors noted their study’s limitations, including analyzing English-language articles only and the random-effects model used to pool studies potentially returning narrow CIs. They did note, however, that the “analyses were repeated using the profile likelihood method,” which produced similar findings.
All members of the USPSTF receive travel reimbursement and an honorarium for participating in meetings. The study was funded by the Department of Health and Human Services. One of the authors reported receiving grants from the National Institutes of Health/National Institute on Drug Abuse and serving as principal investigator of NIH-funded clinical trials that received donated drugs from two pharmaceutical companies. No other conflicts of interest were reported.
SOURCE: Owens DK et al. JAMA. 2019 Jun 11. doi: 10.1001/jama.2019.6390; Chou R et al. JAMA. 2019 Jun 11. doi: 10.1001/jama.2019.2591.
To end HIV, guidelines like this one that reflect and promote advances in treatment are needed, according to Hyman Scott, MD, MPH, of the San Francisco Department of Public Health and Paul A. Volberding, MD, of the University of California, San Francisco.
With less than 10% of individuals with an indication for PrEP currently receiving the medication, it is now time to support policies aimed at broadening the access of PrEP to people at risk, the coauthors wrote. They noted that recent USPSTF guidelines show that evidence and policy in HIV medicine has matured not only in the United States but across the globe.
That said, sometimes the simplest solutions are also the best. Though the systematic review from Roger Chou, MD, and associates notes the necessity and importance of adherence, if a clinician thinks that a candidate for PrEP might be nonadherent, that clinicians should not withhold the medication, they wrote. Averting new HIV infections is the goal, and fully endorsing treatments like PrEP is an important step in that direction.*
These comments are adapted from an accompanying editorial (JAMA. 2019 Jun 11. doi: 10.1001/jama.2019.2590). Dr. Volberding reported serving on a data and safety monitoring board for Merck.
*This article was updated on 6/11/2019.
To end HIV, guidelines like this one that reflect and promote advances in treatment are needed, according to Hyman Scott, MD, MPH, of the San Francisco Department of Public Health and Paul A. Volberding, MD, of the University of California, San Francisco.
With less than 10% of individuals with an indication for PrEP currently receiving the medication, it is now time to support policies aimed at broadening the access of PrEP to people at risk, the coauthors wrote. They noted that recent USPSTF guidelines show that evidence and policy in HIV medicine has matured not only in the United States but across the globe.
That said, sometimes the simplest solutions are also the best. Though the systematic review from Roger Chou, MD, and associates notes the necessity and importance of adherence, if a clinician thinks that a candidate for PrEP might be nonadherent, that clinicians should not withhold the medication, they wrote. Averting new HIV infections is the goal, and fully endorsing treatments like PrEP is an important step in that direction.*
These comments are adapted from an accompanying editorial (JAMA. 2019 Jun 11. doi: 10.1001/jama.2019.2590). Dr. Volberding reported serving on a data and safety monitoring board for Merck.
*This article was updated on 6/11/2019.
To end HIV, guidelines like this one that reflect and promote advances in treatment are needed, according to Hyman Scott, MD, MPH, of the San Francisco Department of Public Health and Paul A. Volberding, MD, of the University of California, San Francisco.
With less than 10% of individuals with an indication for PrEP currently receiving the medication, it is now time to support policies aimed at broadening the access of PrEP to people at risk, the coauthors wrote. They noted that recent USPSTF guidelines show that evidence and policy in HIV medicine has matured not only in the United States but across the globe.
That said, sometimes the simplest solutions are also the best. Though the systematic review from Roger Chou, MD, and associates notes the necessity and importance of adherence, if a clinician thinks that a candidate for PrEP might be nonadherent, that clinicians should not withhold the medication, they wrote. Averting new HIV infections is the goal, and fully endorsing treatments like PrEP is an important step in that direction.*
These comments are adapted from an accompanying editorial (JAMA. 2019 Jun 11. doi: 10.1001/jama.2019.2590). Dr. Volberding reported serving on a data and safety monitoring board for Merck.
*This article was updated on 6/11/2019.
Pre-exposure prophylaxis (PrEP) plus effective antiretroviral therapy should be offered to people at high risk of HIV acquisition, according to a new recommendation from the U.S. Preventive Services Task Force (USPSTF).
“The USPSTF concludes with high certainty that the net benefit of the use of PrEP to reduce the risk of acquisition of HIV infection in persons at high risk of HIV infection is substantial,” wrote first author Douglas K. Owens, MD, of Stanford (Calif.) University and fellow members of the USPSTF. The recommendation was published in JAMA.
In various at-risk groups – including men who have sex with men, people at risk through heterosexual contact, and people who inject drugs – the USPSTF recommends a Food and Drug Adminstration–approved, once-daily oral treatment with combined tenofovir disoproxil fumarate and emtricitabine.
This recommendation was developed after a systematic review of PrEP’s effects on HIV, adherence to the treatment, and accuracy in identifying potential treatment candidates. “The findings of this review are generally consistent with those from other recent meta-analyses that found PrEP to be effective at reducing risk of HIV infection and found greater effectiveness in trials reporting higher adherence,” wrote Roger Chou, MD, of Oregon Health & Science University in Portland and coauthors. Their study was also published in JAMA.
To comprehensively assess PrEP and thus inform the USPSTF’s HIV prevention recommendations, the researchers reviewed criteria-meeting studies on oral PrEP with tenofovir disoproxil fumarate/emtricitabine or tenofovir disoproxil fumarate monotherapy; on the diagnostic accuracy of instruments to predict HIV infection; and on PrEP adherence. The final analysis included 14 randomized clinical trials, 8 observational studies, and 7 studies of diagnostic accuracy.
In 11 of the trials, PrEP was associated with reduced risk of HIV infection versus placebo or no PrEP (relative risk, 0.46; 95% confidence interval, 0.33-0.66). In 6 trials with adherence 70% or greater, the relative risk was 0.27 (95% CI, 0.19-0.39). In 7 studies on risk assessment tools for HIV infection, the instruments had moderate discrimination, though several of the studies had methodological shortcomings. As for serious adverse events, an analysis of 12 trials found no significant difference between PrEP and placebo (RR, 0.93; 95% CI, 0.77-1.12).
Dr. Chou and coauthors noted their study’s limitations, including analyzing English-language articles only and the random-effects model used to pool studies potentially returning narrow CIs. They did note, however, that the “analyses were repeated using the profile likelihood method,” which produced similar findings.
All members of the USPSTF receive travel reimbursement and an honorarium for participating in meetings. The study was funded by the Department of Health and Human Services. One of the authors reported receiving grants from the National Institutes of Health/National Institute on Drug Abuse and serving as principal investigator of NIH-funded clinical trials that received donated drugs from two pharmaceutical companies. No other conflicts of interest were reported.
SOURCE: Owens DK et al. JAMA. 2019 Jun 11. doi: 10.1001/jama.2019.6390; Chou R et al. JAMA. 2019 Jun 11. doi: 10.1001/jama.2019.2591.
Pre-exposure prophylaxis (PrEP) plus effective antiretroviral therapy should be offered to people at high risk of HIV acquisition, according to a new recommendation from the U.S. Preventive Services Task Force (USPSTF).
“The USPSTF concludes with high certainty that the net benefit of the use of PrEP to reduce the risk of acquisition of HIV infection in persons at high risk of HIV infection is substantial,” wrote first author Douglas K. Owens, MD, of Stanford (Calif.) University and fellow members of the USPSTF. The recommendation was published in JAMA.
In various at-risk groups – including men who have sex with men, people at risk through heterosexual contact, and people who inject drugs – the USPSTF recommends a Food and Drug Adminstration–approved, once-daily oral treatment with combined tenofovir disoproxil fumarate and emtricitabine.
This recommendation was developed after a systematic review of PrEP’s effects on HIV, adherence to the treatment, and accuracy in identifying potential treatment candidates. “The findings of this review are generally consistent with those from other recent meta-analyses that found PrEP to be effective at reducing risk of HIV infection and found greater effectiveness in trials reporting higher adherence,” wrote Roger Chou, MD, of Oregon Health & Science University in Portland and coauthors. Their study was also published in JAMA.
To comprehensively assess PrEP and thus inform the USPSTF’s HIV prevention recommendations, the researchers reviewed criteria-meeting studies on oral PrEP with tenofovir disoproxil fumarate/emtricitabine or tenofovir disoproxil fumarate monotherapy; on the diagnostic accuracy of instruments to predict HIV infection; and on PrEP adherence. The final analysis included 14 randomized clinical trials, 8 observational studies, and 7 studies of diagnostic accuracy.
In 11 of the trials, PrEP was associated with reduced risk of HIV infection versus placebo or no PrEP (relative risk, 0.46; 95% confidence interval, 0.33-0.66). In 6 trials with adherence 70% or greater, the relative risk was 0.27 (95% CI, 0.19-0.39). In 7 studies on risk assessment tools for HIV infection, the instruments had moderate discrimination, though several of the studies had methodological shortcomings. As for serious adverse events, an analysis of 12 trials found no significant difference between PrEP and placebo (RR, 0.93; 95% CI, 0.77-1.12).
Dr. Chou and coauthors noted their study’s limitations, including analyzing English-language articles only and the random-effects model used to pool studies potentially returning narrow CIs. They did note, however, that the “analyses were repeated using the profile likelihood method,” which produced similar findings.
All members of the USPSTF receive travel reimbursement and an honorarium for participating in meetings. The study was funded by the Department of Health and Human Services. One of the authors reported receiving grants from the National Institutes of Health/National Institute on Drug Abuse and serving as principal investigator of NIH-funded clinical trials that received donated drugs from two pharmaceutical companies. No other conflicts of interest were reported.
SOURCE: Owens DK et al. JAMA. 2019 Jun 11. doi: 10.1001/jama.2019.6390; Chou R et al. JAMA. 2019 Jun 11. doi: 10.1001/jama.2019.2591.
FROM JAMA
Early TIPS shows superiority to standard care for advanced cirrhosis with acute variceal bleeding
Early TIPS “should therefore be preferred to the current standard of care,” reported lead author Yong Lv, MD, of the Fourth Military Medical University in Xi’an, China, and colleagues, referring to standard pharmaceutical and endoscopic therapy.
“[The current standard] approach has improved patient outcomes,” the investigators wrote in the Lancet Gastroenterology & Hepatology. “However, up to 10%-20% of patients still experience treatment failure, requiring further intensive management. In such patients, [TIPS] is successful in achieving hemostasis in 90%-100% of patients. However, 6-week mortality remains high [35%-55%]. This is probably because the severity of the underlying liver disease has worsened and additional organ dysfunction may have occurred after several failed endoscopic therapy attempts.”
Previous studies have explored earlier intervention with TIPS; however, according to the investigators, these trials were inconclusive for various reasons. For example, uncovered stents and an out-of-date control therapy were employed in a trial by Monescillo et al., while a study by Garcia-Pagan et al. lacked a primary survival endpoint and has been criticized for selection bias. “Thus, whether early TIPS confers a survival benefit in a broader population remains to be assessed,” the investigators wrote.
To this end, the investigators screened 373 patients with advanced cirrhosis (Child-Pugh class B or C) and acute variceal bleeding. Of these, 132 were eligible for inclusion based on age, disease severity, willingness to participate, comorbidities, and other factors. Patients were randomized 2:1 to receive either early TIPS or standard therapy. Within 12 hours of hospital admission for the initial bleeding episode, all patients received vasoactive drugs or endoscopic band ligation and prophylactic antibiotics. Control patients continued vasoactive drugs for up to 5 days, followed by propranolol, which was titrated to reduce resting heart rate by 25% but not less than 55 beats per minute. Elective endoscopic band ligation was performed within 1-2 weeks of initial endoscopic treatment, then approximately every 2 weeks until variceal eradication, and additionally if varices reappeared. TIPS was allowed as rescue therapy. In contrast, patients in the TIPS group underwent the procedure with conscious sedation and local anesthesia within 72 hours of diagnostic endoscopy, followed by approximately 1 week of antibiotics and vasoactive drugs. TIPS revision with angioplasty or another stent placement was performed in the event of shunt dysfunction or reemergence of portal hypertensive complications. The final dataset contained 127 patients, as 3 were excluded after randomization because of exclusionary diagnoses, 1 withdrew consent, and 1 died before TIPS placement.
The primary endpoint was transplantation-free survival. The secondary endpoints were new or worsening ascites based on ultrasound score or sustained ascites necessitating paracentesis, failure to control bleeding or rebleeding, overt hepatic encephalopathy, other complications of portal hypertension, and adverse events.
After a median follow-up of 24 months, data analysis showed a survival benefit associated with early TIPS based on multiple measures. Out of 84 patients in the TIPS group, 15 (18%) died during follow-up, compared with 15 (33%) in the control group. Actuarial transplantation-free survival was also better with TIPS instead of standard therapy at 6 weeks (99% vs. 84%), 1 year (86% vs. 73%), and 2 years (79% vs. 64%). The hazard ratio for transplantation-free survival was 0.50 in favor of TIPS (P = .04). These survival advantages were maintained regardless of hepatitis B virus status or Child-Pugh/Model for End-Stage Liver Disease score.
Similarly to transplantation-free survival, patients treated with TIPS were more likely to be free of uncontrolled bleeding or rebleeding at 1 year (89% vs. 66%) and 2 years (86% vs. 57%). The associated hazard ratio for this outcome favored early TIPS (HR, 0.26; P less than .0001), and univariate and multivariate analysis confirmed an independent protective role. In further support of superiority over standard therapy, patients treated with TIPS were more likely than those in the control group to be free of new or worsening ascites at 1 year (89% vs. 57%) and 2 years (81% vs. 54%).
No significant intergroup differences were found for rates of overt hepatic encephalopathy, hepatic hydrothorax, hepatorenal syndrome, spontaneous bacterial peritonitis, hepatocellular carcinoma, serious adverse events, or nonserious adverse events. At 1 and 3 months, patients in the TIPS group had a slight increase of median bilirubin concentrations and median international normalized ratio; however, these values normalized after 6 months. A similar temporal pattern was observed in early TIPS patients with regard to median Model for End-Stage Liver Disease score.
“[The transplantation-free survival benefit of early TIPS] was probably related to better control of factors contributing to death, such as failure to control bleeding or rebleeding or new or worsening ascites, without increasing the frequency and severity of overt hepatic encephalopathy and other adverse events,” the investigators concluded. “This study provides direct evidence and greater confidence in the recommendations of current guidelines that early TIPS should be performed in high-risk patients without contraindications.
“Future studies addressing whether early TIPS can be equally recommended in Child-Pugh B and C patients are warranted,” the investigators added.
The study was funded by the National Key Technology R&D Program, Boost Program of Xijing Hospital, Optimized Overall Project of Shaanxi Province, and National Natural Science Foundation of China. The investigators reported no conflicts of interest.
SOURCE: Lv Y et al. Lancet Gastroenterol Hepatol. 2019 May 29. doi: 10.1016/S2468-1253(19)30090-1.
Although the paper published by Lv et al. supports early transjugular intrahepatic portosystemic shunt (TIPS) for some patients with cirrhosis and variceal bleeding, Dominique Thabut, MD, and Marika Rudler, MD, pointed out that this conclusion cannot be applied to all patients.
“First ... the landscape of cirrhosis with acute variceal bleeding in China is different from that in Europe,” they wrote. “Second, the authors chose to include patients with Child-Pugh B disease without active bleeding at endoscopy [the largest group of patients in this trial]; such patients are not often seen in Europe. Last, a survival benefit was only observed when the Child-Pugh B and Child-Pugh C patients were combined, with and without active bleeding. Hence, this study does not permit conclusions to be made for patients with Child-Pugh B disease.”
“Overall, the authors should be congratulated for tackling the much debated issue of preemptive TIPS,” Dr. Thabut and Dr. Rudler wrote. “There is now no doubt about the benefit of preemptive TIPS in patients with Child-Pugh C disease. The beneficial effects of preemptive TIPS on ascites should push us to consider this approach in all patients, in the absence of contraindication.”
Dr. Tabut and Dr. Rudler, of the Institute of Cardiometabolism and Nutrition, Paris, made their remarks in an accompanying editorial (Lancet Gastroenterol Hepatol. 2019 May 29. doi: 10.1016/S2468-1253[19]30172-4). They reported no conflicts of interest.
Although the paper published by Lv et al. supports early transjugular intrahepatic portosystemic shunt (TIPS) for some patients with cirrhosis and variceal bleeding, Dominique Thabut, MD, and Marika Rudler, MD, pointed out that this conclusion cannot be applied to all patients.
“First ... the landscape of cirrhosis with acute variceal bleeding in China is different from that in Europe,” they wrote. “Second, the authors chose to include patients with Child-Pugh B disease without active bleeding at endoscopy [the largest group of patients in this trial]; such patients are not often seen in Europe. Last, a survival benefit was only observed when the Child-Pugh B and Child-Pugh C patients were combined, with and without active bleeding. Hence, this study does not permit conclusions to be made for patients with Child-Pugh B disease.”
“Overall, the authors should be congratulated for tackling the much debated issue of preemptive TIPS,” Dr. Thabut and Dr. Rudler wrote. “There is now no doubt about the benefit of preemptive TIPS in patients with Child-Pugh C disease. The beneficial effects of preemptive TIPS on ascites should push us to consider this approach in all patients, in the absence of contraindication.”
Dr. Tabut and Dr. Rudler, of the Institute of Cardiometabolism and Nutrition, Paris, made their remarks in an accompanying editorial (Lancet Gastroenterol Hepatol. 2019 May 29. doi: 10.1016/S2468-1253[19]30172-4). They reported no conflicts of interest.
Although the paper published by Lv et al. supports early transjugular intrahepatic portosystemic shunt (TIPS) for some patients with cirrhosis and variceal bleeding, Dominique Thabut, MD, and Marika Rudler, MD, pointed out that this conclusion cannot be applied to all patients.
“First ... the landscape of cirrhosis with acute variceal bleeding in China is different from that in Europe,” they wrote. “Second, the authors chose to include patients with Child-Pugh B disease without active bleeding at endoscopy [the largest group of patients in this trial]; such patients are not often seen in Europe. Last, a survival benefit was only observed when the Child-Pugh B and Child-Pugh C patients were combined, with and without active bleeding. Hence, this study does not permit conclusions to be made for patients with Child-Pugh B disease.”
“Overall, the authors should be congratulated for tackling the much debated issue of preemptive TIPS,” Dr. Thabut and Dr. Rudler wrote. “There is now no doubt about the benefit of preemptive TIPS in patients with Child-Pugh C disease. The beneficial effects of preemptive TIPS on ascites should push us to consider this approach in all patients, in the absence of contraindication.”
Dr. Tabut and Dr. Rudler, of the Institute of Cardiometabolism and Nutrition, Paris, made their remarks in an accompanying editorial (Lancet Gastroenterol Hepatol. 2019 May 29. doi: 10.1016/S2468-1253[19]30172-4). They reported no conflicts of interest.
Early TIPS “should therefore be preferred to the current standard of care,” reported lead author Yong Lv, MD, of the Fourth Military Medical University in Xi’an, China, and colleagues, referring to standard pharmaceutical and endoscopic therapy.
“[The current standard] approach has improved patient outcomes,” the investigators wrote in the Lancet Gastroenterology & Hepatology. “However, up to 10%-20% of patients still experience treatment failure, requiring further intensive management. In such patients, [TIPS] is successful in achieving hemostasis in 90%-100% of patients. However, 6-week mortality remains high [35%-55%]. This is probably because the severity of the underlying liver disease has worsened and additional organ dysfunction may have occurred after several failed endoscopic therapy attempts.”
Previous studies have explored earlier intervention with TIPS; however, according to the investigators, these trials were inconclusive for various reasons. For example, uncovered stents and an out-of-date control therapy were employed in a trial by Monescillo et al., while a study by Garcia-Pagan et al. lacked a primary survival endpoint and has been criticized for selection bias. “Thus, whether early TIPS confers a survival benefit in a broader population remains to be assessed,” the investigators wrote.
To this end, the investigators screened 373 patients with advanced cirrhosis (Child-Pugh class B or C) and acute variceal bleeding. Of these, 132 were eligible for inclusion based on age, disease severity, willingness to participate, comorbidities, and other factors. Patients were randomized 2:1 to receive either early TIPS or standard therapy. Within 12 hours of hospital admission for the initial bleeding episode, all patients received vasoactive drugs or endoscopic band ligation and prophylactic antibiotics. Control patients continued vasoactive drugs for up to 5 days, followed by propranolol, which was titrated to reduce resting heart rate by 25% but not less than 55 beats per minute. Elective endoscopic band ligation was performed within 1-2 weeks of initial endoscopic treatment, then approximately every 2 weeks until variceal eradication, and additionally if varices reappeared. TIPS was allowed as rescue therapy. In contrast, patients in the TIPS group underwent the procedure with conscious sedation and local anesthesia within 72 hours of diagnostic endoscopy, followed by approximately 1 week of antibiotics and vasoactive drugs. TIPS revision with angioplasty or another stent placement was performed in the event of shunt dysfunction or reemergence of portal hypertensive complications. The final dataset contained 127 patients, as 3 were excluded after randomization because of exclusionary diagnoses, 1 withdrew consent, and 1 died before TIPS placement.
The primary endpoint was transplantation-free survival. The secondary endpoints were new or worsening ascites based on ultrasound score or sustained ascites necessitating paracentesis, failure to control bleeding or rebleeding, overt hepatic encephalopathy, other complications of portal hypertension, and adverse events.
After a median follow-up of 24 months, data analysis showed a survival benefit associated with early TIPS based on multiple measures. Out of 84 patients in the TIPS group, 15 (18%) died during follow-up, compared with 15 (33%) in the control group. Actuarial transplantation-free survival was also better with TIPS instead of standard therapy at 6 weeks (99% vs. 84%), 1 year (86% vs. 73%), and 2 years (79% vs. 64%). The hazard ratio for transplantation-free survival was 0.50 in favor of TIPS (P = .04). These survival advantages were maintained regardless of hepatitis B virus status or Child-Pugh/Model for End-Stage Liver Disease score.
Similarly to transplantation-free survival, patients treated with TIPS were more likely to be free of uncontrolled bleeding or rebleeding at 1 year (89% vs. 66%) and 2 years (86% vs. 57%). The associated hazard ratio for this outcome favored early TIPS (HR, 0.26; P less than .0001), and univariate and multivariate analysis confirmed an independent protective role. In further support of superiority over standard therapy, patients treated with TIPS were more likely than those in the control group to be free of new or worsening ascites at 1 year (89% vs. 57%) and 2 years (81% vs. 54%).
No significant intergroup differences were found for rates of overt hepatic encephalopathy, hepatic hydrothorax, hepatorenal syndrome, spontaneous bacterial peritonitis, hepatocellular carcinoma, serious adverse events, or nonserious adverse events. At 1 and 3 months, patients in the TIPS group had a slight increase of median bilirubin concentrations and median international normalized ratio; however, these values normalized after 6 months. A similar temporal pattern was observed in early TIPS patients with regard to median Model for End-Stage Liver Disease score.
“[The transplantation-free survival benefit of early TIPS] was probably related to better control of factors contributing to death, such as failure to control bleeding or rebleeding or new or worsening ascites, without increasing the frequency and severity of overt hepatic encephalopathy and other adverse events,” the investigators concluded. “This study provides direct evidence and greater confidence in the recommendations of current guidelines that early TIPS should be performed in high-risk patients without contraindications.
“Future studies addressing whether early TIPS can be equally recommended in Child-Pugh B and C patients are warranted,” the investigators added.
The study was funded by the National Key Technology R&D Program, Boost Program of Xijing Hospital, Optimized Overall Project of Shaanxi Province, and National Natural Science Foundation of China. The investigators reported no conflicts of interest.
SOURCE: Lv Y et al. Lancet Gastroenterol Hepatol. 2019 May 29. doi: 10.1016/S2468-1253(19)30090-1.
Early TIPS “should therefore be preferred to the current standard of care,” reported lead author Yong Lv, MD, of the Fourth Military Medical University in Xi’an, China, and colleagues, referring to standard pharmaceutical and endoscopic therapy.
“[The current standard] approach has improved patient outcomes,” the investigators wrote in the Lancet Gastroenterology & Hepatology. “However, up to 10%-20% of patients still experience treatment failure, requiring further intensive management. In such patients, [TIPS] is successful in achieving hemostasis in 90%-100% of patients. However, 6-week mortality remains high [35%-55%]. This is probably because the severity of the underlying liver disease has worsened and additional organ dysfunction may have occurred after several failed endoscopic therapy attempts.”
Previous studies have explored earlier intervention with TIPS; however, according to the investigators, these trials were inconclusive for various reasons. For example, uncovered stents and an out-of-date control therapy were employed in a trial by Monescillo et al., while a study by Garcia-Pagan et al. lacked a primary survival endpoint and has been criticized for selection bias. “Thus, whether early TIPS confers a survival benefit in a broader population remains to be assessed,” the investigators wrote.
To this end, the investigators screened 373 patients with advanced cirrhosis (Child-Pugh class B or C) and acute variceal bleeding. Of these, 132 were eligible for inclusion based on age, disease severity, willingness to participate, comorbidities, and other factors. Patients were randomized 2:1 to receive either early TIPS or standard therapy. Within 12 hours of hospital admission for the initial bleeding episode, all patients received vasoactive drugs or endoscopic band ligation and prophylactic antibiotics. Control patients continued vasoactive drugs for up to 5 days, followed by propranolol, which was titrated to reduce resting heart rate by 25% but not less than 55 beats per minute. Elective endoscopic band ligation was performed within 1-2 weeks of initial endoscopic treatment, then approximately every 2 weeks until variceal eradication, and additionally if varices reappeared. TIPS was allowed as rescue therapy. In contrast, patients in the TIPS group underwent the procedure with conscious sedation and local anesthesia within 72 hours of diagnostic endoscopy, followed by approximately 1 week of antibiotics and vasoactive drugs. TIPS revision with angioplasty or another stent placement was performed in the event of shunt dysfunction or reemergence of portal hypertensive complications. The final dataset contained 127 patients, as 3 were excluded after randomization because of exclusionary diagnoses, 1 withdrew consent, and 1 died before TIPS placement.
The primary endpoint was transplantation-free survival. The secondary endpoints were new or worsening ascites based on ultrasound score or sustained ascites necessitating paracentesis, failure to control bleeding or rebleeding, overt hepatic encephalopathy, other complications of portal hypertension, and adverse events.
After a median follow-up of 24 months, data analysis showed a survival benefit associated with early TIPS based on multiple measures. Out of 84 patients in the TIPS group, 15 (18%) died during follow-up, compared with 15 (33%) in the control group. Actuarial transplantation-free survival was also better with TIPS instead of standard therapy at 6 weeks (99% vs. 84%), 1 year (86% vs. 73%), and 2 years (79% vs. 64%). The hazard ratio for transplantation-free survival was 0.50 in favor of TIPS (P = .04). These survival advantages were maintained regardless of hepatitis B virus status or Child-Pugh/Model for End-Stage Liver Disease score.
Similarly to transplantation-free survival, patients treated with TIPS were more likely to be free of uncontrolled bleeding or rebleeding at 1 year (89% vs. 66%) and 2 years (86% vs. 57%). The associated hazard ratio for this outcome favored early TIPS (HR, 0.26; P less than .0001), and univariate and multivariate analysis confirmed an independent protective role. In further support of superiority over standard therapy, patients treated with TIPS were more likely than those in the control group to be free of new or worsening ascites at 1 year (89% vs. 57%) and 2 years (81% vs. 54%).
No significant intergroup differences were found for rates of overt hepatic encephalopathy, hepatic hydrothorax, hepatorenal syndrome, spontaneous bacterial peritonitis, hepatocellular carcinoma, serious adverse events, or nonserious adverse events. At 1 and 3 months, patients in the TIPS group had a slight increase of median bilirubin concentrations and median international normalized ratio; however, these values normalized after 6 months. A similar temporal pattern was observed in early TIPS patients with regard to median Model for End-Stage Liver Disease score.
“[The transplantation-free survival benefit of early TIPS] was probably related to better control of factors contributing to death, such as failure to control bleeding or rebleeding or new or worsening ascites, without increasing the frequency and severity of overt hepatic encephalopathy and other adverse events,” the investigators concluded. “This study provides direct evidence and greater confidence in the recommendations of current guidelines that early TIPS should be performed in high-risk patients without contraindications.
“Future studies addressing whether early TIPS can be equally recommended in Child-Pugh B and C patients are warranted,” the investigators added.
The study was funded by the National Key Technology R&D Program, Boost Program of Xijing Hospital, Optimized Overall Project of Shaanxi Province, and National Natural Science Foundation of China. The investigators reported no conflicts of interest.
SOURCE: Lv Y et al. Lancet Gastroenterol Hepatol. 2019 May 29. doi: 10.1016/S2468-1253(19)30090-1.
FROM THE LANCET GASTROENTEROLOGY & HEPATOLOGY
Bringing QI training to an IM residency program
Consider a formal step-wise curriculum
For current and future hospitalists, there’s no doubt that knowledge of quality improvement (QI) fundamentals is an important component of a successful practice. One physician team set out to provide their trainees with that QI foundation and described the results.
“We believed that implementing a formal step-wise QI curriculum would not only meet the Accreditation Council of Graduate Medical Education (ACGME) requirements, but also increase residents’ knowledge of QI fundamentals and ultimately establish a culture of continuous improvement aiming to provide high-value care to our health care consumers,” said lead author J. Colt Cowdell, MD, MBA, of Mayo Clinic in Jacksonville, Fla.
Prior to any interventions, the team surveyed internal medicine residents regarding three unique patient scenarios and scored their answers. Residents were then assigned to one of five unique QI projects for the academic year in combination with a structured didactic QI curriculum.
After the structured progressive curriculum, in combination with team-based QI projects, residents were surveyed again. Results showed not only increased QI knowledge, but also improved patient safety and reduced waste.
“Keys to successful implementation included a thorough explanation of the need for this curriculum to the learners and ensuring that QI teams were multidisciplinary – residents, QI experts, nurses, techs, pharmacy, administrators, etc.,” said Dr. Cowdell.
For hospitalists in an academic setting, this work can provide a framework to incorporate QI into their residency programs. “I hope, if they have a passion for QI, they would seek out opportunities to mentor residents and help lead multidisciplinary team-based projects,” Dr. Cowdell said.
Reference
1. Cowdell, JC; Trautman, C; Lewis, M; Dawson, N. Integration of a Novel Quality Improvement Curriculum into an Internal Medicine Residency Program. Abstract published at Hospital Medicine 2018; April 8-11; Orlando, Fla. Abstract 54. https://www.shmabstracts.com/abstract/integration-of-a-novel-quality-improvement-curriculum-into-an-internal-medicine-residency-program/. Accessed Dec. 11, 2018.
Consider a formal step-wise curriculum
Consider a formal step-wise curriculum
For current and future hospitalists, there’s no doubt that knowledge of quality improvement (QI) fundamentals is an important component of a successful practice. One physician team set out to provide their trainees with that QI foundation and described the results.
“We believed that implementing a formal step-wise QI curriculum would not only meet the Accreditation Council of Graduate Medical Education (ACGME) requirements, but also increase residents’ knowledge of QI fundamentals and ultimately establish a culture of continuous improvement aiming to provide high-value care to our health care consumers,” said lead author J. Colt Cowdell, MD, MBA, of Mayo Clinic in Jacksonville, Fla.
Prior to any interventions, the team surveyed internal medicine residents regarding three unique patient scenarios and scored their answers. Residents were then assigned to one of five unique QI projects for the academic year in combination with a structured didactic QI curriculum.
After the structured progressive curriculum, in combination with team-based QI projects, residents were surveyed again. Results showed not only increased QI knowledge, but also improved patient safety and reduced waste.
“Keys to successful implementation included a thorough explanation of the need for this curriculum to the learners and ensuring that QI teams were multidisciplinary – residents, QI experts, nurses, techs, pharmacy, administrators, etc.,” said Dr. Cowdell.
For hospitalists in an academic setting, this work can provide a framework to incorporate QI into their residency programs. “I hope, if they have a passion for QI, they would seek out opportunities to mentor residents and help lead multidisciplinary team-based projects,” Dr. Cowdell said.
Reference
1. Cowdell, JC; Trautman, C; Lewis, M; Dawson, N. Integration of a Novel Quality Improvement Curriculum into an Internal Medicine Residency Program. Abstract published at Hospital Medicine 2018; April 8-11; Orlando, Fla. Abstract 54. https://www.shmabstracts.com/abstract/integration-of-a-novel-quality-improvement-curriculum-into-an-internal-medicine-residency-program/. Accessed Dec. 11, 2018.
For current and future hospitalists, there’s no doubt that knowledge of quality improvement (QI) fundamentals is an important component of a successful practice. One physician team set out to provide their trainees with that QI foundation and described the results.
“We believed that implementing a formal step-wise QI curriculum would not only meet the Accreditation Council of Graduate Medical Education (ACGME) requirements, but also increase residents’ knowledge of QI fundamentals and ultimately establish a culture of continuous improvement aiming to provide high-value care to our health care consumers,” said lead author J. Colt Cowdell, MD, MBA, of Mayo Clinic in Jacksonville, Fla.
Prior to any interventions, the team surveyed internal medicine residents regarding three unique patient scenarios and scored their answers. Residents were then assigned to one of five unique QI projects for the academic year in combination with a structured didactic QI curriculum.
After the structured progressive curriculum, in combination with team-based QI projects, residents were surveyed again. Results showed not only increased QI knowledge, but also improved patient safety and reduced waste.
“Keys to successful implementation included a thorough explanation of the need for this curriculum to the learners and ensuring that QI teams were multidisciplinary – residents, QI experts, nurses, techs, pharmacy, administrators, etc.,” said Dr. Cowdell.
For hospitalists in an academic setting, this work can provide a framework to incorporate QI into their residency programs. “I hope, if they have a passion for QI, they would seek out opportunities to mentor residents and help lead multidisciplinary team-based projects,” Dr. Cowdell said.
Reference
1. Cowdell, JC; Trautman, C; Lewis, M; Dawson, N. Integration of a Novel Quality Improvement Curriculum into an Internal Medicine Residency Program. Abstract published at Hospital Medicine 2018; April 8-11; Orlando, Fla. Abstract 54. https://www.shmabstracts.com/abstract/integration-of-a-novel-quality-improvement-curriculum-into-an-internal-medicine-residency-program/. Accessed Dec. 11, 2018.
The Opioid Crisis: An MDedge Psychcast Presentation
Nurse Responses to Physiologic Monitor Alarms on a General Pediatric Unit
Alarms from bedside continuous physiologic monitors (CPMs) occur frequently in children’s hospitals and can lead to harm. Recent studies conducted in children’s hospitals have identified alarm rates of up to 152 alarms per patient per day outside of the intensive care unit,1-3 with as few as 1% of alarms being considered clinically important.4 Excessive alarms have been linked to alarm fatigue, when providers become desensitized to and may miss alarms indicating impending patient deterioration. Alarm fatigue has been identified by national patient safety organizations as a patient safety concern given the risk of patient harm.5-7 Despite these concerns, CPMs are routinely used: up to 48% of pediatric patients in nonintensive care units at children’s hospitals are monitored.2
Although the low number of alarms that receive responses has been well-described,8,9 the reasons why clinicians do or do not respond to alarms are unclear. A study conducted in an adult perioperative unit noted prolonged nurse response times for patients with high alarm rates.10 A second study conducted in the pediatric inpatient setting demonstrated a dose-response effect and noted progressively prolonged nurse response times with increased rates of nonactionable alarms.4,11 Findings from another study suggested that underlying factors are highly complex and may be a result of excessive alarms, clinician characteristics, and working conditions (eg, workload and unit noise level).12 Evidence also suggests that humans have difficulty distinguishing the importance of alarms in situations where multiple alarm tones are used, a common scenario in hospitals.
An enhanced understanding of why nurses respond to alarms in daily practice will inform intervention development and improvement work. In the long term, this information could help improve systems for monitoring pediatric inpatients that are less prone to issues with alarm fatigue. The objective of this qualitative study, which employed structured observation, was to describe how bedside nurses think about and act upon bedside monitor alarms in a general pediatric inpatient unit.
METHODS
Study Design and Setting
This prospective observational study took place on a 48-bed hospital medicine unit at a large, freestanding children’s hospital with >650 beds and >19,000 annual admissions. General Electric (Little Chalfont, United Kingdom) physiologic monitors (models Dash 3000, 4000, and 5000) were used at the time of the study, and nurses could be notified of monitor alarms in four ways: First, an in-room auditory alarm sounds. Second, a light positioned above the door outside of each patient room blinks for alarms that are at a “warning” or “critical level” (eg ventricular tachycardia or low oxygen saturation). Third, audible alarms occur at the unit’s central monitoring station. Lastly, another staff member can notify the patient’s nurse via in-person conversion or secure smart phone communication. On the study unit, CPMs are initiated and discontinued through a physician order.
This study was reviewed and approved by the hospital’s institutional review board.
Study Population
We used a purposive recruitment strategy to enroll bedside nurses working on general hospital medicine units, stratified to ensure varying levels of experience and primary shifts (eg, day vs night). We planned to conduct approximately two observations with each participating nurse and to continue collecting data until we could no longer identify new insights in terms of responses to alarms (ie, thematic saturation15). Observations were targeted to cover times of day that coincided with increased rates of distraction. These times included just prior to and after the morning and evening change of shifts (7:00
Data Sources
Prior to data collection, the research team, which consisted of physicians, bedside nurses, research coordinators, and a human factors expert, created a system for categorizing alarm responses. Categories for observed responses were based on the location and corresponding action taken. Initial categories were developed a priori from existing literature and expanded through input from the multidisciplinary study team, then vetted with bedside staff, and finally pilot tested through >4 hours of observations, thus producing the final categories. These categories were entered into a work-sampling program (WorkStudy by Quetech Ltd., Waterloo, Ontario, Canada) to facilitate quick data recording during observations.
The hospital uses a central alarm collection software (BedMasterEx by Anandic Medical Systems, Feuerthalen, Switzerland), which permitted the collection of date, time, trigger (eg, high heart rate), and level (eg, crisis, warning) of the generated CPM alarms. Alarms collected are based on thresholds preset at the bedside monitor. The central collection software does not differentiate between accurate (eg, correctly representing the physiologic state of the patient) and inaccurate alarms.
Observation Procedure
At the time of observation, nurse demographic information (eg, primary shift worked and years working as a nurse) was obtained. A brief preobservation questionnaire was administered to collect patient information (eg, age and diagnosis) and the nurses’ perspectives on the necessity of monitors for each monitored patient in his/her care.
The observer shadowed the nurse for a two-hour block of his/her shift. During this time, nurses were instructed to “think aloud” as they responded to alarms (eg, “I notice the oxygen saturation monitor alarming off, but the probe has fallen off”). A trained observer (AML or KMT) recorded responses verbalized by the nurse and his/her reaction by selecting the appropriate category using the work-sampling software. Data were also collected on the vital sign associated with the alarm (eg, heart rate). Moreover, the observer kept written notes to provide context for electronically recorded data. Alarms that were not verbalized by the nurse were not counted. Similarly, alarms that were noted outside of the room by the nurse were not classified by vital sign unless the nurse confirmed with the bedside monitor. Observers did not adjudicate the accuracy of the alarms. The session was stopped if monitors were discontinued during the observation period. Alarm data generated by the bedside monitor were pulled for each patient room after observations were completed.
Analysis
Descriptive statistics were used to assess the percentage of each nurse response category and each alarm type (eg, heart rate and respiratory rate). The observed alarm rate was calculated by taking the total number of observed alarms (ie, alarms noted by the nurse) divided by the total number of patient-hours observed. The monitor-generated alarm rate was calculated by taking the total number of alarms from the bedside-alarm generated data divided by the number of patient-hours observed.
Electronically recorded observations using the work-sampling program were cross-referenced with hand-written field notes to assess for any discrepancies or identify relevant events not captured by the program. Three study team members (AML, KMT, and ACS) reviewed each observation independently and compared field notes to ensure accurate categorization. Discrepancies were referred to the larger study group in cases of uncertainty.
RESULTS
Nine nurses had monitored patients during the available observations and participated in 19 observation sessions, which included 35 monitored patients for a total of 61.3 patient-hours of observation. Nurses were observed for a median of two times each (range 1-4). The median number of monitored patients during a single observation session was two (range 1-3). Observed nurses were female with a median of eight years of experience (range 0.5-26 years). Patients represented a broad range of age categories and were hospitalized with a variety of diagnoses (Table). Nurses, when queried at the start of the observation, felt that monitors were necessary for 29 (82.9%) of the observed patients given either patient condition or unit policy.
A total of 207 observed nurse responses to alarms occurred during the study period for a rate of 3.4 responses per patient per hour. Of the total number of responses, 45 (21.7%) were noted outside of a patient room, and in 15 (33.3%) the nurse chose to go to the room. The other 162 were recorded when the nurse was present in the room when the alarm activated. Of the 177 in-person nurse responses, 50 were related to a pulse oximetry alarm, 66 were related to a heart rate alarm, and 61 were related to a respiratory rate alarm. The most common observed in-person response to an alarm involved the nurse judging that no intervention was necessary (n = 152, 73.1%). Only 14 (7% of total responses) observed in-person responses involved a clinical intervention, such as suctioning or titrating supplemental oxygen. Findings are summarized in the Figure and describe nurse-verbalized reasons to further assess (or not) and then whether the nurse chose to take action (or not) after an alarm.
Alarm data were available for 17 of the 19 observation periods during the study. Technical issues with the central alarm collection software precluded alarm data collection for two of the observation sessions. A total of 483 alarms were recorded on bedside monitors during those 17 observation periods or 8.8 alarms per patient per hour, which was equivalent to 211.2 alarms per patient-day. A total of 175 observed responses were collected during these 17 observation periods. This number of responses was 36% of the number we would have expected on the basis of the alarm count from the central alarm software.
There were no patients transferred to the intensive care unit during the observation period. Nurses who chose not to respond to alarms outside the room most often cited the brevity of the alarm or other reassuring contextual details, such as that a family member was in the room to notify them if anything was truly wrong, that another member of the medical team was with the patient, or that they had recently assessed the patient and thought likely the alarm did not require any action. During three observations, the observed nurse cited the presence of family in the patient’s room in their decision not to conduct further assessment in response to the alarm, noting that the parent would be able to notify the nurse if something required attention. On two occasions in which a nurse had multiple monitored patients, the observed nurse noted that if the other monitored patients were alarming and she happened to be in another patient’s room, she would not be able to hear them. Four nurses cited policy as the reason a patient was on monitors (eg, patient was on respiratory support at night for obstructive sleep apnea).
DISCUSSION
We characterized responses to physiologic monitor alarms by a group of nurses with a range of experience levels. We found that most nurse responses to alarms in continuously monitored general pediatric patients involved no intervention, and further assessment was often not conducted for alarms that occurred outside of the room if the nurse noted otherwise reassuring clinical context. Observed responses occurred for 36% of alarms during the study period when compared with bedside monitor-alarm generated data. Overall, only 14 clinical interventions were noted among the observed responses. Nurses noted that they felt the monitors were necessary for 82.9% of monitored patients because of the clinical context or because of unit policy.
Our study findings highlight some potential contradictions in the current widespread use of CPMs in general pediatric units and how clinicians respond to them in practice.2 First, while nurses reported that monitors were necessary for most of their patients, participating nurses deemed few alarms clinically actionable and often chose not to further assess when they noted alarms outside of the room. This is in line with findings from prior studies suggesting that clinicians overvalue the contribution of monitoring systems to patient safety.
Our findings provide a novel understanding of previously observed phenomena, such as long response times or nonresponses in settings with high alarm rates.4,10 Similar to that in a prior study conducted in the pediatric setting,11 alarms with an observed response constituted a minority of the total alarms that occurred in our study. This finding has previously been attributed to mental fatigue, caregiver apathy, and desensitization.8 However, even though a minority of observed responses in our study included an intervention, the nurse had a rationale for why the alarm did or did not need a response. This behavior and the verbalized rationale indicate that in his/her opinion, not responding to the alarm was clinically appropriate. Study participants also reflected on the difficulties of responding to alarms given the monitor system setup, in which they may not always be capable of hearing alarms for their patients. Without data from nurses regarding the alarms that had no observed response, we can only speculate; however, based on our findings, each of these factors could contribute to nonresponse. Finally, while high numbers of false alarms have been posited as an underlying cause of alarm fatigue, we noted that a majority of nonresponse was reported to be related to other clinical factors. This relationship suggests that from the nurse’s perspective, a more applicable framework for understanding alarms would be based on clinical actionability4 over physiologic accuracy.
In total, our findings suggest that a multifaceted approach will be necessary to improve alarm response rates. These interventions should include adjusting parameters such that alarms are highly likely to indicate a need for intervention coupled with educational interventions addressing clinician knowledge of the alarm system and bias about the actionability of alarms may improve response rates. Changes in the monitoring system setup such that nurses can easily be notified when alarms occur may also be indicated, in addition to formally engaging patients and families around response to alarms. Although secondary notification systems (eg, alarms transmitted to individual clinician’s devices) are one solution, the utilization of these systems needs to be balanced with the risks of contributing to existing alarm fatigue and the need to appropriately tailor monitoring thresholds and strategies to patients.
Our study has several limitations. First, nurses may have responded in a way they perceive to be socially desirable, and studies using in-person observers are also prone to a Hawthorne-like effect,19-21 where the nurse may have tried to respond more frequently to alarms than usual during observations. However, given that the majority of bedside alarms did not receive a response and a substantial number of responses involved no action, these effects were likely weak. Second, we were unable to assess which alarms were accurately reflecting the patient’s physiologic status and which were not; we were also unable to link observed alarm response to monitor-recorded alarms. Third, despite the use of silent observers and an actual, rather than a simulated, clinical setting, by virtue of the data collection method we likely captured a more deliberate thought process (so-called System 2 thinking)22 rather than the subconscious processes that may predominate when nurses respond to alarms in the course of clinical care (System 1 thinking).22 Despite this limitation, our study findings, which reflect a nurse’s in-the-moment thinking, remain relevant to guiding the improvement of monitoring systems, and the development of nurse-facing interventions and education. Finally, we studied a small, purposive sample of nurses at a single hospital. Our study sample impacts the generalizability of our results and precluded a detailed analysis of the effect of nurse- and patient-level variables.
CONCLUSION
We found that nurses often deemed that no response was necessary for CPM alarms. Nurses cited contextual factors, including the duration of alarms and the presence of other providers or parents in their decision-making. Few (7%) of the alarm responses in our study included a clinical intervention. The number of observed alarm responses constituted roughly a third of the alarms recorded by bedside CPMs during the study. This result supports concerns about the nurse’s capacity to hear and process all CPM alarms given system limitations and a heavy clinical workload. Subsequent steps should include staff education, reducing overall alarm rates with appropriate monitor use and actionable alarm thresholds, and ensuring that patient alarms are easily recognizable for frontline staff.
Disclosures
The authors have no conflicts of interest to disclose.
Funding
This work was supported by the Place Outcomes Research Award from the Cincinnati Children’s Research Foundation. Dr. Brady is supported by the Agency for Healthcare Research and Quality under Award Number K08HS23827. The content is solely the responsibility of the authors and does not necessarily represent the official views of the Agency for Healthcare Research and Quality.
1. Schondelmeyer AC, Bonafide CP, Goel VV, et al. The frequency of physiologic monitor alarms in a children’s hospital. J Hosp Med. 2016;11(11):796-798. https://doi.org/10.1002/jhm.2612.
2. Schondelmeyer AC, Brady PW, Goel VV, et al. Physiologic monitor alarm rates at 5 children’s hospitals. J Hosp Med. 2018;13(6):396-398. https://doi.org/10.12788/jhm.2918.
3. Schondelmeyer AC, Brady PW, Sucharew H, et al. The impact of reduced pulse oximetry use on alarm frequency. Hosp Pediatr. In press. PubMed
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6. Sendelbach S, Funk M. Alarm fatigue: a patient safety concern. AACN Adv Crit Care. 2013;24(4):378-386. https://doi.org/10.1097/NCI.0b013e3182a903f9.
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8. Cvach M. Monitor alarm fatigue: an integrative review. Biomed Instrum Technol. 2012;46(4):268-277. https://doi.org/10.2345/0899-8205-46.4.268.
9. Paine CW, Goel VV, Ely E, et al. Systematic review of physiologic monitor alarm characteristics and pragmatic interventions to reduce alarm frequency. J Hosp Med. 2016;11(2):136-144. https://doi.org/10.1002/jhm.2520.
10. Voepel-Lewis T, Parker ML, Burke CN, et al. Pulse oximetry desaturation alarms on a general postoperative adult unit: a prospective observational study of nurse response time. Int J Nurs Stud. 2013;50(10):1351-1358. https://doi.org/10.1016/j.ijnurstu.2013.02.006.
11. Bonafide CP, Localio AR, Holmes JH, et al. Video analysis of factors associated With response time to physiologic monitor alarms in a children’s hospital. JAMA Pediatr. 2017;171(6):524-531. https://doi.org/10.1001/jamapediatrics.2016.5123.
12. Deb S, Claudio D. Alarm fatigue and its influence on staff performance. IIE Trans Healthc Syst Eng. 2015;5(3):183-196. https://doi.org/10.1080/19488300.2015.1062065.
13. Mondor TA, Hurlburt J, Thorne L. Categorizing sounds by pitch: effects of stimulus similarity and response repetition. Percept Psychophys. 2003;65(1):107-114. https://doi.org/10.3758/BF03194787.
14. Mondor TA, Finley GA. The perceived urgency of auditory warning alarms used in the hospital operating room is inappropriate. Can J Anaesth. 2003;50(3):221-228. https://doi.org/10.1007/BF03017788.
15. Fusch PI, Ness LR. Are we there yet? Data saturation in qualitative research. Qual Rep; 20(9), 2015:1408-1416.
16. Najafi N, Auerbach A. Use and outcomes of telemetry monitoring on a medicine service. Arch Intern Med. 2012;172(17):1349-1350. https://doi.org/10.1001/archinternmed.2012.3163.
17. Estrada CA, Rosman HS, Prasad NK, et al. Role of telemetry monitoring in the non-intensive care unit. Am J Cardiol. 1995;76(12):960-965. https://doi.org/10.1016/S0002-9149(99)80270-7.
18. Khan A, Furtak SL, Melvin P et al. Parent-reported errors and adverse events in hospitalized children. JAMA Pediatr. 2016;170(4):e154608.https://doi.org/10.1001/jamapediatrics.2015.4608.
19. Adair JG. The Hawthorne effect: a reconsideration of the methodological artifact. J Appl Psychol. 1984;69(2):334-345. https://doi.org/10.1037/0021-9010.69.2.334.
20. Kovacs-Litman A, Wong K, Shojania KG, et al. Do physicians clean their hands? Insights from a covert observational study. J Hosp Med. 2016;11(12):862-864. https://doi.org/10.1002/jhm.2632.
21. Wolfe F, Michaud K. The Hawthorne effect, sponsored trials, and the overestimation of treatment effectiveness. J Rheumatol. 2010;37(11):2216-2220. https://doi.org/10.3899/jrheum.100497.
22. Kahneman D. Thinking, Fast and Slow. 1st Pbk. ed. New York: Farrar, Straus and Giroux; 2013.
Alarms from bedside continuous physiologic monitors (CPMs) occur frequently in children’s hospitals and can lead to harm. Recent studies conducted in children’s hospitals have identified alarm rates of up to 152 alarms per patient per day outside of the intensive care unit,1-3 with as few as 1% of alarms being considered clinically important.4 Excessive alarms have been linked to alarm fatigue, when providers become desensitized to and may miss alarms indicating impending patient deterioration. Alarm fatigue has been identified by national patient safety organizations as a patient safety concern given the risk of patient harm.5-7 Despite these concerns, CPMs are routinely used: up to 48% of pediatric patients in nonintensive care units at children’s hospitals are monitored.2
Although the low number of alarms that receive responses has been well-described,8,9 the reasons why clinicians do or do not respond to alarms are unclear. A study conducted in an adult perioperative unit noted prolonged nurse response times for patients with high alarm rates.10 A second study conducted in the pediatric inpatient setting demonstrated a dose-response effect and noted progressively prolonged nurse response times with increased rates of nonactionable alarms.4,11 Findings from another study suggested that underlying factors are highly complex and may be a result of excessive alarms, clinician characteristics, and working conditions (eg, workload and unit noise level).12 Evidence also suggests that humans have difficulty distinguishing the importance of alarms in situations where multiple alarm tones are used, a common scenario in hospitals.
An enhanced understanding of why nurses respond to alarms in daily practice will inform intervention development and improvement work. In the long term, this information could help improve systems for monitoring pediatric inpatients that are less prone to issues with alarm fatigue. The objective of this qualitative study, which employed structured observation, was to describe how bedside nurses think about and act upon bedside monitor alarms in a general pediatric inpatient unit.
METHODS
Study Design and Setting
This prospective observational study took place on a 48-bed hospital medicine unit at a large, freestanding children’s hospital with >650 beds and >19,000 annual admissions. General Electric (Little Chalfont, United Kingdom) physiologic monitors (models Dash 3000, 4000, and 5000) were used at the time of the study, and nurses could be notified of monitor alarms in four ways: First, an in-room auditory alarm sounds. Second, a light positioned above the door outside of each patient room blinks for alarms that are at a “warning” or “critical level” (eg ventricular tachycardia or low oxygen saturation). Third, audible alarms occur at the unit’s central monitoring station. Lastly, another staff member can notify the patient’s nurse via in-person conversion or secure smart phone communication. On the study unit, CPMs are initiated and discontinued through a physician order.
This study was reviewed and approved by the hospital’s institutional review board.
Study Population
We used a purposive recruitment strategy to enroll bedside nurses working on general hospital medicine units, stratified to ensure varying levels of experience and primary shifts (eg, day vs night). We planned to conduct approximately two observations with each participating nurse and to continue collecting data until we could no longer identify new insights in terms of responses to alarms (ie, thematic saturation15). Observations were targeted to cover times of day that coincided with increased rates of distraction. These times included just prior to and after the morning and evening change of shifts (7:00
Data Sources
Prior to data collection, the research team, which consisted of physicians, bedside nurses, research coordinators, and a human factors expert, created a system for categorizing alarm responses. Categories for observed responses were based on the location and corresponding action taken. Initial categories were developed a priori from existing literature and expanded through input from the multidisciplinary study team, then vetted with bedside staff, and finally pilot tested through >4 hours of observations, thus producing the final categories. These categories were entered into a work-sampling program (WorkStudy by Quetech Ltd., Waterloo, Ontario, Canada) to facilitate quick data recording during observations.
The hospital uses a central alarm collection software (BedMasterEx by Anandic Medical Systems, Feuerthalen, Switzerland), which permitted the collection of date, time, trigger (eg, high heart rate), and level (eg, crisis, warning) of the generated CPM alarms. Alarms collected are based on thresholds preset at the bedside monitor. The central collection software does not differentiate between accurate (eg, correctly representing the physiologic state of the patient) and inaccurate alarms.
Observation Procedure
At the time of observation, nurse demographic information (eg, primary shift worked and years working as a nurse) was obtained. A brief preobservation questionnaire was administered to collect patient information (eg, age and diagnosis) and the nurses’ perspectives on the necessity of monitors for each monitored patient in his/her care.
The observer shadowed the nurse for a two-hour block of his/her shift. During this time, nurses were instructed to “think aloud” as they responded to alarms (eg, “I notice the oxygen saturation monitor alarming off, but the probe has fallen off”). A trained observer (AML or KMT) recorded responses verbalized by the nurse and his/her reaction by selecting the appropriate category using the work-sampling software. Data were also collected on the vital sign associated with the alarm (eg, heart rate). Moreover, the observer kept written notes to provide context for electronically recorded data. Alarms that were not verbalized by the nurse were not counted. Similarly, alarms that were noted outside of the room by the nurse were not classified by vital sign unless the nurse confirmed with the bedside monitor. Observers did not adjudicate the accuracy of the alarms. The session was stopped if monitors were discontinued during the observation period. Alarm data generated by the bedside monitor were pulled for each patient room after observations were completed.
Analysis
Descriptive statistics were used to assess the percentage of each nurse response category and each alarm type (eg, heart rate and respiratory rate). The observed alarm rate was calculated by taking the total number of observed alarms (ie, alarms noted by the nurse) divided by the total number of patient-hours observed. The monitor-generated alarm rate was calculated by taking the total number of alarms from the bedside-alarm generated data divided by the number of patient-hours observed.
Electronically recorded observations using the work-sampling program were cross-referenced with hand-written field notes to assess for any discrepancies or identify relevant events not captured by the program. Three study team members (AML, KMT, and ACS) reviewed each observation independently and compared field notes to ensure accurate categorization. Discrepancies were referred to the larger study group in cases of uncertainty.
RESULTS
Nine nurses had monitored patients during the available observations and participated in 19 observation sessions, which included 35 monitored patients for a total of 61.3 patient-hours of observation. Nurses were observed for a median of two times each (range 1-4). The median number of monitored patients during a single observation session was two (range 1-3). Observed nurses were female with a median of eight years of experience (range 0.5-26 years). Patients represented a broad range of age categories and were hospitalized with a variety of diagnoses (Table). Nurses, when queried at the start of the observation, felt that monitors were necessary for 29 (82.9%) of the observed patients given either patient condition or unit policy.
A total of 207 observed nurse responses to alarms occurred during the study period for a rate of 3.4 responses per patient per hour. Of the total number of responses, 45 (21.7%) were noted outside of a patient room, and in 15 (33.3%) the nurse chose to go to the room. The other 162 were recorded when the nurse was present in the room when the alarm activated. Of the 177 in-person nurse responses, 50 were related to a pulse oximetry alarm, 66 were related to a heart rate alarm, and 61 were related to a respiratory rate alarm. The most common observed in-person response to an alarm involved the nurse judging that no intervention was necessary (n = 152, 73.1%). Only 14 (7% of total responses) observed in-person responses involved a clinical intervention, such as suctioning or titrating supplemental oxygen. Findings are summarized in the Figure and describe nurse-verbalized reasons to further assess (or not) and then whether the nurse chose to take action (or not) after an alarm.
Alarm data were available for 17 of the 19 observation periods during the study. Technical issues with the central alarm collection software precluded alarm data collection for two of the observation sessions. A total of 483 alarms were recorded on bedside monitors during those 17 observation periods or 8.8 alarms per patient per hour, which was equivalent to 211.2 alarms per patient-day. A total of 175 observed responses were collected during these 17 observation periods. This number of responses was 36% of the number we would have expected on the basis of the alarm count from the central alarm software.
There were no patients transferred to the intensive care unit during the observation period. Nurses who chose not to respond to alarms outside the room most often cited the brevity of the alarm or other reassuring contextual details, such as that a family member was in the room to notify them if anything was truly wrong, that another member of the medical team was with the patient, or that they had recently assessed the patient and thought likely the alarm did not require any action. During three observations, the observed nurse cited the presence of family in the patient’s room in their decision not to conduct further assessment in response to the alarm, noting that the parent would be able to notify the nurse if something required attention. On two occasions in which a nurse had multiple monitored patients, the observed nurse noted that if the other monitored patients were alarming and she happened to be in another patient’s room, she would not be able to hear them. Four nurses cited policy as the reason a patient was on monitors (eg, patient was on respiratory support at night for obstructive sleep apnea).
DISCUSSION
We characterized responses to physiologic monitor alarms by a group of nurses with a range of experience levels. We found that most nurse responses to alarms in continuously monitored general pediatric patients involved no intervention, and further assessment was often not conducted for alarms that occurred outside of the room if the nurse noted otherwise reassuring clinical context. Observed responses occurred for 36% of alarms during the study period when compared with bedside monitor-alarm generated data. Overall, only 14 clinical interventions were noted among the observed responses. Nurses noted that they felt the monitors were necessary for 82.9% of monitored patients because of the clinical context or because of unit policy.
Our study findings highlight some potential contradictions in the current widespread use of CPMs in general pediatric units and how clinicians respond to them in practice.2 First, while nurses reported that monitors were necessary for most of their patients, participating nurses deemed few alarms clinically actionable and often chose not to further assess when they noted alarms outside of the room. This is in line with findings from prior studies suggesting that clinicians overvalue the contribution of monitoring systems to patient safety.
Our findings provide a novel understanding of previously observed phenomena, such as long response times or nonresponses in settings with high alarm rates.4,10 Similar to that in a prior study conducted in the pediatric setting,11 alarms with an observed response constituted a minority of the total alarms that occurred in our study. This finding has previously been attributed to mental fatigue, caregiver apathy, and desensitization.8 However, even though a minority of observed responses in our study included an intervention, the nurse had a rationale for why the alarm did or did not need a response. This behavior and the verbalized rationale indicate that in his/her opinion, not responding to the alarm was clinically appropriate. Study participants also reflected on the difficulties of responding to alarms given the monitor system setup, in which they may not always be capable of hearing alarms for their patients. Without data from nurses regarding the alarms that had no observed response, we can only speculate; however, based on our findings, each of these factors could contribute to nonresponse. Finally, while high numbers of false alarms have been posited as an underlying cause of alarm fatigue, we noted that a majority of nonresponse was reported to be related to other clinical factors. This relationship suggests that from the nurse’s perspective, a more applicable framework for understanding alarms would be based on clinical actionability4 over physiologic accuracy.
In total, our findings suggest that a multifaceted approach will be necessary to improve alarm response rates. These interventions should include adjusting parameters such that alarms are highly likely to indicate a need for intervention coupled with educational interventions addressing clinician knowledge of the alarm system and bias about the actionability of alarms may improve response rates. Changes in the monitoring system setup such that nurses can easily be notified when alarms occur may also be indicated, in addition to formally engaging patients and families around response to alarms. Although secondary notification systems (eg, alarms transmitted to individual clinician’s devices) are one solution, the utilization of these systems needs to be balanced with the risks of contributing to existing alarm fatigue and the need to appropriately tailor monitoring thresholds and strategies to patients.
Our study has several limitations. First, nurses may have responded in a way they perceive to be socially desirable, and studies using in-person observers are also prone to a Hawthorne-like effect,19-21 where the nurse may have tried to respond more frequently to alarms than usual during observations. However, given that the majority of bedside alarms did not receive a response and a substantial number of responses involved no action, these effects were likely weak. Second, we were unable to assess which alarms were accurately reflecting the patient’s physiologic status and which were not; we were also unable to link observed alarm response to monitor-recorded alarms. Third, despite the use of silent observers and an actual, rather than a simulated, clinical setting, by virtue of the data collection method we likely captured a more deliberate thought process (so-called System 2 thinking)22 rather than the subconscious processes that may predominate when nurses respond to alarms in the course of clinical care (System 1 thinking).22 Despite this limitation, our study findings, which reflect a nurse’s in-the-moment thinking, remain relevant to guiding the improvement of monitoring systems, and the development of nurse-facing interventions and education. Finally, we studied a small, purposive sample of nurses at a single hospital. Our study sample impacts the generalizability of our results and precluded a detailed analysis of the effect of nurse- and patient-level variables.
CONCLUSION
We found that nurses often deemed that no response was necessary for CPM alarms. Nurses cited contextual factors, including the duration of alarms and the presence of other providers or parents in their decision-making. Few (7%) of the alarm responses in our study included a clinical intervention. The number of observed alarm responses constituted roughly a third of the alarms recorded by bedside CPMs during the study. This result supports concerns about the nurse’s capacity to hear and process all CPM alarms given system limitations and a heavy clinical workload. Subsequent steps should include staff education, reducing overall alarm rates with appropriate monitor use and actionable alarm thresholds, and ensuring that patient alarms are easily recognizable for frontline staff.
Disclosures
The authors have no conflicts of interest to disclose.
Funding
This work was supported by the Place Outcomes Research Award from the Cincinnati Children’s Research Foundation. Dr. Brady is supported by the Agency for Healthcare Research and Quality under Award Number K08HS23827. The content is solely the responsibility of the authors and does not necessarily represent the official views of the Agency for Healthcare Research and Quality.
Alarms from bedside continuous physiologic monitors (CPMs) occur frequently in children’s hospitals and can lead to harm. Recent studies conducted in children’s hospitals have identified alarm rates of up to 152 alarms per patient per day outside of the intensive care unit,1-3 with as few as 1% of alarms being considered clinically important.4 Excessive alarms have been linked to alarm fatigue, when providers become desensitized to and may miss alarms indicating impending patient deterioration. Alarm fatigue has been identified by national patient safety organizations as a patient safety concern given the risk of patient harm.5-7 Despite these concerns, CPMs are routinely used: up to 48% of pediatric patients in nonintensive care units at children’s hospitals are monitored.2
Although the low number of alarms that receive responses has been well-described,8,9 the reasons why clinicians do or do not respond to alarms are unclear. A study conducted in an adult perioperative unit noted prolonged nurse response times for patients with high alarm rates.10 A second study conducted in the pediatric inpatient setting demonstrated a dose-response effect and noted progressively prolonged nurse response times with increased rates of nonactionable alarms.4,11 Findings from another study suggested that underlying factors are highly complex and may be a result of excessive alarms, clinician characteristics, and working conditions (eg, workload and unit noise level).12 Evidence also suggests that humans have difficulty distinguishing the importance of alarms in situations where multiple alarm tones are used, a common scenario in hospitals.
An enhanced understanding of why nurses respond to alarms in daily practice will inform intervention development and improvement work. In the long term, this information could help improve systems for monitoring pediatric inpatients that are less prone to issues with alarm fatigue. The objective of this qualitative study, which employed structured observation, was to describe how bedside nurses think about and act upon bedside monitor alarms in a general pediatric inpatient unit.
METHODS
Study Design and Setting
This prospective observational study took place on a 48-bed hospital medicine unit at a large, freestanding children’s hospital with >650 beds and >19,000 annual admissions. General Electric (Little Chalfont, United Kingdom) physiologic monitors (models Dash 3000, 4000, and 5000) were used at the time of the study, and nurses could be notified of monitor alarms in four ways: First, an in-room auditory alarm sounds. Second, a light positioned above the door outside of each patient room blinks for alarms that are at a “warning” or “critical level” (eg ventricular tachycardia or low oxygen saturation). Third, audible alarms occur at the unit’s central monitoring station. Lastly, another staff member can notify the patient’s nurse via in-person conversion or secure smart phone communication. On the study unit, CPMs are initiated and discontinued through a physician order.
This study was reviewed and approved by the hospital’s institutional review board.
Study Population
We used a purposive recruitment strategy to enroll bedside nurses working on general hospital medicine units, stratified to ensure varying levels of experience and primary shifts (eg, day vs night). We planned to conduct approximately two observations with each participating nurse and to continue collecting data until we could no longer identify new insights in terms of responses to alarms (ie, thematic saturation15). Observations were targeted to cover times of day that coincided with increased rates of distraction. These times included just prior to and after the morning and evening change of shifts (7:00
Data Sources
Prior to data collection, the research team, which consisted of physicians, bedside nurses, research coordinators, and a human factors expert, created a system for categorizing alarm responses. Categories for observed responses were based on the location and corresponding action taken. Initial categories were developed a priori from existing literature and expanded through input from the multidisciplinary study team, then vetted with bedside staff, and finally pilot tested through >4 hours of observations, thus producing the final categories. These categories were entered into a work-sampling program (WorkStudy by Quetech Ltd., Waterloo, Ontario, Canada) to facilitate quick data recording during observations.
The hospital uses a central alarm collection software (BedMasterEx by Anandic Medical Systems, Feuerthalen, Switzerland), which permitted the collection of date, time, trigger (eg, high heart rate), and level (eg, crisis, warning) of the generated CPM alarms. Alarms collected are based on thresholds preset at the bedside monitor. The central collection software does not differentiate between accurate (eg, correctly representing the physiologic state of the patient) and inaccurate alarms.
Observation Procedure
At the time of observation, nurse demographic information (eg, primary shift worked and years working as a nurse) was obtained. A brief preobservation questionnaire was administered to collect patient information (eg, age and diagnosis) and the nurses’ perspectives on the necessity of monitors for each monitored patient in his/her care.
The observer shadowed the nurse for a two-hour block of his/her shift. During this time, nurses were instructed to “think aloud” as they responded to alarms (eg, “I notice the oxygen saturation monitor alarming off, but the probe has fallen off”). A trained observer (AML or KMT) recorded responses verbalized by the nurse and his/her reaction by selecting the appropriate category using the work-sampling software. Data were also collected on the vital sign associated with the alarm (eg, heart rate). Moreover, the observer kept written notes to provide context for electronically recorded data. Alarms that were not verbalized by the nurse were not counted. Similarly, alarms that were noted outside of the room by the nurse were not classified by vital sign unless the nurse confirmed with the bedside monitor. Observers did not adjudicate the accuracy of the alarms. The session was stopped if monitors were discontinued during the observation period. Alarm data generated by the bedside monitor were pulled for each patient room after observations were completed.
Analysis
Descriptive statistics were used to assess the percentage of each nurse response category and each alarm type (eg, heart rate and respiratory rate). The observed alarm rate was calculated by taking the total number of observed alarms (ie, alarms noted by the nurse) divided by the total number of patient-hours observed. The monitor-generated alarm rate was calculated by taking the total number of alarms from the bedside-alarm generated data divided by the number of patient-hours observed.
Electronically recorded observations using the work-sampling program were cross-referenced with hand-written field notes to assess for any discrepancies or identify relevant events not captured by the program. Three study team members (AML, KMT, and ACS) reviewed each observation independently and compared field notes to ensure accurate categorization. Discrepancies were referred to the larger study group in cases of uncertainty.
RESULTS
Nine nurses had monitored patients during the available observations and participated in 19 observation sessions, which included 35 monitored patients for a total of 61.3 patient-hours of observation. Nurses were observed for a median of two times each (range 1-4). The median number of monitored patients during a single observation session was two (range 1-3). Observed nurses were female with a median of eight years of experience (range 0.5-26 years). Patients represented a broad range of age categories and were hospitalized with a variety of diagnoses (Table). Nurses, when queried at the start of the observation, felt that monitors were necessary for 29 (82.9%) of the observed patients given either patient condition or unit policy.
A total of 207 observed nurse responses to alarms occurred during the study period for a rate of 3.4 responses per patient per hour. Of the total number of responses, 45 (21.7%) were noted outside of a patient room, and in 15 (33.3%) the nurse chose to go to the room. The other 162 were recorded when the nurse was present in the room when the alarm activated. Of the 177 in-person nurse responses, 50 were related to a pulse oximetry alarm, 66 were related to a heart rate alarm, and 61 were related to a respiratory rate alarm. The most common observed in-person response to an alarm involved the nurse judging that no intervention was necessary (n = 152, 73.1%). Only 14 (7% of total responses) observed in-person responses involved a clinical intervention, such as suctioning or titrating supplemental oxygen. Findings are summarized in the Figure and describe nurse-verbalized reasons to further assess (or not) and then whether the nurse chose to take action (or not) after an alarm.
Alarm data were available for 17 of the 19 observation periods during the study. Technical issues with the central alarm collection software precluded alarm data collection for two of the observation sessions. A total of 483 alarms were recorded on bedside monitors during those 17 observation periods or 8.8 alarms per patient per hour, which was equivalent to 211.2 alarms per patient-day. A total of 175 observed responses were collected during these 17 observation periods. This number of responses was 36% of the number we would have expected on the basis of the alarm count from the central alarm software.
There were no patients transferred to the intensive care unit during the observation period. Nurses who chose not to respond to alarms outside the room most often cited the brevity of the alarm or other reassuring contextual details, such as that a family member was in the room to notify them if anything was truly wrong, that another member of the medical team was with the patient, or that they had recently assessed the patient and thought likely the alarm did not require any action. During three observations, the observed nurse cited the presence of family in the patient’s room in their decision not to conduct further assessment in response to the alarm, noting that the parent would be able to notify the nurse if something required attention. On two occasions in which a nurse had multiple monitored patients, the observed nurse noted that if the other monitored patients were alarming and she happened to be in another patient’s room, she would not be able to hear them. Four nurses cited policy as the reason a patient was on monitors (eg, patient was on respiratory support at night for obstructive sleep apnea).
DISCUSSION
We characterized responses to physiologic monitor alarms by a group of nurses with a range of experience levels. We found that most nurse responses to alarms in continuously monitored general pediatric patients involved no intervention, and further assessment was often not conducted for alarms that occurred outside of the room if the nurse noted otherwise reassuring clinical context. Observed responses occurred for 36% of alarms during the study period when compared with bedside monitor-alarm generated data. Overall, only 14 clinical interventions were noted among the observed responses. Nurses noted that they felt the monitors were necessary for 82.9% of monitored patients because of the clinical context or because of unit policy.
Our study findings highlight some potential contradictions in the current widespread use of CPMs in general pediatric units and how clinicians respond to them in practice.2 First, while nurses reported that monitors were necessary for most of their patients, participating nurses deemed few alarms clinically actionable and often chose not to further assess when they noted alarms outside of the room. This is in line with findings from prior studies suggesting that clinicians overvalue the contribution of monitoring systems to patient safety.
Our findings provide a novel understanding of previously observed phenomena, such as long response times or nonresponses in settings with high alarm rates.4,10 Similar to that in a prior study conducted in the pediatric setting,11 alarms with an observed response constituted a minority of the total alarms that occurred in our study. This finding has previously been attributed to mental fatigue, caregiver apathy, and desensitization.8 However, even though a minority of observed responses in our study included an intervention, the nurse had a rationale for why the alarm did or did not need a response. This behavior and the verbalized rationale indicate that in his/her opinion, not responding to the alarm was clinically appropriate. Study participants also reflected on the difficulties of responding to alarms given the monitor system setup, in which they may not always be capable of hearing alarms for their patients. Without data from nurses regarding the alarms that had no observed response, we can only speculate; however, based on our findings, each of these factors could contribute to nonresponse. Finally, while high numbers of false alarms have been posited as an underlying cause of alarm fatigue, we noted that a majority of nonresponse was reported to be related to other clinical factors. This relationship suggests that from the nurse’s perspective, a more applicable framework for understanding alarms would be based on clinical actionability4 over physiologic accuracy.
In total, our findings suggest that a multifaceted approach will be necessary to improve alarm response rates. These interventions should include adjusting parameters such that alarms are highly likely to indicate a need for intervention coupled with educational interventions addressing clinician knowledge of the alarm system and bias about the actionability of alarms may improve response rates. Changes in the monitoring system setup such that nurses can easily be notified when alarms occur may also be indicated, in addition to formally engaging patients and families around response to alarms. Although secondary notification systems (eg, alarms transmitted to individual clinician’s devices) are one solution, the utilization of these systems needs to be balanced with the risks of contributing to existing alarm fatigue and the need to appropriately tailor monitoring thresholds and strategies to patients.
Our study has several limitations. First, nurses may have responded in a way they perceive to be socially desirable, and studies using in-person observers are also prone to a Hawthorne-like effect,19-21 where the nurse may have tried to respond more frequently to alarms than usual during observations. However, given that the majority of bedside alarms did not receive a response and a substantial number of responses involved no action, these effects were likely weak. Second, we were unable to assess which alarms were accurately reflecting the patient’s physiologic status and which were not; we were also unable to link observed alarm response to monitor-recorded alarms. Third, despite the use of silent observers and an actual, rather than a simulated, clinical setting, by virtue of the data collection method we likely captured a more deliberate thought process (so-called System 2 thinking)22 rather than the subconscious processes that may predominate when nurses respond to alarms in the course of clinical care (System 1 thinking).22 Despite this limitation, our study findings, which reflect a nurse’s in-the-moment thinking, remain relevant to guiding the improvement of monitoring systems, and the development of nurse-facing interventions and education. Finally, we studied a small, purposive sample of nurses at a single hospital. Our study sample impacts the generalizability of our results and precluded a detailed analysis of the effect of nurse- and patient-level variables.
CONCLUSION
We found that nurses often deemed that no response was necessary for CPM alarms. Nurses cited contextual factors, including the duration of alarms and the presence of other providers or parents in their decision-making. Few (7%) of the alarm responses in our study included a clinical intervention. The number of observed alarm responses constituted roughly a third of the alarms recorded by bedside CPMs during the study. This result supports concerns about the nurse’s capacity to hear and process all CPM alarms given system limitations and a heavy clinical workload. Subsequent steps should include staff education, reducing overall alarm rates with appropriate monitor use and actionable alarm thresholds, and ensuring that patient alarms are easily recognizable for frontline staff.
Disclosures
The authors have no conflicts of interest to disclose.
Funding
This work was supported by the Place Outcomes Research Award from the Cincinnati Children’s Research Foundation. Dr. Brady is supported by the Agency for Healthcare Research and Quality under Award Number K08HS23827. The content is solely the responsibility of the authors and does not necessarily represent the official views of the Agency for Healthcare Research and Quality.
1. Schondelmeyer AC, Bonafide CP, Goel VV, et al. The frequency of physiologic monitor alarms in a children’s hospital. J Hosp Med. 2016;11(11):796-798. https://doi.org/10.1002/jhm.2612.
2. Schondelmeyer AC, Brady PW, Goel VV, et al. Physiologic monitor alarm rates at 5 children’s hospitals. J Hosp Med. 2018;13(6):396-398. https://doi.org/10.12788/jhm.2918.
3. Schondelmeyer AC, Brady PW, Sucharew H, et al. The impact of reduced pulse oximetry use on alarm frequency. Hosp Pediatr. In press. PubMed
4. Bonafide CP, Lin R, Zander M, et al. Association between exposure to nonactionable physiologic monitor alarms and response time in a children’s hospital. J Hosp Med. 2015;10(6):345-351. https://doi.org/10.1002/jhm.2331.
5. Siebig S, Kuhls S, Imhoff M, et al. Intensive care unit alarms--how many do we need? Crit Care Med. 2010;38(2):451-456. https://doi.org/10.1097/CCM.0b013e3181cb0888.
6. Sendelbach S, Funk M. Alarm fatigue: a patient safety concern. AACN Adv Crit Care. 2013;24(4):378-386. https://doi.org/10.1097/NCI.0b013e3182a903f9.
7. Sendelbach S. Alarm fatigue. Nurs Clin North Am. 2012;47(3):375-382. https://doi.org/10.1016/j.cnur.2012.05.009.
8. Cvach M. Monitor alarm fatigue: an integrative review. Biomed Instrum Technol. 2012;46(4):268-277. https://doi.org/10.2345/0899-8205-46.4.268.
9. Paine CW, Goel VV, Ely E, et al. Systematic review of physiologic monitor alarm characteristics and pragmatic interventions to reduce alarm frequency. J Hosp Med. 2016;11(2):136-144. https://doi.org/10.1002/jhm.2520.
10. Voepel-Lewis T, Parker ML, Burke CN, et al. Pulse oximetry desaturation alarms on a general postoperative adult unit: a prospective observational study of nurse response time. Int J Nurs Stud. 2013;50(10):1351-1358. https://doi.org/10.1016/j.ijnurstu.2013.02.006.
11. Bonafide CP, Localio AR, Holmes JH, et al. Video analysis of factors associated With response time to physiologic monitor alarms in a children’s hospital. JAMA Pediatr. 2017;171(6):524-531. https://doi.org/10.1001/jamapediatrics.2016.5123.
12. Deb S, Claudio D. Alarm fatigue and its influence on staff performance. IIE Trans Healthc Syst Eng. 2015;5(3):183-196. https://doi.org/10.1080/19488300.2015.1062065.
13. Mondor TA, Hurlburt J, Thorne L. Categorizing sounds by pitch: effects of stimulus similarity and response repetition. Percept Psychophys. 2003;65(1):107-114. https://doi.org/10.3758/BF03194787.
14. Mondor TA, Finley GA. The perceived urgency of auditory warning alarms used in the hospital operating room is inappropriate. Can J Anaesth. 2003;50(3):221-228. https://doi.org/10.1007/BF03017788.
15. Fusch PI, Ness LR. Are we there yet? Data saturation in qualitative research. Qual Rep; 20(9), 2015:1408-1416.
16. Najafi N, Auerbach A. Use and outcomes of telemetry monitoring on a medicine service. Arch Intern Med. 2012;172(17):1349-1350. https://doi.org/10.1001/archinternmed.2012.3163.
17. Estrada CA, Rosman HS, Prasad NK, et al. Role of telemetry monitoring in the non-intensive care unit. Am J Cardiol. 1995;76(12):960-965. https://doi.org/10.1016/S0002-9149(99)80270-7.
18. Khan A, Furtak SL, Melvin P et al. Parent-reported errors and adverse events in hospitalized children. JAMA Pediatr. 2016;170(4):e154608.https://doi.org/10.1001/jamapediatrics.2015.4608.
19. Adair JG. The Hawthorne effect: a reconsideration of the methodological artifact. J Appl Psychol. 1984;69(2):334-345. https://doi.org/10.1037/0021-9010.69.2.334.
20. Kovacs-Litman A, Wong K, Shojania KG, et al. Do physicians clean their hands? Insights from a covert observational study. J Hosp Med. 2016;11(12):862-864. https://doi.org/10.1002/jhm.2632.
21. Wolfe F, Michaud K. The Hawthorne effect, sponsored trials, and the overestimation of treatment effectiveness. J Rheumatol. 2010;37(11):2216-2220. https://doi.org/10.3899/jrheum.100497.
22. Kahneman D. Thinking, Fast and Slow. 1st Pbk. ed. New York: Farrar, Straus and Giroux; 2013.
1. Schondelmeyer AC, Bonafide CP, Goel VV, et al. The frequency of physiologic monitor alarms in a children’s hospital. J Hosp Med. 2016;11(11):796-798. https://doi.org/10.1002/jhm.2612.
2. Schondelmeyer AC, Brady PW, Goel VV, et al. Physiologic monitor alarm rates at 5 children’s hospitals. J Hosp Med. 2018;13(6):396-398. https://doi.org/10.12788/jhm.2918.
3. Schondelmeyer AC, Brady PW, Sucharew H, et al. The impact of reduced pulse oximetry use on alarm frequency. Hosp Pediatr. In press. PubMed
4. Bonafide CP, Lin R, Zander M, et al. Association between exposure to nonactionable physiologic monitor alarms and response time in a children’s hospital. J Hosp Med. 2015;10(6):345-351. https://doi.org/10.1002/jhm.2331.
5. Siebig S, Kuhls S, Imhoff M, et al. Intensive care unit alarms--how many do we need? Crit Care Med. 2010;38(2):451-456. https://doi.org/10.1097/CCM.0b013e3181cb0888.
6. Sendelbach S, Funk M. Alarm fatigue: a patient safety concern. AACN Adv Crit Care. 2013;24(4):378-386. https://doi.org/10.1097/NCI.0b013e3182a903f9.
7. Sendelbach S. Alarm fatigue. Nurs Clin North Am. 2012;47(3):375-382. https://doi.org/10.1016/j.cnur.2012.05.009.
8. Cvach M. Monitor alarm fatigue: an integrative review. Biomed Instrum Technol. 2012;46(4):268-277. https://doi.org/10.2345/0899-8205-46.4.268.
9. Paine CW, Goel VV, Ely E, et al. Systematic review of physiologic monitor alarm characteristics and pragmatic interventions to reduce alarm frequency. J Hosp Med. 2016;11(2):136-144. https://doi.org/10.1002/jhm.2520.
10. Voepel-Lewis T, Parker ML, Burke CN, et al. Pulse oximetry desaturation alarms on a general postoperative adult unit: a prospective observational study of nurse response time. Int J Nurs Stud. 2013;50(10):1351-1358. https://doi.org/10.1016/j.ijnurstu.2013.02.006.
11. Bonafide CP, Localio AR, Holmes JH, et al. Video analysis of factors associated With response time to physiologic monitor alarms in a children’s hospital. JAMA Pediatr. 2017;171(6):524-531. https://doi.org/10.1001/jamapediatrics.2016.5123.
12. Deb S, Claudio D. Alarm fatigue and its influence on staff performance. IIE Trans Healthc Syst Eng. 2015;5(3):183-196. https://doi.org/10.1080/19488300.2015.1062065.
13. Mondor TA, Hurlburt J, Thorne L. Categorizing sounds by pitch: effects of stimulus similarity and response repetition. Percept Psychophys. 2003;65(1):107-114. https://doi.org/10.3758/BF03194787.
14. Mondor TA, Finley GA. The perceived urgency of auditory warning alarms used in the hospital operating room is inappropriate. Can J Anaesth. 2003;50(3):221-228. https://doi.org/10.1007/BF03017788.
15. Fusch PI, Ness LR. Are we there yet? Data saturation in qualitative research. Qual Rep; 20(9), 2015:1408-1416.
16. Najafi N, Auerbach A. Use and outcomes of telemetry monitoring on a medicine service. Arch Intern Med. 2012;172(17):1349-1350. https://doi.org/10.1001/archinternmed.2012.3163.
17. Estrada CA, Rosman HS, Prasad NK, et al. Role of telemetry monitoring in the non-intensive care unit. Am J Cardiol. 1995;76(12):960-965. https://doi.org/10.1016/S0002-9149(99)80270-7.
18. Khan A, Furtak SL, Melvin P et al. Parent-reported errors and adverse events in hospitalized children. JAMA Pediatr. 2016;170(4):e154608.https://doi.org/10.1001/jamapediatrics.2015.4608.
19. Adair JG. The Hawthorne effect: a reconsideration of the methodological artifact. J Appl Psychol. 1984;69(2):334-345. https://doi.org/10.1037/0021-9010.69.2.334.
20. Kovacs-Litman A, Wong K, Shojania KG, et al. Do physicians clean their hands? Insights from a covert observational study. J Hosp Med. 2016;11(12):862-864. https://doi.org/10.1002/jhm.2632.
21. Wolfe F, Michaud K. The Hawthorne effect, sponsored trials, and the overestimation of treatment effectiveness. J Rheumatol. 2010;37(11):2216-2220. https://doi.org/10.3899/jrheum.100497.
22. Kahneman D. Thinking, Fast and Slow. 1st Pbk. ed. New York: Farrar, Straus and Giroux; 2013.
© 2019 Society of Hospital Medicine
Early Warning Systems: The Neglected Importance of Timing
Automated early warning systems (EWSs) use data inputs to recognize clinical states requiring time-sensitive intervention and then generate notifications through different modalities to clinicians. EWSs serve as common tools for improving the recognition and treatment of important clinical states such as sepsis. However, despite the early enthusiasm, these warning systems have often yielded disappointing outcomes. In sepsis, for example, EWSs have shown mixed results in clinical trials, and concerns regarding the overuse of EWSs in diagnosing sepsis have grown.1-4 We argue that inattention to the importance of timing in EWS training and evaluation provides one reason that EWSs have underperformed. Thus, to improve care, a warning system must not only identify the clinical state accurately, but it must also do so in a sufficiently timely manner to implement the associated interventions, such as administration of antibiotics for sepsis. Although the literature has occasionally highlighted the importance of timing in electronic surveillance systems, no one has linked the temporal dependence of performance metrics and intervention feasibility to the failure of such warning systems and explained how to operationalize timing in their development.5-8 Using sepsis as an example, we explain why timing is important and propose new metrics and strategies for training and evaluating EWS models. EWSs are divided into two types: detection systems that recognize critical illnesses at a particular moment and prediction systems that estimate risk of deterioration over varying time frames.9 We focus primarily on detection systems, but our analysis is also important for prediction systems, which we will discuss in the last section.
CLINICAL TIME ZERO AND POSITIVE PREDICTIVE VALUE
EWS metrics have evolved from focusing on crude measures of discrimination to more clinically relevant metrics, such as the positive predictive value (PPV). The common performance metrics, including the c-statistic, evaluate the performance of EWSs in distinguishing events from nonevents, such as the presence or absence of sepsis in hospitalized patients. However, the c-statistic does not account for disease prevalence. A given c-statistic is compatible with a wide range of PPVs; a low PPV may limit an EWS’s usefulness to promote interventions and generate increased alert fatigue.10
However, the PPV, although important, provides no information on the timing of state recognition in relation to clinical time zero. Time zero is the first moment at which a critical state can be recognized based on available data and current medical science. Different approaches, including laboratory values, clinical assessments, retrospective chart reviews, triage times, and others, have been used to measure time zero.8,11-13 All these approaches feature advantages and disadvantages; the evaluation of timing will exhibit sensitivity to the approach used.14 Further work is needed to gain additional insights into the measurement of time zero.
Just as the same c-statistic is consistent with varying PPVs, so too is the same PPV consistent with different timing in relation to clinical time zero (Figure). An alert-level PPV of 50% indicates that 50% of the alerts signify true cases of sepsis. However, such a value could also indicate any of the following:
a) 50% true cases of sepsis, with a mean time of 35 minutes after clinical time zero;
b) 50% true cases, with a mean time of 60 minutes before clinical time zero (prediction EWS);
c) 50% true cases of sepsis, with a mean time of 1.3 days since clinical time zero, but with 70% of these cases undiagnosed at the time of EWS detection;
d) 50% true cases of cases, with mean time of 1.3 days since clinical time zero, that is, all cases among those promptly detected and treated through routine clinician oversight.
Each of these situations features differing clinical utility to help meet the hospital objective of increasing early administration of antibiotics. More generally, three dimensions of timing are important for detection systems. The first dimension is the timing of detection relative to time zero. The second is the timing relative to ”real-world” clinician detection. The third is timing with respect to the associated clinical objective. For a given PPV, an EWS performs better when detecting a state (1) at, near, or in advance of time zero, (2) prior to clinician detection, and (3) sufficiently in advance of an operational objective to promote change. On the other hand, when an EWS consistently sends alerts after clinician action, it serves a lesser purpose and risks causing alert fatigue; such cases have been described in studies.15
OPERATIONALIZING TIMING IN EWS TRAINING AND EVALUATION
Acknowledging the importance of timing features implications for researchers and health system leaders. Researchers who develop EWS should include how these systems perform relative to both time zero and critical milestones in the clinical course. Operational leadership should understand the trade-offs that occur between alert fatigue (through lower PPV at the margin with earlier detection) and lead time to implement an intervention. Navigating these trade-offs involves a complex organizational decision. The “number needed to evaluate” is one way to quantify this fatigue factor.16 Such a measure gives a sense of the number of cases a clinician will need to evaluate per event. Collaborations between clinical leadership, operational leadership, and data scientists are needed to determine how to evaluate individual systems.
A good metric should capture the three important dimensions of timing while retaining intuitiveness to clinicians and leadership. One graphical option involves plotting the PPVs over time and relative to the clinical state evolution (Figure). This PPV-over-time curve shows when true positives occur relative to the time course of sepsis, including the three major dimensions of timing. This curve can also show a “clinically important window (CIW)”, which is bounded on the right by the latest point in time when recognition could still meet the clinical objective. For sepsis, the curve might be bounded at 2.5 hours to meet an objective of antibiotics within three hours, with the assumption that 0.5 hour is needed for a response. For detection systems, the window would be bounded on the left by clinical time zero. The graph can also designate the point when most cases of sepsis have been recognized clinically with historical data. The Figure depicts an example curve for a detection model.
The metrics derived from this curve may be used alongside the PPV for training and evaluation. Often, adjusting the PPV for its relationship to time zero and the CIW will aid in recognizing the existence of a time beyond which detection fails to help achieve the intended intervention. Detection beyond the window should not credited as a true positive if it fails to facilitate the objective. One option is to credit detection at or before time zero as one and discount later detection by the delay from time zero. More specifically, a true positive could be discounted by the difference between the end of the CIW and the moment of detection divided by the CIW length. This discounted PPV could be displayed alongside the PPV to gauge the temporal dimension of performance and be used for training.
The use of timing places additional demands on validation owing to the need for a time-based gold standard. In such a case, the unit of analysis in system development might not be the patient encounter but rather the patient-hour or patient-15-minute epoch, depending on how frequently the EWS updates risk information and may alert. By contrast, the sepsis detection models used in administrative databases rely on an encounter-level PPV, which provides more limited information compared with real-time EWSs.17 When time zero cannot be measured, alternatives may be used to capture several dimensions of timing; these alternatives include measurement of the percentage of cases that recognize the event prior to clinicians.15
MOVING TOWARD PREDICTION
Detection systems face the limitation that they lack the capability to identify a state before its occurrence. Prediction systems are more likely to be actionable, as they provide more lead time for intervention, but accurate prediction models are also more difficult to develop. With a predictive system, an additional dimension of timing becomes important: the time horizon for prediction. Prediction models may be trained to recognize a state within a specific time frame (eg, 6, 12, or 24 hours), and test characteristics, including PPV, may vary with the window.18 A given PPV (of eventual development of sepsis) is compatible with varying time windows and thus again lacks important information on performance.
The timing relative to clinical time zero remains important for prediction. For a predictive EWS, the graph in the figure may be expected to shift to the left. Models with good performance will occasionally send an alert after time zero. For a prediction system with a time horizon of six hours, it is more useful to have alerts occur a mean time of four hours prior to time zero than four minutes prior.
CONCLUSION
Improving the clinical utility of EWSs requires better measurement of timing. Researchers should incorporate timing into system development, and operational leaders should be cognizant of timing during implementation. Specific steps should include devising better strategies to estimate the relationship of state recognition to clinical time zero and developing methods to discount recognition when it occurs too late to be actionable.
Disclosures
Dr. Rolnick is a consultant to Tuple Health, Inc. and was previously a part-time employee of Acumen, LLC. Dr. Weissman has nothing to disclose.
1. The Lancet Respiratory Medicine. Crying wolf: the growing fatigue around sepsis alerts. Lancet Respir Med. 2018;6(3):161. doi: 10.1016/S2213-2600(18)30072-9.
2. Hooper MH, Weavind L, Wheeler AP, et al. Randomized trial of automated, electronic monitoring to facilitate early detection of sepsis in the intensive care unit. Crit Care Med. 2012;40(7):2096-2101. doi: 10.1097/CCM.0b013e318250a887. PubMed
3. Nelson JL, Smith BL, Jared JD, et al. Prospective trial of real-time electronic surveillance to expedite early care of severe sepsis. Ann Emerg Med. 2011;57(5):500-504. doi: 10.1016/j.annemergmed.2010.12.008. PubMed
4. Umscheid CA, Betesh J, VanZandbergen C, et al. Development, implementation, and impact of an automated early warning and response system for sepsis. J Hosp Med. 2015;10(1):26-31. doi: 10.1002/jhm.2259. PubMed
5. Kleinman KP, Abrams AM. Assessing surveillance using sensitivity, specificity and timeliness. Stat Methods Med Res. 2006;15(5):445-464. doi: 10.1177/0962280206071641. PubMed
6. Jiang X, Cooper GF, Neill DB. Generalized AMOC curves for evaluation and improvement of event surveillance. AMIA Annu Symp Proc. 2009;281-285. PubMed
7. Futoma J, Hariharan S, Sendak M, et al. An improved multi-output Gaussian process RNN with real-time validation for early sepsis detection. In Proceedings of the 2nd Machine Learning for Healthcare Conference (MLHC), Boston, MA, Aug 2017.
8. Rolnick J, Downing N, Shepard J, et al. Validation of test performance and clinical time zero for an electronic health record embedded severe sepsis alert. Appl Clin Inform. 2016;7(2):560-572. doi: 10.4338/ACI-2015-11-RA-0159. PubMed
9. DeVita MA, Smith GB, Adam SK, et al. “Identifying the hospitalised patient in crisis”—A consensus conference on the afferent limb of rapid response systems. Resuscitation. 2010;81(4):375-382. doi: 10.1016/j.resuscitation.2009.12.008. PubMed
10. Romero-Brufau S, Huddleston JM, Escobar GJ, et al. Why the C-statistic is not informative to evaluate early warning scores and what metrics to use. Crit Care. 2015;19(1):284-290. doi: 10.1186/s13054-015-0999-1. PubMed
11. Evans IVR, Phillips GS, Alpern ER, et al. Association between the New York sepsis care mandate and in-hospital mortality for pediatric sepsis. JAMA. 2018;320(4):358-367. doi: 10.1001/jama.2018.9071. PubMed
12. Daniels R, Nutbeam T, McNamara G, et al. The sepsis six and the severe sepsis resuscitation bundle: a prospective observational cohort study. Emerg Med J. 2011;28(6):507-512. doi: 10.1136/emj.2010.095067. PubMed
13. Paul R, Melendez E, Wathen B, et al. A quality improvement collaborative for pediatric sepsis: lessons learned. Pediatr Qual Saf. 2018;3(1):1-8. doi: 10.1097/pq9.0000000000000051. PubMed
14. Rhee C, Brown SR, Jones TM, et al. Variability in determining sepsis time zero and bundle compliance rates for the centers for medicare and medicaid services SEP-1 measure. Infect Control Hosp Epidemiol. 2018;39(9):994-996. doi: 10.1017/ice.2018.134. PubMed
15. Winter MC, Kubis S, Bonafide CP. Beyond reporting early warning score sensitivity: the temporal relationship and clinical relevance of “true positive” alerts that precede critical deterioration. J Hosp Med. 2019;14(3):138-143. doi: 10.12788/jhm.3066. PubMed
1 6. Dummett BA, Adams C, Scruth E, et al. Incorporating an early detection system into routine clinical practice in two community hospitals: Incorporating an EWS into practice. J Hosp Med. 2016;11(51):S25-S31. doi: 10.1002/jhm.2661. PubMed
17. Jolley RJ, Quan H, Jetté N, et al. Validation and optimisation of an ICD-10-coded case definition for sepsis using administrative health data. BMJ Open. 2015;5(12):e009487. doi: 10.1136/bmjopen-2015-009487. PubMed
18. Wellner B, Grand J, Canzone E, et al. Predicting unplanned transfers to the intensive care unit: a machine learning approach leveraging diverse clinical elements. JMIR Med Inform. 2017;5(4):e45. doi: 10.2196/medinform.8680. PubMed
Automated early warning systems (EWSs) use data inputs to recognize clinical states requiring time-sensitive intervention and then generate notifications through different modalities to clinicians. EWSs serve as common tools for improving the recognition and treatment of important clinical states such as sepsis. However, despite the early enthusiasm, these warning systems have often yielded disappointing outcomes. In sepsis, for example, EWSs have shown mixed results in clinical trials, and concerns regarding the overuse of EWSs in diagnosing sepsis have grown.1-4 We argue that inattention to the importance of timing in EWS training and evaluation provides one reason that EWSs have underperformed. Thus, to improve care, a warning system must not only identify the clinical state accurately, but it must also do so in a sufficiently timely manner to implement the associated interventions, such as administration of antibiotics for sepsis. Although the literature has occasionally highlighted the importance of timing in electronic surveillance systems, no one has linked the temporal dependence of performance metrics and intervention feasibility to the failure of such warning systems and explained how to operationalize timing in their development.5-8 Using sepsis as an example, we explain why timing is important and propose new metrics and strategies for training and evaluating EWS models. EWSs are divided into two types: detection systems that recognize critical illnesses at a particular moment and prediction systems that estimate risk of deterioration over varying time frames.9 We focus primarily on detection systems, but our analysis is also important for prediction systems, which we will discuss in the last section.
CLINICAL TIME ZERO AND POSITIVE PREDICTIVE VALUE
EWS metrics have evolved from focusing on crude measures of discrimination to more clinically relevant metrics, such as the positive predictive value (PPV). The common performance metrics, including the c-statistic, evaluate the performance of EWSs in distinguishing events from nonevents, such as the presence or absence of sepsis in hospitalized patients. However, the c-statistic does not account for disease prevalence. A given c-statistic is compatible with a wide range of PPVs; a low PPV may limit an EWS’s usefulness to promote interventions and generate increased alert fatigue.10
However, the PPV, although important, provides no information on the timing of state recognition in relation to clinical time zero. Time zero is the first moment at which a critical state can be recognized based on available data and current medical science. Different approaches, including laboratory values, clinical assessments, retrospective chart reviews, triage times, and others, have been used to measure time zero.8,11-13 All these approaches feature advantages and disadvantages; the evaluation of timing will exhibit sensitivity to the approach used.14 Further work is needed to gain additional insights into the measurement of time zero.
Just as the same c-statistic is consistent with varying PPVs, so too is the same PPV consistent with different timing in relation to clinical time zero (Figure). An alert-level PPV of 50% indicates that 50% of the alerts signify true cases of sepsis. However, such a value could also indicate any of the following:
a) 50% true cases of sepsis, with a mean time of 35 minutes after clinical time zero;
b) 50% true cases, with a mean time of 60 minutes before clinical time zero (prediction EWS);
c) 50% true cases of sepsis, with a mean time of 1.3 days since clinical time zero, but with 70% of these cases undiagnosed at the time of EWS detection;
d) 50% true cases of cases, with mean time of 1.3 days since clinical time zero, that is, all cases among those promptly detected and treated through routine clinician oversight.
Each of these situations features differing clinical utility to help meet the hospital objective of increasing early administration of antibiotics. More generally, three dimensions of timing are important for detection systems. The first dimension is the timing of detection relative to time zero. The second is the timing relative to ”real-world” clinician detection. The third is timing with respect to the associated clinical objective. For a given PPV, an EWS performs better when detecting a state (1) at, near, or in advance of time zero, (2) prior to clinician detection, and (3) sufficiently in advance of an operational objective to promote change. On the other hand, when an EWS consistently sends alerts after clinician action, it serves a lesser purpose and risks causing alert fatigue; such cases have been described in studies.15
OPERATIONALIZING TIMING IN EWS TRAINING AND EVALUATION
Acknowledging the importance of timing features implications for researchers and health system leaders. Researchers who develop EWS should include how these systems perform relative to both time zero and critical milestones in the clinical course. Operational leadership should understand the trade-offs that occur between alert fatigue (through lower PPV at the margin with earlier detection) and lead time to implement an intervention. Navigating these trade-offs involves a complex organizational decision. The “number needed to evaluate” is one way to quantify this fatigue factor.16 Such a measure gives a sense of the number of cases a clinician will need to evaluate per event. Collaborations between clinical leadership, operational leadership, and data scientists are needed to determine how to evaluate individual systems.
A good metric should capture the three important dimensions of timing while retaining intuitiveness to clinicians and leadership. One graphical option involves plotting the PPVs over time and relative to the clinical state evolution (Figure). This PPV-over-time curve shows when true positives occur relative to the time course of sepsis, including the three major dimensions of timing. This curve can also show a “clinically important window (CIW)”, which is bounded on the right by the latest point in time when recognition could still meet the clinical objective. For sepsis, the curve might be bounded at 2.5 hours to meet an objective of antibiotics within three hours, with the assumption that 0.5 hour is needed for a response. For detection systems, the window would be bounded on the left by clinical time zero. The graph can also designate the point when most cases of sepsis have been recognized clinically with historical data. The Figure depicts an example curve for a detection model.
The metrics derived from this curve may be used alongside the PPV for training and evaluation. Often, adjusting the PPV for its relationship to time zero and the CIW will aid in recognizing the existence of a time beyond which detection fails to help achieve the intended intervention. Detection beyond the window should not credited as a true positive if it fails to facilitate the objective. One option is to credit detection at or before time zero as one and discount later detection by the delay from time zero. More specifically, a true positive could be discounted by the difference between the end of the CIW and the moment of detection divided by the CIW length. This discounted PPV could be displayed alongside the PPV to gauge the temporal dimension of performance and be used for training.
The use of timing places additional demands on validation owing to the need for a time-based gold standard. In such a case, the unit of analysis in system development might not be the patient encounter but rather the patient-hour or patient-15-minute epoch, depending on how frequently the EWS updates risk information and may alert. By contrast, the sepsis detection models used in administrative databases rely on an encounter-level PPV, which provides more limited information compared with real-time EWSs.17 When time zero cannot be measured, alternatives may be used to capture several dimensions of timing; these alternatives include measurement of the percentage of cases that recognize the event prior to clinicians.15
MOVING TOWARD PREDICTION
Detection systems face the limitation that they lack the capability to identify a state before its occurrence. Prediction systems are more likely to be actionable, as they provide more lead time for intervention, but accurate prediction models are also more difficult to develop. With a predictive system, an additional dimension of timing becomes important: the time horizon for prediction. Prediction models may be trained to recognize a state within a specific time frame (eg, 6, 12, or 24 hours), and test characteristics, including PPV, may vary with the window.18 A given PPV (of eventual development of sepsis) is compatible with varying time windows and thus again lacks important information on performance.
The timing relative to clinical time zero remains important for prediction. For a predictive EWS, the graph in the figure may be expected to shift to the left. Models with good performance will occasionally send an alert after time zero. For a prediction system with a time horizon of six hours, it is more useful to have alerts occur a mean time of four hours prior to time zero than four minutes prior.
CONCLUSION
Improving the clinical utility of EWSs requires better measurement of timing. Researchers should incorporate timing into system development, and operational leaders should be cognizant of timing during implementation. Specific steps should include devising better strategies to estimate the relationship of state recognition to clinical time zero and developing methods to discount recognition when it occurs too late to be actionable.
Disclosures
Dr. Rolnick is a consultant to Tuple Health, Inc. and was previously a part-time employee of Acumen, LLC. Dr. Weissman has nothing to disclose.
Automated early warning systems (EWSs) use data inputs to recognize clinical states requiring time-sensitive intervention and then generate notifications through different modalities to clinicians. EWSs serve as common tools for improving the recognition and treatment of important clinical states such as sepsis. However, despite the early enthusiasm, these warning systems have often yielded disappointing outcomes. In sepsis, for example, EWSs have shown mixed results in clinical trials, and concerns regarding the overuse of EWSs in diagnosing sepsis have grown.1-4 We argue that inattention to the importance of timing in EWS training and evaluation provides one reason that EWSs have underperformed. Thus, to improve care, a warning system must not only identify the clinical state accurately, but it must also do so in a sufficiently timely manner to implement the associated interventions, such as administration of antibiotics for sepsis. Although the literature has occasionally highlighted the importance of timing in electronic surveillance systems, no one has linked the temporal dependence of performance metrics and intervention feasibility to the failure of such warning systems and explained how to operationalize timing in their development.5-8 Using sepsis as an example, we explain why timing is important and propose new metrics and strategies for training and evaluating EWS models. EWSs are divided into two types: detection systems that recognize critical illnesses at a particular moment and prediction systems that estimate risk of deterioration over varying time frames.9 We focus primarily on detection systems, but our analysis is also important for prediction systems, which we will discuss in the last section.
CLINICAL TIME ZERO AND POSITIVE PREDICTIVE VALUE
EWS metrics have evolved from focusing on crude measures of discrimination to more clinically relevant metrics, such as the positive predictive value (PPV). The common performance metrics, including the c-statistic, evaluate the performance of EWSs in distinguishing events from nonevents, such as the presence or absence of sepsis in hospitalized patients. However, the c-statistic does not account for disease prevalence. A given c-statistic is compatible with a wide range of PPVs; a low PPV may limit an EWS’s usefulness to promote interventions and generate increased alert fatigue.10
However, the PPV, although important, provides no information on the timing of state recognition in relation to clinical time zero. Time zero is the first moment at which a critical state can be recognized based on available data and current medical science. Different approaches, including laboratory values, clinical assessments, retrospective chart reviews, triage times, and others, have been used to measure time zero.8,11-13 All these approaches feature advantages and disadvantages; the evaluation of timing will exhibit sensitivity to the approach used.14 Further work is needed to gain additional insights into the measurement of time zero.
Just as the same c-statistic is consistent with varying PPVs, so too is the same PPV consistent with different timing in relation to clinical time zero (Figure). An alert-level PPV of 50% indicates that 50% of the alerts signify true cases of sepsis. However, such a value could also indicate any of the following:
a) 50% true cases of sepsis, with a mean time of 35 minutes after clinical time zero;
b) 50% true cases, with a mean time of 60 minutes before clinical time zero (prediction EWS);
c) 50% true cases of sepsis, with a mean time of 1.3 days since clinical time zero, but with 70% of these cases undiagnosed at the time of EWS detection;
d) 50% true cases of cases, with mean time of 1.3 days since clinical time zero, that is, all cases among those promptly detected and treated through routine clinician oversight.
Each of these situations features differing clinical utility to help meet the hospital objective of increasing early administration of antibiotics. More generally, three dimensions of timing are important for detection systems. The first dimension is the timing of detection relative to time zero. The second is the timing relative to ”real-world” clinician detection. The third is timing with respect to the associated clinical objective. For a given PPV, an EWS performs better when detecting a state (1) at, near, or in advance of time zero, (2) prior to clinician detection, and (3) sufficiently in advance of an operational objective to promote change. On the other hand, when an EWS consistently sends alerts after clinician action, it serves a lesser purpose and risks causing alert fatigue; such cases have been described in studies.15
OPERATIONALIZING TIMING IN EWS TRAINING AND EVALUATION
Acknowledging the importance of timing features implications for researchers and health system leaders. Researchers who develop EWS should include how these systems perform relative to both time zero and critical milestones in the clinical course. Operational leadership should understand the trade-offs that occur between alert fatigue (through lower PPV at the margin with earlier detection) and lead time to implement an intervention. Navigating these trade-offs involves a complex organizational decision. The “number needed to evaluate” is one way to quantify this fatigue factor.16 Such a measure gives a sense of the number of cases a clinician will need to evaluate per event. Collaborations between clinical leadership, operational leadership, and data scientists are needed to determine how to evaluate individual systems.
A good metric should capture the three important dimensions of timing while retaining intuitiveness to clinicians and leadership. One graphical option involves plotting the PPVs over time and relative to the clinical state evolution (Figure). This PPV-over-time curve shows when true positives occur relative to the time course of sepsis, including the three major dimensions of timing. This curve can also show a “clinically important window (CIW)”, which is bounded on the right by the latest point in time when recognition could still meet the clinical objective. For sepsis, the curve might be bounded at 2.5 hours to meet an objective of antibiotics within three hours, with the assumption that 0.5 hour is needed for a response. For detection systems, the window would be bounded on the left by clinical time zero. The graph can also designate the point when most cases of sepsis have been recognized clinically with historical data. The Figure depicts an example curve for a detection model.
The metrics derived from this curve may be used alongside the PPV for training and evaluation. Often, adjusting the PPV for its relationship to time zero and the CIW will aid in recognizing the existence of a time beyond which detection fails to help achieve the intended intervention. Detection beyond the window should not credited as a true positive if it fails to facilitate the objective. One option is to credit detection at or before time zero as one and discount later detection by the delay from time zero. More specifically, a true positive could be discounted by the difference between the end of the CIW and the moment of detection divided by the CIW length. This discounted PPV could be displayed alongside the PPV to gauge the temporal dimension of performance and be used for training.
The use of timing places additional demands on validation owing to the need for a time-based gold standard. In such a case, the unit of analysis in system development might not be the patient encounter but rather the patient-hour or patient-15-minute epoch, depending on how frequently the EWS updates risk information and may alert. By contrast, the sepsis detection models used in administrative databases rely on an encounter-level PPV, which provides more limited information compared with real-time EWSs.17 When time zero cannot be measured, alternatives may be used to capture several dimensions of timing; these alternatives include measurement of the percentage of cases that recognize the event prior to clinicians.15
MOVING TOWARD PREDICTION
Detection systems face the limitation that they lack the capability to identify a state before its occurrence. Prediction systems are more likely to be actionable, as they provide more lead time for intervention, but accurate prediction models are also more difficult to develop. With a predictive system, an additional dimension of timing becomes important: the time horizon for prediction. Prediction models may be trained to recognize a state within a specific time frame (eg, 6, 12, or 24 hours), and test characteristics, including PPV, may vary with the window.18 A given PPV (of eventual development of sepsis) is compatible with varying time windows and thus again lacks important information on performance.
The timing relative to clinical time zero remains important for prediction. For a predictive EWS, the graph in the figure may be expected to shift to the left. Models with good performance will occasionally send an alert after time zero. For a prediction system with a time horizon of six hours, it is more useful to have alerts occur a mean time of four hours prior to time zero than four minutes prior.
CONCLUSION
Improving the clinical utility of EWSs requires better measurement of timing. Researchers should incorporate timing into system development, and operational leaders should be cognizant of timing during implementation. Specific steps should include devising better strategies to estimate the relationship of state recognition to clinical time zero and developing methods to discount recognition when it occurs too late to be actionable.
Disclosures
Dr. Rolnick is a consultant to Tuple Health, Inc. and was previously a part-time employee of Acumen, LLC. Dr. Weissman has nothing to disclose.
1. The Lancet Respiratory Medicine. Crying wolf: the growing fatigue around sepsis alerts. Lancet Respir Med. 2018;6(3):161. doi: 10.1016/S2213-2600(18)30072-9.
2. Hooper MH, Weavind L, Wheeler AP, et al. Randomized trial of automated, electronic monitoring to facilitate early detection of sepsis in the intensive care unit. Crit Care Med. 2012;40(7):2096-2101. doi: 10.1097/CCM.0b013e318250a887. PubMed
3. Nelson JL, Smith BL, Jared JD, et al. Prospective trial of real-time electronic surveillance to expedite early care of severe sepsis. Ann Emerg Med. 2011;57(5):500-504. doi: 10.1016/j.annemergmed.2010.12.008. PubMed
4. Umscheid CA, Betesh J, VanZandbergen C, et al. Development, implementation, and impact of an automated early warning and response system for sepsis. J Hosp Med. 2015;10(1):26-31. doi: 10.1002/jhm.2259. PubMed
5. Kleinman KP, Abrams AM. Assessing surveillance using sensitivity, specificity and timeliness. Stat Methods Med Res. 2006;15(5):445-464. doi: 10.1177/0962280206071641. PubMed
6. Jiang X, Cooper GF, Neill DB. Generalized AMOC curves for evaluation and improvement of event surveillance. AMIA Annu Symp Proc. 2009;281-285. PubMed
7. Futoma J, Hariharan S, Sendak M, et al. An improved multi-output Gaussian process RNN with real-time validation for early sepsis detection. In Proceedings of the 2nd Machine Learning for Healthcare Conference (MLHC), Boston, MA, Aug 2017.
8. Rolnick J, Downing N, Shepard J, et al. Validation of test performance and clinical time zero for an electronic health record embedded severe sepsis alert. Appl Clin Inform. 2016;7(2):560-572. doi: 10.4338/ACI-2015-11-RA-0159. PubMed
9. DeVita MA, Smith GB, Adam SK, et al. “Identifying the hospitalised patient in crisis”—A consensus conference on the afferent limb of rapid response systems. Resuscitation. 2010;81(4):375-382. doi: 10.1016/j.resuscitation.2009.12.008. PubMed
10. Romero-Brufau S, Huddleston JM, Escobar GJ, et al. Why the C-statistic is not informative to evaluate early warning scores and what metrics to use. Crit Care. 2015;19(1):284-290. doi: 10.1186/s13054-015-0999-1. PubMed
11. Evans IVR, Phillips GS, Alpern ER, et al. Association between the New York sepsis care mandate and in-hospital mortality for pediatric sepsis. JAMA. 2018;320(4):358-367. doi: 10.1001/jama.2018.9071. PubMed
12. Daniels R, Nutbeam T, McNamara G, et al. The sepsis six and the severe sepsis resuscitation bundle: a prospective observational cohort study. Emerg Med J. 2011;28(6):507-512. doi: 10.1136/emj.2010.095067. PubMed
13. Paul R, Melendez E, Wathen B, et al. A quality improvement collaborative for pediatric sepsis: lessons learned. Pediatr Qual Saf. 2018;3(1):1-8. doi: 10.1097/pq9.0000000000000051. PubMed
14. Rhee C, Brown SR, Jones TM, et al. Variability in determining sepsis time zero and bundle compliance rates for the centers for medicare and medicaid services SEP-1 measure. Infect Control Hosp Epidemiol. 2018;39(9):994-996. doi: 10.1017/ice.2018.134. PubMed
15. Winter MC, Kubis S, Bonafide CP. Beyond reporting early warning score sensitivity: the temporal relationship and clinical relevance of “true positive” alerts that precede critical deterioration. J Hosp Med. 2019;14(3):138-143. doi: 10.12788/jhm.3066. PubMed
1 6. Dummett BA, Adams C, Scruth E, et al. Incorporating an early detection system into routine clinical practice in two community hospitals: Incorporating an EWS into practice. J Hosp Med. 2016;11(51):S25-S31. doi: 10.1002/jhm.2661. PubMed
17. Jolley RJ, Quan H, Jetté N, et al. Validation and optimisation of an ICD-10-coded case definition for sepsis using administrative health data. BMJ Open. 2015;5(12):e009487. doi: 10.1136/bmjopen-2015-009487. PubMed
18. Wellner B, Grand J, Canzone E, et al. Predicting unplanned transfers to the intensive care unit: a machine learning approach leveraging diverse clinical elements. JMIR Med Inform. 2017;5(4):e45. doi: 10.2196/medinform.8680. PubMed
1. The Lancet Respiratory Medicine. Crying wolf: the growing fatigue around sepsis alerts. Lancet Respir Med. 2018;6(3):161. doi: 10.1016/S2213-2600(18)30072-9.
2. Hooper MH, Weavind L, Wheeler AP, et al. Randomized trial of automated, electronic monitoring to facilitate early detection of sepsis in the intensive care unit. Crit Care Med. 2012;40(7):2096-2101. doi: 10.1097/CCM.0b013e318250a887. PubMed
3. Nelson JL, Smith BL, Jared JD, et al. Prospective trial of real-time electronic surveillance to expedite early care of severe sepsis. Ann Emerg Med. 2011;57(5):500-504. doi: 10.1016/j.annemergmed.2010.12.008. PubMed
4. Umscheid CA, Betesh J, VanZandbergen C, et al. Development, implementation, and impact of an automated early warning and response system for sepsis. J Hosp Med. 2015;10(1):26-31. doi: 10.1002/jhm.2259. PubMed
5. Kleinman KP, Abrams AM. Assessing surveillance using sensitivity, specificity and timeliness. Stat Methods Med Res. 2006;15(5):445-464. doi: 10.1177/0962280206071641. PubMed
6. Jiang X, Cooper GF, Neill DB. Generalized AMOC curves for evaluation and improvement of event surveillance. AMIA Annu Symp Proc. 2009;281-285. PubMed
7. Futoma J, Hariharan S, Sendak M, et al. An improved multi-output Gaussian process RNN with real-time validation for early sepsis detection. In Proceedings of the 2nd Machine Learning for Healthcare Conference (MLHC), Boston, MA, Aug 2017.
8. Rolnick J, Downing N, Shepard J, et al. Validation of test performance and clinical time zero for an electronic health record embedded severe sepsis alert. Appl Clin Inform. 2016;7(2):560-572. doi: 10.4338/ACI-2015-11-RA-0159. PubMed
9. DeVita MA, Smith GB, Adam SK, et al. “Identifying the hospitalised patient in crisis”—A consensus conference on the afferent limb of rapid response systems. Resuscitation. 2010;81(4):375-382. doi: 10.1016/j.resuscitation.2009.12.008. PubMed
10. Romero-Brufau S, Huddleston JM, Escobar GJ, et al. Why the C-statistic is not informative to evaluate early warning scores and what metrics to use. Crit Care. 2015;19(1):284-290. doi: 10.1186/s13054-015-0999-1. PubMed
11. Evans IVR, Phillips GS, Alpern ER, et al. Association between the New York sepsis care mandate and in-hospital mortality for pediatric sepsis. JAMA. 2018;320(4):358-367. doi: 10.1001/jama.2018.9071. PubMed
12. Daniels R, Nutbeam T, McNamara G, et al. The sepsis six and the severe sepsis resuscitation bundle: a prospective observational cohort study. Emerg Med J. 2011;28(6):507-512. doi: 10.1136/emj.2010.095067. PubMed
13. Paul R, Melendez E, Wathen B, et al. A quality improvement collaborative for pediatric sepsis: lessons learned. Pediatr Qual Saf. 2018;3(1):1-8. doi: 10.1097/pq9.0000000000000051. PubMed
14. Rhee C, Brown SR, Jones TM, et al. Variability in determining sepsis time zero and bundle compliance rates for the centers for medicare and medicaid services SEP-1 measure. Infect Control Hosp Epidemiol. 2018;39(9):994-996. doi: 10.1017/ice.2018.134. PubMed
15. Winter MC, Kubis S, Bonafide CP. Beyond reporting early warning score sensitivity: the temporal relationship and clinical relevance of “true positive” alerts that precede critical deterioration. J Hosp Med. 2019;14(3):138-143. doi: 10.12788/jhm.3066. PubMed
1 6. Dummett BA, Adams C, Scruth E, et al. Incorporating an early detection system into routine clinical practice in two community hospitals: Incorporating an EWS into practice. J Hosp Med. 2016;11(51):S25-S31. doi: 10.1002/jhm.2661. PubMed
17. Jolley RJ, Quan H, Jetté N, et al. Validation and optimisation of an ICD-10-coded case definition for sepsis using administrative health data. BMJ Open. 2015;5(12):e009487. doi: 10.1136/bmjopen-2015-009487. PubMed
18. Wellner B, Grand J, Canzone E, et al. Predicting unplanned transfers to the intensive care unit: a machine learning approach leveraging diverse clinical elements. JMIR Med Inform. 2017;5(4):e45. doi: 10.2196/medinform.8680. PubMed
© 2019 Society of Hospital Medicine
“Just Getting a Cup of Coffee”—Considering Best Practices for Patients’ Movement off the Hospital Floor
A 58-year-old man with a remote history of endocarditis and no prior injection drug use was admitted to the inpatient medicine service with fever and concern for recurrent endocarditis. A transthoracic echocardiogram was unremarkable and the patient remained clinically stable. A transesophageal echocardiogram (TEE) was scheduled for the following morning, but during nursing rounds, the patient was missing from his room. Multiple staff members searched for the patient and eventually located him in the hospital lobby drinking a cup of coffee purchased from the cafeteria. Despite his opposition, he was escorted back to his room and advised to not leave the floor again. Later that day, the patient became frustrated and left the hospital before his scheduled TEE. He was subsequently lost to follow-up.
INTRODUCTION
Patients are admitted to the hospital based upon a medical determination that the patient requires acute observation, evaluation, or treatment. Once admitted, healthcare providers may impose restrictions on the patient’s movement in the hospital, such as restrictions on leaving their assigned floor. Managing the movement of hospitalized patients poses significant challenges for the clinical staff because of the difficulty of providing a treatment environment that ensures safe and efficient delivery of care while promoting patients’ preferences for an unrestrictive environment that respects their independence.1,2 Broad limits may make it easier for staff to care for patients and reduce concerns about liability, but they may also frustrate patients who may be medically, psychiatrically, and physically stable and do not require stringent monitoring (eg, completing a course of intravenous antibiotics or awaiting placement at outside facilities).
Although this issue has broad implications for patient safety and hospital liability, authoritative guidance and evidence-based literature are lacking. Without clear guidelines, healthcare staff members are likely to spend more time in managing each individual request to leave the floor because they do not have a systematic strategy for making fair and consistent decisions. Here, we describe the patient and institutional considerations when managing patient movement in the hospital. We refer to “patient movement” specifically as a patient’s choice to move to different locations within the hospital, but outside of their assigned room and/or floor. This does not include scheduled, supervised ambulation activities, such as physical therapy.
POTENTIAL CONSEQUENCES OF LIBERALIZING AND RESTRICTING INPATIENT MOVEMENT
Practices that promote patient movement offer significant benefits and risks. Enhancing movement is likely to reduce the “physiologic disruption”3 of hospitalization while improving patients’ overall satisfaction and alignment with patient-centered care. Liberalized movement also promotes independence and ambulation that reduces the rate of physical deconditioning.4
Despite theoretical benefits, hospitals may be more concerned about adverse events related to patient movement, such as falls, the use of illicit substances, or elopement. Given that hospitals may be legally5 and financially responsible6 for adverse events associated with patient movement, allowances for off-floor movement should be carefully considered with input from risk management, physicians, nursing leadership, patient advocates, and hospital administration.
Additionally, unannounced movement off the floor may interfere with timely and efficient care by causing lapses in monitoring, such as cardiac telemetry,7 medication administration, and scheduled diagnostic tests. In these situations, the risks of patient absence from the floor are significant and may ultimately negate the benefits of continued hospitalization by compromising the central elements of patient care.
CLINICAL CONSIDERATIONS
Patients’ requests to leave the hospital floor should be evaluated systemically and transparently to promote fair, high-value care. First, a request for liberalized movement should prompt physicians that the patient may no longer require hospitalization and may be ready for the transition to outpatient care.8 If the patient still requires inpatient care, then the medical practitioner should make a clinical determination if the patient is medically stable enough to leave their hospital floor. The provider should first identify when the liberalization of movement would be universally inappropriate, such as in patients who are physically unable to ambulate without posing significant harm to themselves. This includes an accidental fall (usually while walking5), which is one of the most commonly reported adverse events in an inpatient setting.9 Additionally, patients with significant cognitive impairments or those lacking in decision-making capacity may be restricted from leaving their floors unescorted, as they are at a higher risk of disorientation, falls, and death.10
In determining movement restrictions for patients in isolation, hospitals should refer to the existing guidelines on isolation precautions for the transmission of communicable infections11,12 and neutropenic precautions.13 Additionally, movement restriction for patients who are isolated after screening positive for certain drug-resistant organisms (eg, methicillin-resistant Staphylococcus aureus and vancomycin-resistant enterococci) is controversial and should be evaluated based on the available medical evidence and standards.14-16
When making a risk-benefit determination about movement, providers should also assess the intent and the potentially unmet needs behind the patient’s request. Patient-centered reasons for enhanced freedom of movement within the hospital include a desire for exercise, greater food choice, and visiting with loved ones, all of which can enable patients to manage the well-known inconveniences and stresses of hospitalization. In contrast, there may be concerns for other intentions behind leaving assigned floors based on the patient’s clinical history, such as the surreptitious use of illicit substances or attempts to elope from the hospital. Advising restriction of movement is justifiable if there is a significant concern for behavior that undermines the safe delivery of care. In patients with active substance use disorders, the appropriate treatment of pain or withdrawal symptoms may better address the patients’ unmet needs, but a lower threshold to restrict movement may be reasonable given the significant risks involved. However, given the widespread stigmatization of patients with substance use disorders,17 institutional policy and clinicians should adhere to systematic, transparent, and consistent risk assessments for all patients in order to minimize the potential for introducing or exacerbating disparities in care.
ETHICAL CONSIDERATIONS
In order to work productively with admitted patients, strong practices honor patients’ autonomy by specifying
Patients may request or even demand to leave the floor after a healthcare provider has determined that doing so would be unsafe and/or undermine the timely and efficient delivery of care. In these cases, shared decision-making (SDM) can help identify acceptable solutions within the identified constraints. SDM combines the physicians’ experience, expertise, and knowledge of medical evidence with patients’ values, needs, and preferences for care.19 If patients continue to request to leave the floor after the restriction has been communicated, physicians should discuss whether the current treatment plan should be renegotiated to include a relatively minor modification (eg, a change in the timing or route of administration of medication). If inpatient care cannot be provided safely within the patient’s preferences for movement and attempts to accommodate the patient’s preferences are unsuccessful, then a shift to discharge planning may be appropriate. A summary of this decision process is outlined in the Figure.
Of note, physicians’ decisions about the appropriateness of patient movement could conflict with the existing institutional procedures or policies (eg, a physician deems increased patient movement to carry minimal risks, while the institution seeks to restrict movement due to concerns about liability). For this reason, it is important for clinicians to participate in the development of institutional policy to ensure that it reflects the clinical and ethical considerations that clinicians apply to patient care. A policy designed with input from relevant stakeholders across the institution including legal, nursing, physicians, administration, ethics, risk management, and patient advocates can provide expert guidance that is based on and consistent with the institution’s mission, values, and priorities.20
ENHANCING SAFE MOVEMENT
In mitigating the burdens of restriction on movement, hospitals may implement a range of options that address patients’ preferences while maintaining safety. Given the potential consequences of liberalized patient movement, it may be prudent to implement these safeguards as a compromise that addresses both the patients’ needs and the hospital’s concerns. These could include an escort for off-floor supervision, timed passes to leave the floor, or volunteers purchasing food for patients from the cafeteria. Creating open, supervised spaces within the hospital (eg, lounges) may also help provide the respite patients need, but in a safe and medically structured environment.
CONCLUSION
Returning to the introductory case example, we now present an alternative outcome in the context of the practices described above. On the morning of the scheduled TEE, a nurse noted that the patient was missing from his room. Before the staff began searching for the patient, they consulted the medical record which included the admission discussion and agreement to expectations for inpatient movement. The record also included an informed consent discussion indicating the minimal risks of leaving the floor, as the patient could ambulate independently and had no need for continuous monitoring. Finally, a physician’s order authorized the patient to be off the floor until 10
The above scenario highlights the benefits of a comprehensive framework for patient movement practices that are transparent, fair, and systematic. Explicitly recognizing competing institutional and patient perspectives can prevent conflict and promote high-quality, safe, efficient, patient-centered care that only restricts the patient’s movement under specified and justifiable conditions. In developing strong hospital practices, institutions should refer to the relevant clinical and ethical standards and draw upon their institutional resources in risk management, clinical staff, and patient advocates.
Acknowledgments
The authors thank Dr. Neil Shapiro and Dr. David Chuquin for their constructive reviews of prior versions of this manuscript.
Disclosures
The authors have no financial conflicts of interest to disclose.
Disclaimer
The views expressed in this article are those of the authors and do not necessarily reflect the position or policy of the U.S. Department of Veterans Affairs, the US Government, or the VA National Center for Ethics in Health Care.
1. Smith T. Wandering off the floors: safety and security risks of patient wandering. PSNet Patient Safety Network. Web M&M 2014. Accessed December 4, 2017.
2. Douglas CH, Douglas MR. Patient-friendly hospital environments: exploring the patients’ perspective. Health Expect. 2004;7(1):61-73. https://doi.org/10.1046/j.1369-6513.2003.00251.x.
3. Detsky AS, Krumholz HM. Reducing the trauma of hospitalization. JAMA. 2014;311(21):2169-2170. https://doi.org/10.1001/jama.2014.3695
4. Covinsky KE, Pierluissi E, Johnston CB. Hospitalization-associated disability: “She was probably able to ambulate, but I’m not sure.” JAMA. 2011;306(16):1782-1793. https://doi.org/10.1001/jama.2011.1556.
5. Oliver D, Killick S, Even T, Willmott M. Do falls and falls-injuries in hospital indicate negligent care-and how big is the risk? A retrospective analysis of the NHS Litigation Authority Database of clinical negligence claims, resulting from falls in hospitals in England 1995 to 2006. Qual Saf Health Care. 2008;17(6):431-436. https://doi.org/10.1136/qshc.2007.024703.
6. Mello MM, Chandra A, Gawande AA, Studdert DM. National costs of the medical liability system. Health Aff (Millwood). 2010;29(9):1569-1577. https://doi.org/10.1377/hlthaff.2009.0807.
7. Dressler R, Dryer MM, Coletti C, Mahoney D, Doorey AJ. Altering overuse of cardiac telemetry in non-intensive care unit settings by hardwiring the use of American Heart Association guidelines. JAMA Intern Med. 2014;174(11):1852-1854. https://doi.org/10.1001/jamainternmed.2014.4491.
8. Conley J, O’Brien CW, Leff BA, Bolen S, Zulman D. Alternative strategies to inpatient hospitalization for acute medical conditions: a systematic review. JAMA Intern Med. 2016;176(11):1693-1702. https://doi.org/10.1001/jamainternmed.2016.5974.
9. Halfon P, Eggli Y, Van Melle G, Vagnair A. Risk of falls for hospitalized patients: a predictive model based on routinely available data. J Clin Epidemiol. 2001;54(12):1258-1266. https://doi.org/10.1016/S0895-4356(01)00406-1
10. Rowe M. Wandering in hospitalized older adults: identifying risk is the first step in this approach to preventing wandering in patients with dementia. Am J Nurs. 2008;108(10):62-70. https://doi.org/10.1097/01.NAJ.0000336968.32462.c9.
11. Siegel JD, Rhinehart E, Jackson M, Chiarello L. Health care infection control practices advisory C. 2007 Guideline for isolation precautions: preventing transmission of infectious agents in health care settings. Am J Infect Control. 2007;35(10 Suppl 2):S65-S164. https://doi.org/10.1016/j.ajic.2007.10.007
12. Ito Y, Nagao M, Iinuma Y, et al. Risk factors for nosocomial tuberculosis transmission among health care workers. Am J Infect Control. 2016;44(5):596-598. https://doi.org/10.1016/j.ajic.2015.11.022.
13. Freifeld AG, Bow EJ, Sepkowitz KA, et al. Clinical practice guideline for the use of antimicrobial agents in neutropenic patients with cancer: 2010 update by the infectious diseases society of america. Clin Infect Dis. 2011;52(4):e56-e93. https://doi.org/10.1093/cid/ciq147
14. Martin EM, Russell D, Rubin Z, et al. Elimination of routine contact precautions for endemic methicillin-resistant staphylococcus aureus and vancomycin-resistant enterococcus: a retrospective quasi-experimental study. Infect Control Hosp Epidemiol. 2016;37(11):1323-1330. https://doi.org/10.1017/ice.2016.156
15. Morgan DJ, Murthy R, Munoz-Price LS, et al. Reconsidering contact precautions for endemic methicillin-resistant Staphylococcus aureus and vancomycin-resistant Enterococcus. Infect Control Hosp Epidemiol. 2015;36(10):1163-1172. https://doi.org/10.1017/ice.2015.156.
16. Fatkenheuer G, Hirschel B, Harbarth S. Screening and isolation to control meticillin-resistant Staphylococcus aureus: sense, nonsense, and evidence. Lancet. 2015;385(9973):1146-1149. https://doi.org/10.1016/S0140-6736(14)60660-7.
17. van Boekel LC, Brouwers EP, van Weeghel J, Garretsen HF. Stigma among health professionals towards patients with substance use disorders and its consequences for healthcare delivery: systematic review. Drug Alcohol Depend. 2013;131(1-2):23-35. https://doi.org/10.1016/j.drugalcdep.2013.02.018.
18. Handel DA, Fu R, Daya M, York J, Larson E, John McConnell K. The use of scripting at triage and its impact on elopements. Acad Emerg Med. 2010;17(5):495-500. https://doi.org/10.1111/j.1553-2712.2010.00721.x.
19. Barry MJ, Edgman-Levitan S. Shared decision making-pinnacle of patient-centered care. N Engl J Med. 2012;366(9):780-781. https://doi.org/10.1056/NEJMp1109283.
20. Donn SM. Medical liability, risk management, and the quality of health care. Semin Fetal Neonatal Med. 2005;10(1):3-9. https://doi.org/10.1016/j.siny.2004.09.004.
A 58-year-old man with a remote history of endocarditis and no prior injection drug use was admitted to the inpatient medicine service with fever and concern for recurrent endocarditis. A transthoracic echocardiogram was unremarkable and the patient remained clinically stable. A transesophageal echocardiogram (TEE) was scheduled for the following morning, but during nursing rounds, the patient was missing from his room. Multiple staff members searched for the patient and eventually located him in the hospital lobby drinking a cup of coffee purchased from the cafeteria. Despite his opposition, he was escorted back to his room and advised to not leave the floor again. Later that day, the patient became frustrated and left the hospital before his scheduled TEE. He was subsequently lost to follow-up.
INTRODUCTION
Patients are admitted to the hospital based upon a medical determination that the patient requires acute observation, evaluation, or treatment. Once admitted, healthcare providers may impose restrictions on the patient’s movement in the hospital, such as restrictions on leaving their assigned floor. Managing the movement of hospitalized patients poses significant challenges for the clinical staff because of the difficulty of providing a treatment environment that ensures safe and efficient delivery of care while promoting patients’ preferences for an unrestrictive environment that respects their independence.1,2 Broad limits may make it easier for staff to care for patients and reduce concerns about liability, but they may also frustrate patients who may be medically, psychiatrically, and physically stable and do not require stringent monitoring (eg, completing a course of intravenous antibiotics or awaiting placement at outside facilities).
Although this issue has broad implications for patient safety and hospital liability, authoritative guidance and evidence-based literature are lacking. Without clear guidelines, healthcare staff members are likely to spend more time in managing each individual request to leave the floor because they do not have a systematic strategy for making fair and consistent decisions. Here, we describe the patient and institutional considerations when managing patient movement in the hospital. We refer to “patient movement” specifically as a patient’s choice to move to different locations within the hospital, but outside of their assigned room and/or floor. This does not include scheduled, supervised ambulation activities, such as physical therapy.
POTENTIAL CONSEQUENCES OF LIBERALIZING AND RESTRICTING INPATIENT MOVEMENT
Practices that promote patient movement offer significant benefits and risks. Enhancing movement is likely to reduce the “physiologic disruption”3 of hospitalization while improving patients’ overall satisfaction and alignment with patient-centered care. Liberalized movement also promotes independence and ambulation that reduces the rate of physical deconditioning.4
Despite theoretical benefits, hospitals may be more concerned about adverse events related to patient movement, such as falls, the use of illicit substances, or elopement. Given that hospitals may be legally5 and financially responsible6 for adverse events associated with patient movement, allowances for off-floor movement should be carefully considered with input from risk management, physicians, nursing leadership, patient advocates, and hospital administration.
Additionally, unannounced movement off the floor may interfere with timely and efficient care by causing lapses in monitoring, such as cardiac telemetry,7 medication administration, and scheduled diagnostic tests. In these situations, the risks of patient absence from the floor are significant and may ultimately negate the benefits of continued hospitalization by compromising the central elements of patient care.
CLINICAL CONSIDERATIONS
Patients’ requests to leave the hospital floor should be evaluated systemically and transparently to promote fair, high-value care. First, a request for liberalized movement should prompt physicians that the patient may no longer require hospitalization and may be ready for the transition to outpatient care.8 If the patient still requires inpatient care, then the medical practitioner should make a clinical determination if the patient is medically stable enough to leave their hospital floor. The provider should first identify when the liberalization of movement would be universally inappropriate, such as in patients who are physically unable to ambulate without posing significant harm to themselves. This includes an accidental fall (usually while walking5), which is one of the most commonly reported adverse events in an inpatient setting.9 Additionally, patients with significant cognitive impairments or those lacking in decision-making capacity may be restricted from leaving their floors unescorted, as they are at a higher risk of disorientation, falls, and death.10
In determining movement restrictions for patients in isolation, hospitals should refer to the existing guidelines on isolation precautions for the transmission of communicable infections11,12 and neutropenic precautions.13 Additionally, movement restriction for patients who are isolated after screening positive for certain drug-resistant organisms (eg, methicillin-resistant Staphylococcus aureus and vancomycin-resistant enterococci) is controversial and should be evaluated based on the available medical evidence and standards.14-16
When making a risk-benefit determination about movement, providers should also assess the intent and the potentially unmet needs behind the patient’s request. Patient-centered reasons for enhanced freedom of movement within the hospital include a desire for exercise, greater food choice, and visiting with loved ones, all of which can enable patients to manage the well-known inconveniences and stresses of hospitalization. In contrast, there may be concerns for other intentions behind leaving assigned floors based on the patient’s clinical history, such as the surreptitious use of illicit substances or attempts to elope from the hospital. Advising restriction of movement is justifiable if there is a significant concern for behavior that undermines the safe delivery of care. In patients with active substance use disorders, the appropriate treatment of pain or withdrawal symptoms may better address the patients’ unmet needs, but a lower threshold to restrict movement may be reasonable given the significant risks involved. However, given the widespread stigmatization of patients with substance use disorders,17 institutional policy and clinicians should adhere to systematic, transparent, and consistent risk assessments for all patients in order to minimize the potential for introducing or exacerbating disparities in care.
ETHICAL CONSIDERATIONS
In order to work productively with admitted patients, strong practices honor patients’ autonomy by specifying
Patients may request or even demand to leave the floor after a healthcare provider has determined that doing so would be unsafe and/or undermine the timely and efficient delivery of care. In these cases, shared decision-making (SDM) can help identify acceptable solutions within the identified constraints. SDM combines the physicians’ experience, expertise, and knowledge of medical evidence with patients’ values, needs, and preferences for care.19 If patients continue to request to leave the floor after the restriction has been communicated, physicians should discuss whether the current treatment plan should be renegotiated to include a relatively minor modification (eg, a change in the timing or route of administration of medication). If inpatient care cannot be provided safely within the patient’s preferences for movement and attempts to accommodate the patient’s preferences are unsuccessful, then a shift to discharge planning may be appropriate. A summary of this decision process is outlined in the Figure.
Of note, physicians’ decisions about the appropriateness of patient movement could conflict with the existing institutional procedures or policies (eg, a physician deems increased patient movement to carry minimal risks, while the institution seeks to restrict movement due to concerns about liability). For this reason, it is important for clinicians to participate in the development of institutional policy to ensure that it reflects the clinical and ethical considerations that clinicians apply to patient care. A policy designed with input from relevant stakeholders across the institution including legal, nursing, physicians, administration, ethics, risk management, and patient advocates can provide expert guidance that is based on and consistent with the institution’s mission, values, and priorities.20
ENHANCING SAFE MOVEMENT
In mitigating the burdens of restriction on movement, hospitals may implement a range of options that address patients’ preferences while maintaining safety. Given the potential consequences of liberalized patient movement, it may be prudent to implement these safeguards as a compromise that addresses both the patients’ needs and the hospital’s concerns. These could include an escort for off-floor supervision, timed passes to leave the floor, or volunteers purchasing food for patients from the cafeteria. Creating open, supervised spaces within the hospital (eg, lounges) may also help provide the respite patients need, but in a safe and medically structured environment.
CONCLUSION
Returning to the introductory case example, we now present an alternative outcome in the context of the practices described above. On the morning of the scheduled TEE, a nurse noted that the patient was missing from his room. Before the staff began searching for the patient, they consulted the medical record which included the admission discussion and agreement to expectations for inpatient movement. The record also included an informed consent discussion indicating the minimal risks of leaving the floor, as the patient could ambulate independently and had no need for continuous monitoring. Finally, a physician’s order authorized the patient to be off the floor until 10
The above scenario highlights the benefits of a comprehensive framework for patient movement practices that are transparent, fair, and systematic. Explicitly recognizing competing institutional and patient perspectives can prevent conflict and promote high-quality, safe, efficient, patient-centered care that only restricts the patient’s movement under specified and justifiable conditions. In developing strong hospital practices, institutions should refer to the relevant clinical and ethical standards and draw upon their institutional resources in risk management, clinical staff, and patient advocates.
Acknowledgments
The authors thank Dr. Neil Shapiro and Dr. David Chuquin for their constructive reviews of prior versions of this manuscript.
Disclosures
The authors have no financial conflicts of interest to disclose.
Disclaimer
The views expressed in this article are those of the authors and do not necessarily reflect the position or policy of the U.S. Department of Veterans Affairs, the US Government, or the VA National Center for Ethics in Health Care.
A 58-year-old man with a remote history of endocarditis and no prior injection drug use was admitted to the inpatient medicine service with fever and concern for recurrent endocarditis. A transthoracic echocardiogram was unremarkable and the patient remained clinically stable. A transesophageal echocardiogram (TEE) was scheduled for the following morning, but during nursing rounds, the patient was missing from his room. Multiple staff members searched for the patient and eventually located him in the hospital lobby drinking a cup of coffee purchased from the cafeteria. Despite his opposition, he was escorted back to his room and advised to not leave the floor again. Later that day, the patient became frustrated and left the hospital before his scheduled TEE. He was subsequently lost to follow-up.
INTRODUCTION
Patients are admitted to the hospital based upon a medical determination that the patient requires acute observation, evaluation, or treatment. Once admitted, healthcare providers may impose restrictions on the patient’s movement in the hospital, such as restrictions on leaving their assigned floor. Managing the movement of hospitalized patients poses significant challenges for the clinical staff because of the difficulty of providing a treatment environment that ensures safe and efficient delivery of care while promoting patients’ preferences for an unrestrictive environment that respects their independence.1,2 Broad limits may make it easier for staff to care for patients and reduce concerns about liability, but they may also frustrate patients who may be medically, psychiatrically, and physically stable and do not require stringent monitoring (eg, completing a course of intravenous antibiotics or awaiting placement at outside facilities).
Although this issue has broad implications for patient safety and hospital liability, authoritative guidance and evidence-based literature are lacking. Without clear guidelines, healthcare staff members are likely to spend more time in managing each individual request to leave the floor because they do not have a systematic strategy for making fair and consistent decisions. Here, we describe the patient and institutional considerations when managing patient movement in the hospital. We refer to “patient movement” specifically as a patient’s choice to move to different locations within the hospital, but outside of their assigned room and/or floor. This does not include scheduled, supervised ambulation activities, such as physical therapy.
POTENTIAL CONSEQUENCES OF LIBERALIZING AND RESTRICTING INPATIENT MOVEMENT
Practices that promote patient movement offer significant benefits and risks. Enhancing movement is likely to reduce the “physiologic disruption”3 of hospitalization while improving patients’ overall satisfaction and alignment with patient-centered care. Liberalized movement also promotes independence and ambulation that reduces the rate of physical deconditioning.4
Despite theoretical benefits, hospitals may be more concerned about adverse events related to patient movement, such as falls, the use of illicit substances, or elopement. Given that hospitals may be legally5 and financially responsible6 for adverse events associated with patient movement, allowances for off-floor movement should be carefully considered with input from risk management, physicians, nursing leadership, patient advocates, and hospital administration.
Additionally, unannounced movement off the floor may interfere with timely and efficient care by causing lapses in monitoring, such as cardiac telemetry,7 medication administration, and scheduled diagnostic tests. In these situations, the risks of patient absence from the floor are significant and may ultimately negate the benefits of continued hospitalization by compromising the central elements of patient care.
CLINICAL CONSIDERATIONS
Patients’ requests to leave the hospital floor should be evaluated systemically and transparently to promote fair, high-value care. First, a request for liberalized movement should prompt physicians that the patient may no longer require hospitalization and may be ready for the transition to outpatient care.8 If the patient still requires inpatient care, then the medical practitioner should make a clinical determination if the patient is medically stable enough to leave their hospital floor. The provider should first identify when the liberalization of movement would be universally inappropriate, such as in patients who are physically unable to ambulate without posing significant harm to themselves. This includes an accidental fall (usually while walking5), which is one of the most commonly reported adverse events in an inpatient setting.9 Additionally, patients with significant cognitive impairments or those lacking in decision-making capacity may be restricted from leaving their floors unescorted, as they are at a higher risk of disorientation, falls, and death.10
In determining movement restrictions for patients in isolation, hospitals should refer to the existing guidelines on isolation precautions for the transmission of communicable infections11,12 and neutropenic precautions.13 Additionally, movement restriction for patients who are isolated after screening positive for certain drug-resistant organisms (eg, methicillin-resistant Staphylococcus aureus and vancomycin-resistant enterococci) is controversial and should be evaluated based on the available medical evidence and standards.14-16
When making a risk-benefit determination about movement, providers should also assess the intent and the potentially unmet needs behind the patient’s request. Patient-centered reasons for enhanced freedom of movement within the hospital include a desire for exercise, greater food choice, and visiting with loved ones, all of which can enable patients to manage the well-known inconveniences and stresses of hospitalization. In contrast, there may be concerns for other intentions behind leaving assigned floors based on the patient’s clinical history, such as the surreptitious use of illicit substances or attempts to elope from the hospital. Advising restriction of movement is justifiable if there is a significant concern for behavior that undermines the safe delivery of care. In patients with active substance use disorders, the appropriate treatment of pain or withdrawal symptoms may better address the patients’ unmet needs, but a lower threshold to restrict movement may be reasonable given the significant risks involved. However, given the widespread stigmatization of patients with substance use disorders,17 institutional policy and clinicians should adhere to systematic, transparent, and consistent risk assessments for all patients in order to minimize the potential for introducing or exacerbating disparities in care.
ETHICAL CONSIDERATIONS
In order to work productively with admitted patients, strong practices honor patients’ autonomy by specifying
Patients may request or even demand to leave the floor after a healthcare provider has determined that doing so would be unsafe and/or undermine the timely and efficient delivery of care. In these cases, shared decision-making (SDM) can help identify acceptable solutions within the identified constraints. SDM combines the physicians’ experience, expertise, and knowledge of medical evidence with patients’ values, needs, and preferences for care.19 If patients continue to request to leave the floor after the restriction has been communicated, physicians should discuss whether the current treatment plan should be renegotiated to include a relatively minor modification (eg, a change in the timing or route of administration of medication). If inpatient care cannot be provided safely within the patient’s preferences for movement and attempts to accommodate the patient’s preferences are unsuccessful, then a shift to discharge planning may be appropriate. A summary of this decision process is outlined in the Figure.
Of note, physicians’ decisions about the appropriateness of patient movement could conflict with the existing institutional procedures or policies (eg, a physician deems increased patient movement to carry minimal risks, while the institution seeks to restrict movement due to concerns about liability). For this reason, it is important for clinicians to participate in the development of institutional policy to ensure that it reflects the clinical and ethical considerations that clinicians apply to patient care. A policy designed with input from relevant stakeholders across the institution including legal, nursing, physicians, administration, ethics, risk management, and patient advocates can provide expert guidance that is based on and consistent with the institution’s mission, values, and priorities.20
ENHANCING SAFE MOVEMENT
In mitigating the burdens of restriction on movement, hospitals may implement a range of options that address patients’ preferences while maintaining safety. Given the potential consequences of liberalized patient movement, it may be prudent to implement these safeguards as a compromise that addresses both the patients’ needs and the hospital’s concerns. These could include an escort for off-floor supervision, timed passes to leave the floor, or volunteers purchasing food for patients from the cafeteria. Creating open, supervised spaces within the hospital (eg, lounges) may also help provide the respite patients need, but in a safe and medically structured environment.
CONCLUSION
Returning to the introductory case example, we now present an alternative outcome in the context of the practices described above. On the morning of the scheduled TEE, a nurse noted that the patient was missing from his room. Before the staff began searching for the patient, they consulted the medical record which included the admission discussion and agreement to expectations for inpatient movement. The record also included an informed consent discussion indicating the minimal risks of leaving the floor, as the patient could ambulate independently and had no need for continuous monitoring. Finally, a physician’s order authorized the patient to be off the floor until 10
The above scenario highlights the benefits of a comprehensive framework for patient movement practices that are transparent, fair, and systematic. Explicitly recognizing competing institutional and patient perspectives can prevent conflict and promote high-quality, safe, efficient, patient-centered care that only restricts the patient’s movement under specified and justifiable conditions. In developing strong hospital practices, institutions should refer to the relevant clinical and ethical standards and draw upon their institutional resources in risk management, clinical staff, and patient advocates.
Acknowledgments
The authors thank Dr. Neil Shapiro and Dr. David Chuquin for their constructive reviews of prior versions of this manuscript.
Disclosures
The authors have no financial conflicts of interest to disclose.
Disclaimer
The views expressed in this article are those of the authors and do not necessarily reflect the position or policy of the U.S. Department of Veterans Affairs, the US Government, or the VA National Center for Ethics in Health Care.
1. Smith T. Wandering off the floors: safety and security risks of patient wandering. PSNet Patient Safety Network. Web M&M 2014. Accessed December 4, 2017.
2. Douglas CH, Douglas MR. Patient-friendly hospital environments: exploring the patients’ perspective. Health Expect. 2004;7(1):61-73. https://doi.org/10.1046/j.1369-6513.2003.00251.x.
3. Detsky AS, Krumholz HM. Reducing the trauma of hospitalization. JAMA. 2014;311(21):2169-2170. https://doi.org/10.1001/jama.2014.3695
4. Covinsky KE, Pierluissi E, Johnston CB. Hospitalization-associated disability: “She was probably able to ambulate, but I’m not sure.” JAMA. 2011;306(16):1782-1793. https://doi.org/10.1001/jama.2011.1556.
5. Oliver D, Killick S, Even T, Willmott M. Do falls and falls-injuries in hospital indicate negligent care-and how big is the risk? A retrospective analysis of the NHS Litigation Authority Database of clinical negligence claims, resulting from falls in hospitals in England 1995 to 2006. Qual Saf Health Care. 2008;17(6):431-436. https://doi.org/10.1136/qshc.2007.024703.
6. Mello MM, Chandra A, Gawande AA, Studdert DM. National costs of the medical liability system. Health Aff (Millwood). 2010;29(9):1569-1577. https://doi.org/10.1377/hlthaff.2009.0807.
7. Dressler R, Dryer MM, Coletti C, Mahoney D, Doorey AJ. Altering overuse of cardiac telemetry in non-intensive care unit settings by hardwiring the use of American Heart Association guidelines. JAMA Intern Med. 2014;174(11):1852-1854. https://doi.org/10.1001/jamainternmed.2014.4491.
8. Conley J, O’Brien CW, Leff BA, Bolen S, Zulman D. Alternative strategies to inpatient hospitalization for acute medical conditions: a systematic review. JAMA Intern Med. 2016;176(11):1693-1702. https://doi.org/10.1001/jamainternmed.2016.5974.
9. Halfon P, Eggli Y, Van Melle G, Vagnair A. Risk of falls for hospitalized patients: a predictive model based on routinely available data. J Clin Epidemiol. 2001;54(12):1258-1266. https://doi.org/10.1016/S0895-4356(01)00406-1
10. Rowe M. Wandering in hospitalized older adults: identifying risk is the first step in this approach to preventing wandering in patients with dementia. Am J Nurs. 2008;108(10):62-70. https://doi.org/10.1097/01.NAJ.0000336968.32462.c9.
11. Siegel JD, Rhinehart E, Jackson M, Chiarello L. Health care infection control practices advisory C. 2007 Guideline for isolation precautions: preventing transmission of infectious agents in health care settings. Am J Infect Control. 2007;35(10 Suppl 2):S65-S164. https://doi.org/10.1016/j.ajic.2007.10.007
12. Ito Y, Nagao M, Iinuma Y, et al. Risk factors for nosocomial tuberculosis transmission among health care workers. Am J Infect Control. 2016;44(5):596-598. https://doi.org/10.1016/j.ajic.2015.11.022.
13. Freifeld AG, Bow EJ, Sepkowitz KA, et al. Clinical practice guideline for the use of antimicrobial agents in neutropenic patients with cancer: 2010 update by the infectious diseases society of america. Clin Infect Dis. 2011;52(4):e56-e93. https://doi.org/10.1093/cid/ciq147
14. Martin EM, Russell D, Rubin Z, et al. Elimination of routine contact precautions for endemic methicillin-resistant staphylococcus aureus and vancomycin-resistant enterococcus: a retrospective quasi-experimental study. Infect Control Hosp Epidemiol. 2016;37(11):1323-1330. https://doi.org/10.1017/ice.2016.156
15. Morgan DJ, Murthy R, Munoz-Price LS, et al. Reconsidering contact precautions for endemic methicillin-resistant Staphylococcus aureus and vancomycin-resistant Enterococcus. Infect Control Hosp Epidemiol. 2015;36(10):1163-1172. https://doi.org/10.1017/ice.2015.156.
16. Fatkenheuer G, Hirschel B, Harbarth S. Screening and isolation to control meticillin-resistant Staphylococcus aureus: sense, nonsense, and evidence. Lancet. 2015;385(9973):1146-1149. https://doi.org/10.1016/S0140-6736(14)60660-7.
17. van Boekel LC, Brouwers EP, van Weeghel J, Garretsen HF. Stigma among health professionals towards patients with substance use disorders and its consequences for healthcare delivery: systematic review. Drug Alcohol Depend. 2013;131(1-2):23-35. https://doi.org/10.1016/j.drugalcdep.2013.02.018.
18. Handel DA, Fu R, Daya M, York J, Larson E, John McConnell K. The use of scripting at triage and its impact on elopements. Acad Emerg Med. 2010;17(5):495-500. https://doi.org/10.1111/j.1553-2712.2010.00721.x.
19. Barry MJ, Edgman-Levitan S. Shared decision making-pinnacle of patient-centered care. N Engl J Med. 2012;366(9):780-781. https://doi.org/10.1056/NEJMp1109283.
20. Donn SM. Medical liability, risk management, and the quality of health care. Semin Fetal Neonatal Med. 2005;10(1):3-9. https://doi.org/10.1016/j.siny.2004.09.004.
1. Smith T. Wandering off the floors: safety and security risks of patient wandering. PSNet Patient Safety Network. Web M&M 2014. Accessed December 4, 2017.
2. Douglas CH, Douglas MR. Patient-friendly hospital environments: exploring the patients’ perspective. Health Expect. 2004;7(1):61-73. https://doi.org/10.1046/j.1369-6513.2003.00251.x.
3. Detsky AS, Krumholz HM. Reducing the trauma of hospitalization. JAMA. 2014;311(21):2169-2170. https://doi.org/10.1001/jama.2014.3695
4. Covinsky KE, Pierluissi E, Johnston CB. Hospitalization-associated disability: “She was probably able to ambulate, but I’m not sure.” JAMA. 2011;306(16):1782-1793. https://doi.org/10.1001/jama.2011.1556.
5. Oliver D, Killick S, Even T, Willmott M. Do falls and falls-injuries in hospital indicate negligent care-and how big is the risk? A retrospective analysis of the NHS Litigation Authority Database of clinical negligence claims, resulting from falls in hospitals in England 1995 to 2006. Qual Saf Health Care. 2008;17(6):431-436. https://doi.org/10.1136/qshc.2007.024703.
6. Mello MM, Chandra A, Gawande AA, Studdert DM. National costs of the medical liability system. Health Aff (Millwood). 2010;29(9):1569-1577. https://doi.org/10.1377/hlthaff.2009.0807.
7. Dressler R, Dryer MM, Coletti C, Mahoney D, Doorey AJ. Altering overuse of cardiac telemetry in non-intensive care unit settings by hardwiring the use of American Heart Association guidelines. JAMA Intern Med. 2014;174(11):1852-1854. https://doi.org/10.1001/jamainternmed.2014.4491.
8. Conley J, O’Brien CW, Leff BA, Bolen S, Zulman D. Alternative strategies to inpatient hospitalization for acute medical conditions: a systematic review. JAMA Intern Med. 2016;176(11):1693-1702. https://doi.org/10.1001/jamainternmed.2016.5974.
9. Halfon P, Eggli Y, Van Melle G, Vagnair A. Risk of falls for hospitalized patients: a predictive model based on routinely available data. J Clin Epidemiol. 2001;54(12):1258-1266. https://doi.org/10.1016/S0895-4356(01)00406-1
10. Rowe M. Wandering in hospitalized older adults: identifying risk is the first step in this approach to preventing wandering in patients with dementia. Am J Nurs. 2008;108(10):62-70. https://doi.org/10.1097/01.NAJ.0000336968.32462.c9.
11. Siegel JD, Rhinehart E, Jackson M, Chiarello L. Health care infection control practices advisory C. 2007 Guideline for isolation precautions: preventing transmission of infectious agents in health care settings. Am J Infect Control. 2007;35(10 Suppl 2):S65-S164. https://doi.org/10.1016/j.ajic.2007.10.007
12. Ito Y, Nagao M, Iinuma Y, et al. Risk factors for nosocomial tuberculosis transmission among health care workers. Am J Infect Control. 2016;44(5):596-598. https://doi.org/10.1016/j.ajic.2015.11.022.
13. Freifeld AG, Bow EJ, Sepkowitz KA, et al. Clinical practice guideline for the use of antimicrobial agents in neutropenic patients with cancer: 2010 update by the infectious diseases society of america. Clin Infect Dis. 2011;52(4):e56-e93. https://doi.org/10.1093/cid/ciq147
14. Martin EM, Russell D, Rubin Z, et al. Elimination of routine contact precautions for endemic methicillin-resistant staphylococcus aureus and vancomycin-resistant enterococcus: a retrospective quasi-experimental study. Infect Control Hosp Epidemiol. 2016;37(11):1323-1330. https://doi.org/10.1017/ice.2016.156
15. Morgan DJ, Murthy R, Munoz-Price LS, et al. Reconsidering contact precautions for endemic methicillin-resistant Staphylococcus aureus and vancomycin-resistant Enterococcus. Infect Control Hosp Epidemiol. 2015;36(10):1163-1172. https://doi.org/10.1017/ice.2015.156.
16. Fatkenheuer G, Hirschel B, Harbarth S. Screening and isolation to control meticillin-resistant Staphylococcus aureus: sense, nonsense, and evidence. Lancet. 2015;385(9973):1146-1149. https://doi.org/10.1016/S0140-6736(14)60660-7.
17. van Boekel LC, Brouwers EP, van Weeghel J, Garretsen HF. Stigma among health professionals towards patients with substance use disorders and its consequences for healthcare delivery: systematic review. Drug Alcohol Depend. 2013;131(1-2):23-35. https://doi.org/10.1016/j.drugalcdep.2013.02.018.
18. Handel DA, Fu R, Daya M, York J, Larson E, John McConnell K. The use of scripting at triage and its impact on elopements. Acad Emerg Med. 2010;17(5):495-500. https://doi.org/10.1111/j.1553-2712.2010.00721.x.
19. Barry MJ, Edgman-Levitan S. Shared decision making-pinnacle of patient-centered care. N Engl J Med. 2012;366(9):780-781. https://doi.org/10.1056/NEJMp1109283.
20. Donn SM. Medical liability, risk management, and the quality of health care. Semin Fetal Neonatal Med. 2005;10(1):3-9. https://doi.org/10.1016/j.siny.2004.09.004.
© 2019 Society of Hospital Medicine