Hospital Medicine

Transthoracic echocardiography (TTE) is one of the most commonly ordered diagnostic tests in healthcare. Studies of Medicare beneficiaries, for example, have shown that each year, approximately 20% undergo at least 1 TTE, including 4% who have 2 or more.¹ TTE utilization rates increased dramatically in the 1990s and early 2000s. Between 1999 and 2008, for example, the rate of use of TTE per Medicare beneficiary nearly doubled.² In 2014, echocardiography accounted for 10% of all Medicare spending for imaging services, or approximately $930 million.³ In response to concerns about the possible unnecessary use of TTE, the American Heart Association and American Society of Echocardiography developed Appropriate Use Criteria (AUC) in 2007 and 2011, which describe appropriate versus inappropriate indications for TTE.⁴ Subsequent studies have shown that rather than rooting out inappropriate studies, the vast majority of ordered studies appear to be appropriate according to the AUC criteria.⁵ The AUC criteria have also been criticized for being based on expert opinion rather than clinical evidence.⁶ Repeat TTE, defined as TTE done within 1 year of a prior TTE, represents 24% to 42% of all studies,^7-9 and 31% of all Medicare beneficiaries who have a TTE get a repeat TTE within 1 year.¹⁰ In the present study, we reviewed all inpatient TTE performed over 1 year and described the group that have had a prior TTE within the past year (“repeat TTE”). We then derived a clinical prediction model to predict unchanged repeat TTE, with the goal of defining a subset of studies that are potentially unnecessary.

The West Haven Connecticut Veteran’s Administration Hospital (WHVA), located outside New Haven, Connecticut, is a 228-bed tertiary care center affiliated with Yale University School of Medicine. Potential subjects were identified from review of the electronic medical records of all inpatients who had an inpatient echocardiogram between October 1, 2013, and September 30, 2014. Patient’s records were reviewed by using a standardized data extraction form for demographics, comorbidity, cardiovascular risk factors, service ordering the TTE, intensive care unit (ICU) location, prior TTE abnormalities, TTE indication, AUC category, time between TTEs, technical quality of TTE, electrocardiogram (ECG) abnormalities, history of intervening acute coronary syndrome, cardiac surgery, and revascularization. Candidate predictors included any variables suspected by the authors as being potentially associated with the primary outcome of changed repeat TTE. All patients who had an inpatient TTE and a prior TTE within the Veterans Affairs (VA) system within the past year were included in the study. Repeat studies from the same admission were only counted as 1 TTE and patients had to have had a prior TTE from a different admission or a prior outpatient TTE to be included. Patients who did not have a prior TTE within the past year or who had only a transesophageal echocardiogram or stress echocardiography were excluded. Suboptimal studies were included but noted as limited quality. The study was approved by the WHVA Institutional Review Board. The Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis statement was used in planning and reporting this study.¹¹

TTEs were classified as normal, mildly abnormal, or with a major abnormality based on previously published definitions.^12-14 Any abnormality was defined as any left ventricle (LV) dysfunction (left ventricular ejection fraction [LVEF] <55%), any aortic or mitral valve stenosis, any regional wall motion abnormality, any right ventricular dysfunction, any pulmonary hypertension, mild or greater valvular regurgitation, any diastolic dysfunction, moderate or greater pericardial effusion, any ventricular hypertrophy, or any other significant abnormality including thrombus, vegetation, or tamponade. Major abnormality was defined as moderate or greater LV dysfunction (LVEF <45%), moderate or greater valvular regurgitation, moderate or greater valvular stenosis (aortic or mitral valve area <1.5 cm²), any regional wall motion abnormality, right ventricular dysfunction, moderate or greater pulmonary hypertension, moderate or greater diastolic dysfunction, moderate or greater pericardial effusion, or any other major abnormality including thrombus, vegetation, tumor, or tamponade. Repeat TTEs were classified as changed or unchanged. Changed TTEs were divided into any new abnormality or improvement or a new major abnormality or improvement. Any new abnormality or improvement was defined as any new TTE abnormality that had not previously been described or in which there was a change of at least 1 severity grade from a prior TTE, including improvement by 1 grade. A new major TTE abnormality or improvement was defined as any new major TTE abnormality that had previously been normal, or if there had been a prior abnormality, a change in at least 1 severity grade for LVEF or 2 severity grades for abnormal valvular, pericardial, or prior pulmonary hypertension, including improvement by 2 severity grades. A change from mild to moderate mitral regurgitation therefore was classified as a nonmajor change, whereas a change from mild to severe was classified as major. All TTE classifications were based on the electronic TTE reports and were reviewed by 2 independent investigators (CG and JC) blinded to the patients’ other clinical characteristics. For TTE studies in which the investigators agreed, that determination was the final classification. Disagreements were reviewed and the final classification was determined by consensus.

In an analogous manner, ECGs were classified as normal, mildly abnormal, or with a major abnormality based on previous definitions in the literature.¹⁵ Major abnormality was defined as atrial fibrillation or flutter, high-degree atrioventricular blocks, left bundle-branch block, right bundle-branch block, indeterminate conduction delay, q-wave myocardial infarction, isolated ischemic abnormalities, left ventricular hypertrophy with ST-T abnormalities, other arrhythmias including supraventricular tachycardia (SVT) or ventricular tachycardia (VT), low voltage (peak-to-peak QRS amplitude of <5 mm in the limb leads and/or <10 mm in the precordial leads), paced rhythm, sinus tachycardia (heart rate [HR] >100) or bradycardia (HR <50). Mild ECG abnormality was defined as low-grade atrioventricular blocks, borderline prolonged ventricular excitation, prolonged ventricular repolarization, isolated minor Q and ST-T abnormalities, left ventricular hypertrophy without ST-T abnormalities, left atrial enlargement, atrial or ventricular premature beats, or fascicular blocks. New major ECG abnormalities were any of the listed major ECG abnormalities that were not present on ECGs prior to the admission during which the repeat TTE was performed.

Other study definitions included intervening acute myocardial infarction (AMI), which was defined by any intervening history of elevated troponins, regardless of symptoms or ECG changes and including demand ischemia. Chronic kidney disease (CKD) was defined as an abnormal serum creatinine on 2 or more occasions 3 months apart. Active cancer was defined as receiving chemotherapy or palliative care for advanced cancer. Valvular heart disease was defined as prior moderate or severe valvular stenosis or regurgitation.

For analysis, we first compared patients with repeat TTE with major changes with those without major changes. For comparison of dichotomous variables, χ² or Fisher exact tests were used. For continuous variables, Student t test or the Mann-Whitney U test were performed. Because many of the frequencies of individual AUC criteria were small, related AUC criteria were grouped for analysis as grouped by the tables of the American College of Cardiology Foundation Appropriate Use Criteria Task Force, American Society of Echocardiography, American Heart Association, American Society of Nuclear Cardiology, Heart Failure Society of America, Heart Rhythm Society, Society for Cardiovascular Angiography and Interventions, Society of Critical Care Medicine, Society of Cardiovascular Computed Tomography, and Society for Cardiovascular Magnetic Resonance (ACCF/ASE/AHA) Guideline.⁴ Criteria groupings that were significantly less likely to have major TTE changes on analysis were classified as low risk and criteria that were significantly more likely were classified as high risk. Criteria groupings that were not significantly associated with TTE change were classified as average risk. All variables with P values less than 0.05 on bivariate analysis were then entered into a multivariate logistic regression analysis with major TTE change as the dependent variable, using backward stepwise variable selection with entry and exit criteria of P < 0.05 and P > 0.10, respectively. Scores were derived by converting the regression coefficients of independently predictive variables in the logistic regression model into corresponding integers. A total score was calculated for each patient by summing up the points for each independently significant variable. Model performance was described by calculating a C statistic by creation of a receiver operating characteristic curve to assess discrimination, and by performing the Hosmer and Lemeshow test to assess calibration. Internal validation was assessed by calculating the C statistic using the statistical method of bootstrapping in which the data were resampled multiple times (n = 200) and the average resultant C statistic reported. The bootstrap analysis was performed using R version 3.1 (R Foundation for Statistical Computing, Vienna, Austria). All other analyses were performed using SPSS version 21.0 (IBM, Armonk, New York). P values <0.05 were considered significant.

During the 1-year study period, there were 3944 medical/surgical admissions for 3266 patients and 845 inpatient TTEs obtained on 601 patients. Of all patients who were admitted, 601/3266 (18.4%) had at least 1 inpatient TTE. Of these 601 TTEs, 211 (35%) had a TTE within the VA system during the prior year. Of the 211 repeat TTEs, 67 (32%) were unchanged, 66 (31%) had minor changes, and 78 (37%) had major changes. The kappa statistic for agreement between extractors for “major TTE change” was 0.91, P < 0.001. The 10 most common AUC indications for TTE, which accounted for 72% of all studies, are listed in Table 1. The initial AUCs assigned by reviewers were the same in 187 of 211 TTEs (kappa 0.86, P < 0.001). Most indications were not associated with TTE outcome, although studies ordered for AUC indications 1 and 2 were less likely be associated with major changes and AUC indications 22 and 47 were more likely to be associated with major changes. Table 2 shows the comparison of the 78 patients that had repeat TTE with major changes compared with the 133 patients that did not. Nine variables were significantly different between the 2 groups; repeat TTEs with major changes were more likely to have dementia, be ordered by the surgery service, be located in an ICU, have major new ECG changes, have had prior valvular heart disease, have had an intervening AMI or cardiac surgery, or be in a high-risk AUC category. Patients with CKD were less likely to have major changes. Table 3 shows the results of the multivariate analysis; CKD, intervening AMI, prior valvular heart disease, major new ECG changes, and intervening cardiac surgery all independently predicted major changes on repeat TTE. Based on the β-coefficient for each variable, a point system was assigned to each variable and a total score calculated for each patient. Most variables had β-coefficients close to 1 and were therefore assigned a score of 1. CKD was associated with a lower risk of major TTE abnormality and was assigned a negative score. Intervening AMI was associated with a β-coefficient of 2.2 and was assigned a score of 2. Based on the points assigned to each variable and its presence or absence for each patient, a total score, which we named the CAVES score, was calculated. The acronym CAVES stands for CKD, AMI, valvular disease, ECG changes, and surgery (cardiac). Table 4 shows the frequencies of each score for each patient, ranging from patients with CKD and no other risk factors who scored −1 to patients without CKD who had all 4 of the other variables who scored 5. The prevalence of major TTE change for the full cohort was 37%. For the group with a CAVES score of −1, the probability was only 5.6%; for the group with a score of 0, the probability was 17.7%; and for the group with a score ≥1, the probability was 55.3%.

In this retrospective study, we found that approximately 18% of all patients admitted to the hospital had an inpatient TTE performed, and that approximately 35% of this group had a prior TTE within the past year. Of the group with prior TTEs within the past year, 37% had a major new change and 63% had either minor or no changes. Prior studies have reported similar high rates of repeat TTE^7-9 and of major changes on repeat TTE.^8,14,16 On multivariate analysis, we found that 5 variables were independent predictors of new changes on TTE—absence of CKD, intervening AMI, intervening cardiac surgery, history of valvular heart disease, and major new ECG changes. We developed and internally validated a risk score based on these 5 variables, which was found to have good overall accuracy as measured by the bootstrap corrected C statistic. The simplified version of the score divides patients into low, intermediate, and high risk for major changes on TTE. The low-risk group, defined as the group with no risk factors, had an approximately 6% risk of a major TTE change; the intermediate risk group, defined as a score of 0, had an 18% risk of major TTE change; and the high-risk group, defined as a score of 1 or greater, had a 55% chance of major TTE change. We believe that this risk score, if further validated, will potentially allow hospital-based clinicians to estimate the chance of a major change on TTE prior to ordering the study. For the low-risk group, this may indicate that the study is unnecessary. Conversely, for patients at high risk, this may offer further evidence that it will be useful to obtain a repeat TTE.

Disclosure 

The authors indicated no conflicts of interest.

Transthoracic echocardiography (TTE) is one of the most commonly ordered diagnostic tests in healthcare. Studies of Medicare beneficiaries, for example, have shown that each year, approximately 20% undergo at least 1 TTE, including 4% who have 2 or more.¹ TTE utilization rates increased dramatically in the 1990s and early 2000s. Between 1999 and 2008, for example, the rate of use of TTE per Medicare beneficiary nearly doubled.² In 2014, echocardiography accounted for 10% of all Medicare spending for imaging services, or approximately $930 million.³ In response to concerns about the possible unnecessary use of TTE, the American Heart Association and American Society of Echocardiography developed Appropriate Use Criteria (AUC) in 2007 and 2011, which describe appropriate versus inappropriate indications for TTE.⁴ Subsequent studies have shown that rather than rooting out inappropriate studies, the vast majority of ordered studies appear to be appropriate according to the AUC criteria.⁵ The AUC criteria have also been criticized for being based on expert opinion rather than clinical evidence.⁶ Repeat TTE, defined as TTE done within 1 year of a prior TTE, represents 24% to 42% of all studies,^7-9 and 31% of all Medicare beneficiaries who have a TTE get a repeat TTE within 1 year.¹⁰ In the present study, we reviewed all inpatient TTE performed over 1 year and described the group that have had a prior TTE within the past year (“repeat TTE”). We then derived a clinical prediction model to predict unchanged repeat TTE, with the goal of defining a subset of studies that are potentially unnecessary.

The West Haven Connecticut Veteran’s Administration Hospital (WHVA), located outside New Haven, Connecticut, is a 228-bed tertiary care center affiliated with Yale University School of Medicine. Potential subjects were identified from review of the electronic medical records of all inpatients who had an inpatient echocardiogram between October 1, 2013, and September 30, 2014. Patient’s records were reviewed by using a standardized data extraction form for demographics, comorbidity, cardiovascular risk factors, service ordering the TTE, intensive care unit (ICU) location, prior TTE abnormalities, TTE indication, AUC category, time between TTEs, technical quality of TTE, electrocardiogram (ECG) abnormalities, history of intervening acute coronary syndrome, cardiac surgery, and revascularization. Candidate predictors included any variables suspected by the authors as being potentially associated with the primary outcome of changed repeat TTE. All patients who had an inpatient TTE and a prior TTE within the Veterans Affairs (VA) system within the past year were included in the study. Repeat studies from the same admission were only counted as 1 TTE and patients had to have had a prior TTE from a different admission or a prior outpatient TTE to be included. Patients who did not have a prior TTE within the past year or who had only a transesophageal echocardiogram or stress echocardiography were excluded. Suboptimal studies were included but noted as limited quality. The study was approved by the WHVA Institutional Review Board. The Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis statement was used in planning and reporting this study.¹¹

TTEs were classified as normal, mildly abnormal, or with a major abnormality based on previously published definitions.^12-14 Any abnormality was defined as any left ventricle (LV) dysfunction (left ventricular ejection fraction [LVEF] <55%), any aortic or mitral valve stenosis, any regional wall motion abnormality, any right ventricular dysfunction, any pulmonary hypertension, mild or greater valvular regurgitation, any diastolic dysfunction, moderate or greater pericardial effusion, any ventricular hypertrophy, or any other significant abnormality including thrombus, vegetation, or tamponade. Major abnormality was defined as moderate or greater LV dysfunction (LVEF <45%), moderate or greater valvular regurgitation, moderate or greater valvular stenosis (aortic or mitral valve area <1.5 cm²), any regional wall motion abnormality, right ventricular dysfunction, moderate or greater pulmonary hypertension, moderate or greater diastolic dysfunction, moderate or greater pericardial effusion, or any other major abnormality including thrombus, vegetation, tumor, or tamponade. Repeat TTEs were classified as changed or unchanged. Changed TTEs were divided into any new abnormality or improvement or a new major abnormality or improvement. Any new abnormality or improvement was defined as any new TTE abnormality that had not previously been described or in which there was a change of at least 1 severity grade from a prior TTE, including improvement by 1 grade. A new major TTE abnormality or improvement was defined as any new major TTE abnormality that had previously been normal, or if there had been a prior abnormality, a change in at least 1 severity grade for LVEF or 2 severity grades for abnormal valvular, pericardial, or prior pulmonary hypertension, including improvement by 2 severity grades. A change from mild to moderate mitral regurgitation therefore was classified as a nonmajor change, whereas a change from mild to severe was classified as major. All TTE classifications were based on the electronic TTE reports and were reviewed by 2 independent investigators (CG and JC) blinded to the patients’ other clinical characteristics. For TTE studies in which the investigators agreed, that determination was the final classification. Disagreements were reviewed and the final classification was determined by consensus.

In an analogous manner, ECGs were classified as normal, mildly abnormal, or with a major abnormality based on previous definitions in the literature.¹⁵ Major abnormality was defined as atrial fibrillation or flutter, high-degree atrioventricular blocks, left bundle-branch block, right bundle-branch block, indeterminate conduction delay, q-wave myocardial infarction, isolated ischemic abnormalities, left ventricular hypertrophy with ST-T abnormalities, other arrhythmias including supraventricular tachycardia (SVT) or ventricular tachycardia (VT), low voltage (peak-to-peak QRS amplitude of <5 mm in the limb leads and/or <10 mm in the precordial leads), paced rhythm, sinus tachycardia (heart rate [HR] >100) or bradycardia (HR <50). Mild ECG abnormality was defined as low-grade atrioventricular blocks, borderline prolonged ventricular excitation, prolonged ventricular repolarization, isolated minor Q and ST-T abnormalities, left ventricular hypertrophy without ST-T abnormalities, left atrial enlargement, atrial or ventricular premature beats, or fascicular blocks. New major ECG abnormalities were any of the listed major ECG abnormalities that were not present on ECGs prior to the admission during which the repeat TTE was performed.

Other study definitions included intervening acute myocardial infarction (AMI), which was defined by any intervening history of elevated troponins, regardless of symptoms or ECG changes and including demand ischemia. Chronic kidney disease (CKD) was defined as an abnormal serum creatinine on 2 or more occasions 3 months apart. Active cancer was defined as receiving chemotherapy or palliative care for advanced cancer. Valvular heart disease was defined as prior moderate or severe valvular stenosis or regurgitation.

For analysis, we first compared patients with repeat TTE with major changes with those without major changes. For comparison of dichotomous variables, χ² or Fisher exact tests were used. For continuous variables, Student t test or the Mann-Whitney U test were performed. Because many of the frequencies of individual AUC criteria were small, related AUC criteria were grouped for analysis as grouped by the tables of the American College of Cardiology Foundation Appropriate Use Criteria Task Force, American Society of Echocardiography, American Heart Association, American Society of Nuclear Cardiology, Heart Failure Society of America, Heart Rhythm Society, Society for Cardiovascular Angiography and Interventions, Society of Critical Care Medicine, Society of Cardiovascular Computed Tomography, and Society for Cardiovascular Magnetic Resonance (ACCF/ASE/AHA) Guideline.⁴ Criteria groupings that were significantly less likely to have major TTE changes on analysis were classified as low risk and criteria that were significantly more likely were classified as high risk. Criteria groupings that were not significantly associated with TTE change were classified as average risk. All variables with P values less than 0.05 on bivariate analysis were then entered into a multivariate logistic regression analysis with major TTE change as the dependent variable, using backward stepwise variable selection with entry and exit criteria of P < 0.05 and P > 0.10, respectively. Scores were derived by converting the regression coefficients of independently predictive variables in the logistic regression model into corresponding integers. A total score was calculated for each patient by summing up the points for each independently significant variable. Model performance was described by calculating a C statistic by creation of a receiver operating characteristic curve to assess discrimination, and by performing the Hosmer and Lemeshow test to assess calibration. Internal validation was assessed by calculating the C statistic using the statistical method of bootstrapping in which the data were resampled multiple times (n = 200) and the average resultant C statistic reported. The bootstrap analysis was performed using R version 3.1 (R Foundation for Statistical Computing, Vienna, Austria). All other analyses were performed using SPSS version 21.0 (IBM, Armonk, New York). P values <0.05 were considered significant.

During the 1-year study period, there were 3944 medical/surgical admissions for 3266 patients and 845 inpatient TTEs obtained on 601 patients. Of all patients who were admitted, 601/3266 (18.4%) had at least 1 inpatient TTE. Of these 601 TTEs, 211 (35%) had a TTE within the VA system during the prior year. Of the 211 repeat TTEs, 67 (32%) were unchanged, 66 (31%) had minor changes, and 78 (37%) had major changes. The kappa statistic for agreement between extractors for “major TTE change” was 0.91, P < 0.001. The 10 most common AUC indications for TTE, which accounted for 72% of all studies, are listed in Table 1. The initial AUCs assigned by reviewers were the same in 187 of 211 TTEs (kappa 0.86, P < 0.001). Most indications were not associated with TTE outcome, although studies ordered for AUC indications 1 and 2 were less likely be associated with major changes and AUC indications 22 and 47 were more likely to be associated with major changes. Table 2 shows the comparison of the 78 patients that had repeat TTE with major changes compared with the 133 patients that did not. Nine variables were significantly different between the 2 groups; repeat TTEs with major changes were more likely to have dementia, be ordered by the surgery service, be located in an ICU, have major new ECG changes, have had prior valvular heart disease, have had an intervening AMI or cardiac surgery, or be in a high-risk AUC category. Patients with CKD were less likely to have major changes. Table 3 shows the results of the multivariate analysis; CKD, intervening AMI, prior valvular heart disease, major new ECG changes, and intervening cardiac surgery all independently predicted major changes on repeat TTE. Based on the β-coefficient for each variable, a point system was assigned to each variable and a total score calculated for each patient. Most variables had β-coefficients close to 1 and were therefore assigned a score of 1. CKD was associated with a lower risk of major TTE abnormality and was assigned a negative score. Intervening AMI was associated with a β-coefficient of 2.2 and was assigned a score of 2. Based on the points assigned to each variable and its presence or absence for each patient, a total score, which we named the CAVES score, was calculated. The acronym CAVES stands for CKD, AMI, valvular disease, ECG changes, and surgery (cardiac). Table 4 shows the frequencies of each score for each patient, ranging from patients with CKD and no other risk factors who scored −1 to patients without CKD who had all 4 of the other variables who scored 5. The prevalence of major TTE change for the full cohort was 37%. For the group with a CAVES score of −1, the probability was only 5.6%; for the group with a score of 0, the probability was 17.7%; and for the group with a score ≥1, the probability was 55.3%.

In this retrospective study, we found that approximately 18% of all patients admitted to the hospital had an inpatient TTE performed, and that approximately 35% of this group had a prior TTE within the past year. Of the group with prior TTEs within the past year, 37% had a major new change and 63% had either minor or no changes. Prior studies have reported similar high rates of repeat TTE^7-9 and of major changes on repeat TTE.^8,14,16 On multivariate analysis, we found that 5 variables were independent predictors of new changes on TTE—absence of CKD, intervening AMI, intervening cardiac surgery, history of valvular heart disease, and major new ECG changes. We developed and internally validated a risk score based on these 5 variables, which was found to have good overall accuracy as measured by the bootstrap corrected C statistic. The simplified version of the score divides patients into low, intermediate, and high risk for major changes on TTE. The low-risk group, defined as the group with no risk factors, had an approximately 6% risk of a major TTE change; the intermediate risk group, defined as a score of 0, had an 18% risk of major TTE change; and the high-risk group, defined as a score of 1 or greater, had a 55% chance of major TTE change. We believe that this risk score, if further validated, will potentially allow hospital-based clinicians to estimate the chance of a major change on TTE prior to ordering the study. For the low-risk group, this may indicate that the study is unnecessary. Conversely, for patients at high risk, this may offer further evidence that it will be useful to obtain a repeat TTE.

Disclosure 

The authors indicated no conflicts of interest.

Transthoracic echocardiography (TTE) is one of the most commonly ordered diagnostic tests in healthcare. Studies of Medicare beneficiaries, for example, have shown that each year, approximately 20% undergo at least 1 TTE, including 4% who have 2 or more.¹ TTE utilization rates increased dramatically in the 1990s and early 2000s. Between 1999 and 2008, for example, the rate of use of TTE per Medicare beneficiary nearly doubled.² In 2014, echocardiography accounted for 10% of all Medicare spending for imaging services, or approximately $930 million.³ In response to concerns about the possible unnecessary use of TTE, the American Heart Association and American Society of Echocardiography developed Appropriate Use Criteria (AUC) in 2007 and 2011, which describe appropriate versus inappropriate indications for TTE.⁴ Subsequent studies have shown that rather than rooting out inappropriate studies, the vast majority of ordered studies appear to be appropriate according to the AUC criteria.⁵ The AUC criteria have also been criticized for being based on expert opinion rather than clinical evidence.⁶ Repeat TTE, defined as TTE done within 1 year of a prior TTE, represents 24% to 42% of all studies,^7-9 and 31% of all Medicare beneficiaries who have a TTE get a repeat TTE within 1 year.¹⁰ In the present study, we reviewed all inpatient TTE performed over 1 year and described the group that have had a prior TTE within the past year (“repeat TTE”). We then derived a clinical prediction model to predict unchanged repeat TTE, with the goal of defining a subset of studies that are potentially unnecessary.

The West Haven Connecticut Veteran’s Administration Hospital (WHVA), located outside New Haven, Connecticut, is a 228-bed tertiary care center affiliated with Yale University School of Medicine. Potential subjects were identified from review of the electronic medical records of all inpatients who had an inpatient echocardiogram between October 1, 2013, and September 30, 2014. Patient’s records were reviewed by using a standardized data extraction form for demographics, comorbidity, cardiovascular risk factors, service ordering the TTE, intensive care unit (ICU) location, prior TTE abnormalities, TTE indication, AUC category, time between TTEs, technical quality of TTE, electrocardiogram (ECG) abnormalities, history of intervening acute coronary syndrome, cardiac surgery, and revascularization. Candidate predictors included any variables suspected by the authors as being potentially associated with the primary outcome of changed repeat TTE. All patients who had an inpatient TTE and a prior TTE within the Veterans Affairs (VA) system within the past year were included in the study. Repeat studies from the same admission were only counted as 1 TTE and patients had to have had a prior TTE from a different admission or a prior outpatient TTE to be included. Patients who did not have a prior TTE within the past year or who had only a transesophageal echocardiogram or stress echocardiography were excluded. Suboptimal studies were included but noted as limited quality. The study was approved by the WHVA Institutional Review Board. The Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis statement was used in planning and reporting this study.¹¹

TTEs were classified as normal, mildly abnormal, or with a major abnormality based on previously published definitions.^12-14 Any abnormality was defined as any left ventricle (LV) dysfunction (left ventricular ejection fraction [LVEF] <55%), any aortic or mitral valve stenosis, any regional wall motion abnormality, any right ventricular dysfunction, any pulmonary hypertension, mild or greater valvular regurgitation, any diastolic dysfunction, moderate or greater pericardial effusion, any ventricular hypertrophy, or any other significant abnormality including thrombus, vegetation, or tamponade. Major abnormality was defined as moderate or greater LV dysfunction (LVEF <45%), moderate or greater valvular regurgitation, moderate or greater valvular stenosis (aortic or mitral valve area <1.5 cm²), any regional wall motion abnormality, right ventricular dysfunction, moderate or greater pulmonary hypertension, moderate or greater diastolic dysfunction, moderate or greater pericardial effusion, or any other major abnormality including thrombus, vegetation, tumor, or tamponade. Repeat TTEs were classified as changed or unchanged. Changed TTEs were divided into any new abnormality or improvement or a new major abnormality or improvement. Any new abnormality or improvement was defined as any new TTE abnormality that had not previously been described or in which there was a change of at least 1 severity grade from a prior TTE, including improvement by 1 grade. A new major TTE abnormality or improvement was defined as any new major TTE abnormality that had previously been normal, or if there had been a prior abnormality, a change in at least 1 severity grade for LVEF or 2 severity grades for abnormal valvular, pericardial, or prior pulmonary hypertension, including improvement by 2 severity grades. A change from mild to moderate mitral regurgitation therefore was classified as a nonmajor change, whereas a change from mild to severe was classified as major. All TTE classifications were based on the electronic TTE reports and were reviewed by 2 independent investigators (CG and JC) blinded to the patients’ other clinical characteristics. For TTE studies in which the investigators agreed, that determination was the final classification. Disagreements were reviewed and the final classification was determined by consensus.

In an analogous manner, ECGs were classified as normal, mildly abnormal, or with a major abnormality based on previous definitions in the literature.¹⁵ Major abnormality was defined as atrial fibrillation or flutter, high-degree atrioventricular blocks, left bundle-branch block, right bundle-branch block, indeterminate conduction delay, q-wave myocardial infarction, isolated ischemic abnormalities, left ventricular hypertrophy with ST-T abnormalities, other arrhythmias including supraventricular tachycardia (SVT) or ventricular tachycardia (VT), low voltage (peak-to-peak QRS amplitude of <5 mm in the limb leads and/or <10 mm in the precordial leads), paced rhythm, sinus tachycardia (heart rate [HR] >100) or bradycardia (HR <50). Mild ECG abnormality was defined as low-grade atrioventricular blocks, borderline prolonged ventricular excitation, prolonged ventricular repolarization, isolated minor Q and ST-T abnormalities, left ventricular hypertrophy without ST-T abnormalities, left atrial enlargement, atrial or ventricular premature beats, or fascicular blocks. New major ECG abnormalities were any of the listed major ECG abnormalities that were not present on ECGs prior to the admission during which the repeat TTE was performed.

Other study definitions included intervening acute myocardial infarction (AMI), which was defined by any intervening history of elevated troponins, regardless of symptoms or ECG changes and including demand ischemia. Chronic kidney disease (CKD) was defined as an abnormal serum creatinine on 2 or more occasions 3 months apart. Active cancer was defined as receiving chemotherapy or palliative care for advanced cancer. Valvular heart disease was defined as prior moderate or severe valvular stenosis or regurgitation.

For analysis, we first compared patients with repeat TTE with major changes with those without major changes. For comparison of dichotomous variables, χ² or Fisher exact tests were used. For continuous variables, Student t test or the Mann-Whitney U test were performed. Because many of the frequencies of individual AUC criteria were small, related AUC criteria were grouped for analysis as grouped by the tables of the American College of Cardiology Foundation Appropriate Use Criteria Task Force, American Society of Echocardiography, American Heart Association, American Society of Nuclear Cardiology, Heart Failure Society of America, Heart Rhythm Society, Society for Cardiovascular Angiography and Interventions, Society of Critical Care Medicine, Society of Cardiovascular Computed Tomography, and Society for Cardiovascular Magnetic Resonance (ACCF/ASE/AHA) Guideline.⁴ Criteria groupings that were significantly less likely to have major TTE changes on analysis were classified as low risk and criteria that were significantly more likely were classified as high risk. Criteria groupings that were not significantly associated with TTE change were classified as average risk. All variables with P values less than 0.05 on bivariate analysis were then entered into a multivariate logistic regression analysis with major TTE change as the dependent variable, using backward stepwise variable selection with entry and exit criteria of P < 0.05 and P > 0.10, respectively. Scores were derived by converting the regression coefficients of independently predictive variables in the logistic regression model into corresponding integers. A total score was calculated for each patient by summing up the points for each independently significant variable. Model performance was described by calculating a C statistic by creation of a receiver operating characteristic curve to assess discrimination, and by performing the Hosmer and Lemeshow test to assess calibration. Internal validation was assessed by calculating the C statistic using the statistical method of bootstrapping in which the data were resampled multiple times (n = 200) and the average resultant C statistic reported. The bootstrap analysis was performed using R version 3.1 (R Foundation for Statistical Computing, Vienna, Austria). All other analyses were performed using SPSS version 21.0 (IBM, Armonk, New York). P values <0.05 were considered significant.

During the 1-year study period, there were 3944 medical/surgical admissions for 3266 patients and 845 inpatient TTEs obtained on 601 patients. Of all patients who were admitted, 601/3266 (18.4%) had at least 1 inpatient TTE. Of these 601 TTEs, 211 (35%) had a TTE within the VA system during the prior year. Of the 211 repeat TTEs, 67 (32%) were unchanged, 66 (31%) had minor changes, and 78 (37%) had major changes. The kappa statistic for agreement between extractors for “major TTE change” was 0.91, P < 0.001. The 10 most common AUC indications for TTE, which accounted for 72% of all studies, are listed in Table 1. The initial AUCs assigned by reviewers were the same in 187 of 211 TTEs (kappa 0.86, P < 0.001). Most indications were not associated with TTE outcome, although studies ordered for AUC indications 1 and 2 were less likely be associated with major changes and AUC indications 22 and 47 were more likely to be associated with major changes. Table 2 shows the comparison of the 78 patients that had repeat TTE with major changes compared with the 133 patients that did not. Nine variables were significantly different between the 2 groups; repeat TTEs with major changes were more likely to have dementia, be ordered by the surgery service, be located in an ICU, have major new ECG changes, have had prior valvular heart disease, have had an intervening AMI or cardiac surgery, or be in a high-risk AUC category. Patients with CKD were less likely to have major changes. Table 3 shows the results of the multivariate analysis; CKD, intervening AMI, prior valvular heart disease, major new ECG changes, and intervening cardiac surgery all independently predicted major changes on repeat TTE. Based on the β-coefficient for each variable, a point system was assigned to each variable and a total score calculated for each patient. Most variables had β-coefficients close to 1 and were therefore assigned a score of 1. CKD was associated with a lower risk of major TTE abnormality and was assigned a negative score. Intervening AMI was associated with a β-coefficient of 2.2 and was assigned a score of 2. Based on the points assigned to each variable and its presence or absence for each patient, a total score, which we named the CAVES score, was calculated. The acronym CAVES stands for CKD, AMI, valvular disease, ECG changes, and surgery (cardiac). Table 4 shows the frequencies of each score for each patient, ranging from patients with CKD and no other risk factors who scored −1 to patients without CKD who had all 4 of the other variables who scored 5. The prevalence of major TTE change for the full cohort was 37%. For the group with a CAVES score of −1, the probability was only 5.6%; for the group with a score of 0, the probability was 17.7%; and for the group with a score ≥1, the probability was 55.3%.

In this retrospective study, we found that approximately 18% of all patients admitted to the hospital had an inpatient TTE performed, and that approximately 35% of this group had a prior TTE within the past year. Of the group with prior TTEs within the past year, 37% had a major new change and 63% had either minor or no changes. Prior studies have reported similar high rates of repeat TTE^7-9 and of major changes on repeat TTE.^8,14,16 On multivariate analysis, we found that 5 variables were independent predictors of new changes on TTE—absence of CKD, intervening AMI, intervening cardiac surgery, history of valvular heart disease, and major new ECG changes. We developed and internally validated a risk score based on these 5 variables, which was found to have good overall accuracy as measured by the bootstrap corrected C statistic. The simplified version of the score divides patients into low, intermediate, and high risk for major changes on TTE. The low-risk group, defined as the group with no risk factors, had an approximately 6% risk of a major TTE change; the intermediate risk group, defined as a score of 0, had an 18% risk of major TTE change; and the high-risk group, defined as a score of 1 or greater, had a 55% chance of major TTE change. We believe that this risk score, if further validated, will potentially allow hospital-based clinicians to estimate the chance of a major change on TTE prior to ordering the study. For the low-risk group, this may indicate that the study is unnecessary. Conversely, for patients at high risk, this may offer further evidence that it will be useful to obtain a repeat TTE.

Disclosure 

The authors indicated no conflicts of interest.

A 34-year-old, previously healthy Japanese man developed a dry cough. He did not have dyspnea, nasal discharge, sore throat, facial pain, nasal congestion, or postnasal drip. His symptoms persisted despite several courses of antibiotics (from different physicians), including clarithromycin, minocycline, and levofloxacin. A chest x-ray after 2 months of symptoms and a noncontrast chest computed tomography (CT) after 4 months of symptoms were normal, and bacterial and mycobacterial sputum cultures were sterile. Treatment with salmeterol and fluticasone was ineffective.

The persistence of a cough for longer than 8 weeks constitutes chronic cough. The initial negative review of systems argues against several of the usual etiologies. The lack of nasal discharge, sore throat, facial pain, nasal congestion, and postnasal drip lessens the probability of upper airway cough syndrome. The absence of dyspnea decreases the likelihood of congestive heart failure, asthma, or chronic obstructive pulmonary disease. Additional history should include whether the patient has orthopnea, paroxysmal nocturnal dyspnea, or a reduced exercise tolerance.

The persistence of symptoms despite multiple courses of antibiotics suggests that the process is inflammatory but not infectious, that the infection is not susceptible to the selected antibiotics, that the antibiotics cannot penetrate the site of infection, or that the ongoing symptoms are related to the antibiotics themselves. Pathogens that may cause chronic cough for months include mycobacteria, fungi (eg, Aspergillus , endemic mycoses), and parasites (eg, Strongyloides , Paragonimus ). Even when appropriately treated, many infections may result in a prolonged cough (eg, pertussis). The fluoroquinolone and macrolide exposure may have suppressed the mycobacterial cultures. The lack of response to salmeterol and fluticasone lessens the probability of asthma.

After 4 months of symptoms, his cough worsened, and he developed dysphagia and odynophagia, particularly when he initiated swallowing. He experienced daily fevers with temperatures between 38.0°C and 38.5°C. A repeat chest x-ray was normal. His white blood cell count was 14,200 per μL, and the C-reactive protein (CRP) was 12.91 mg/dL (normal <0.24 mg/dL). His symptoms did not improve with additional courses of clarithromycin, levofloxacin, or moxifloxacin. After 5 months of symptoms, he was referred to the internal medicine clinic of a teaching hospital in Japan.

The patient’s fevers, leukocytosis, and elevated CRP signal an inflammatory process, but whether it is infectious or not remains uncertain. The normal repeat chest x-ray lessens the likelihood of a pulmonary infection. Difficulty with initiating a swallow characterizes oropharyngeal dysphagia which features coughing or choking with oral intake and is typically caused by neuromuscular conditions like stroke, amyotrophic lateral sclerosis, or myasthenia gravis. The coexistence of oropharyngeal dysphagia and odynophagia may indicate pharyngitis, a retropharyngeal or parapharyngeal abscess, or oropharyngeal cancer.

Esophageal dysphagia occurs several seconds following swallow initiation and may arise with mucosal, smooth muscle, or neuromuscular diseases of the esophagus. Concomitant dysphagia and odynophagia may indicate esophageal spasm or esophagitis. Causes of esophagitis include infection (eg, candidiasis, herpes simplex virus [HSV], cytomegalovirus [CMV], or human immunodeficiency virus [HIV]), infiltration (eg, eosinophilic esophagitis), or irritation (eg, from medication, caustic ingestion, or gastroesophageal reflux). He is at risk for esophageal candidiasis following multiple courses of antibiotics. Esophageal dysphagia occurring with liquids and solids may indicate disordered motility, as opposed to dysphagia with solids alone, which may signal endoluminal obstruction.

At his outpatient evaluation, he denied headache, vision changes, chest pain, hemoptysis, palpitations, abdominal pain, dysuria, musculoskeletal symptoms, anorexia, or symptoms of gastroesophageal reflux. He did not have chills, rigors, or night sweats, but he had lost 3.4 kg in 5 months. He had not traveled within or outside of Japan in many years and was not involved in outdoor activities. He was engaged to and monogamous with his female partner of 5 years. He smoked 10 cigarettes per day for 14 years but stopped smoking during the last 2 months on account of his symptoms. He drank 6 beers per month and worked as a researcher at a chemical company but did not have any inhalational exposures.

His weight loss could be from reduced caloric intake due to dysphagia and odynophagia or may reflect an energy deficit related to chronic illness and inflammatory state. His smoking history increases his risk of bronchopulmonary infection and malignancy. Bronchogenic carcinoma may present with chronic cough, fevers, weight loss, or dysphagia from external compression by lymphadenopathy or mediastinal disease; however, his young age and recent chest CT results make lung cancer unlikely.

The initial diagnostic branch point for nontraumatic oral ulcers is infectious versus noninfectious. Infections that cause oral ulcers include HSV, CMV, and syphilis. The appearance and occurrence of the ulcers on freely moveable mucosa are consistent with aphthous stomatitis. Recurrent aphthous ulcers may occur in autoimmune diseases, including Behçet disease, Crohn disease, celiac sprue, and reactive arthritis. An endoscopy should be considered to detect esophageal ulcerations or esophageal candidiasis.

The rash may indicate folliculitis, usually attributable to Staphylococcus aureus or to Pseudomonas in the setting of recreational water exposure. Broad-spectrum antibiotics or immunodeficiency predisposes to candida folliculitis, while systemic candidiasis may cause metastatic skin lesions. The most common cutaneous manifestation of Behçet disease is erythema nodosum, but follicular and papulopustular lesions are also characteristic.

Thickening of the aorta and left pulmonary artery may arise from an infectious, infiltrative, or inflammatory process. Arterial infections arise from direct inoculation, such as catheterization, trauma, or a contiguous site of infection, or from embolic seeding of atherosclerotic plaques or aneurysms. Malignant and nonmalignant processes, including sarcomas, lymphomas, histiocytoses (eg, Erdheim–Chester disease), and IgG4-related disease, may infiltrate the vascular walls. He has no evidence of visceral organ involvement to suggest these multisystem diagnoses.

The combined involvement of the aorta and pulmonary artery suggest a large-vessel vasculitis. Giant cell arteritis is exceedingly rare in patients younger than 50. Takayasu arteritis is a large-vessel vasculitis that predominantly affects women and may present with hypertension, arterial bruits, or discrepant blood pressure between arms, none of which were reported in this case. Behçet disease affects blood vessels of all sizes, including the aorta and pulmonary vasculature. His fevers, oral ulcers, perifollicular rash, and lymphadenopathy are consistent with this diagnosis, although he lacks the genital ulcers that occur in the majority of patients. Pulmonary nodules in Behçet disease arise from pulmonary or pleural vasculitis, resulting in focal inflammation, hemorrhage, or infarction. An ophthalmologic examination for uveitis and a pathergy test would support this diagnosis.

FDG accumulation in the aorta and pulmonary arteries signals large-vessel inflammation. The lack of FDG-avidity of the ground-glass opacities and nodular lesion suggests that these are not metabolically active tumors or infections but may be sequelae of the underlying disease, such as a hemorrhage or infarction from vasculitis. Sarcoidosis could account for the lung findings, but large-vessel vasculopathy would be exceedingly uncommon. Microscopic polyangiitis and granulomatosis with polyangiitis also cause pulmonary and vascular inflammation, but the nonreactive ANCA, absence of sinus disease, and normal urinalysis and kidney function make pauci-immune vasculitis unlikely. While the large-vessel involvement is consistent with Takayasu arteritis, the oral ulcers and rash are not.

Despite the absence of uveitis and the negative pathergy test, his oral aphthosis, papulopustular rash, and large-vessel vasculitis make Behçet disease the likely diagnosis. Behçet disease is most strongly associated with HLA B51, although other HLA haplotypes (including HLA A26 and HLA B52) are frequent in Behçet disease as well. As aortitis and pulmonary vasculitis can be associated with substantial morbidity and mortality, an urgent consultation with a rheumatologist regarding the initiation of immunosuppression is warranted.

Based on the mucocutaneous lesions, radiologic findings consistent with large-vessel vasculitis, and positive HLA A26 and HLA B52, he was diagnosed with Behçet disease. After 1 week of treatment with prednisolone 60 mg daily, his cough resolved and the oral aphthous ulcers and papulopustular rash improved. One month later, a chest CT showed significant reduction of the wall thickening of the aorta, its branches, and of the left pulmonary artery. The nodular lesion in the left lower lobe was unchanged, but the ground-glass opacities in the left upper lobe had disappeared.

When prednisolone was tapered down to 17.5 mg, his dry cough and low-grade fevers recurred, along with a slight elevation of inflammatory markers, and a ground-glass opacity appeared on the periphery of the left upper lobe. A sputum culture and fungal antigens were negative. His cough improved with the resumption of the previous dose of prednisolone. He remained symptom-free after 2 years of treatment with azathioprine 150 mg daily and prednisolone 2 mg daily and is now only treated with azathioprine.

Behçet disease is a multisystem vasculitis involving blood vessels of all sizes in the arterial and venous circulation that presents with oral and genital ulcers, ocular abnormalities (uveitis, retinitis), skin lesions (erythema nodosum, nonfollicular papulopustular lesions, or “pseudofolliculitis”), pathergy, and vascular lesions (thrombophlebitis, thrombosis, and aneurysm).

This patient presented with a chronic cough from pulmonary involvement by Behçet disease. The most common presenting symptom in a study of 47 patients with Behçet disease with pulmonary arteriopathy was hemoptysis followed by a nonbloody cough.² Among these patients with pulmonary artery aneurysm, thrombosis, or both, 40 (85%) had nodules caused by infarction or inflammation and 21 (45%) had ground-glass opacities attributed to intraparenchymal hemorrhage. There are several case reports of chronic cough attributed to large-vessel vasculitis.^3-5 Although the pathology of vasculitis-related cough is not fully understood, the inflammation of large vessels (aorta and pulmonary arteries) adjacent to the tracheobronchial tree may irritate regional cough receptors.³

Disease classification criteria are common in rheumatologic diseases; these criteria are developed to categorize patients for research studies and are not intended to diagnose individual patients.⁶ The classification criteria favor increased specificity at the expense of sensitivity to avoid misclassifying patients as having a disease, which would compromise the results of research studies. For instance, a study assessing a treatment for Behçet disease must exclude patients with inflammatory bowel disease, as these distinct patient populations may demonstrate discrepant responses to the investigative therapy. The specificity and homogeneity favored by classification criteria make those criteria inappropriate to rely on exclusively for the diagnosis of individual patients.⁷ The symptoms of many autoimmune diseases develop sequentially over time. Waiting for a patient with active, multisystem vasculitis to fulfill all of the Behçet disease classification criteria can lead to the harmful withholding of disease-modifying treatment.

• Large-vessel vasculitis is a rare cause of chronic cough.
• Although the most well-recognized signs of Behçet disease include genital and oral ulcers and uveitis, patients may also present with less common manifestations such as skin lesions (erythema nodosum, nonfollicular papulopustular lesions, or “pseudofolliculitis”) and vascular lesions of the artery (arteritis and aneurysm) and veins (thrombophlebitis and thrombosis).
• Classification criteria capture cardinal features of a disease but favor specificity over sensitivity and should not serve as a checklist for diagnosing a patient.

Acknowledgment

A brief version of this case was published as a case report in the Journal of Integrated Medicine 2013;23(12):1014-1017. Images from that publication were republished here with the permission of the publisher (Igaku-Shoin Ltd).

Disclosure 

Dr. Dhaliwal reports receiving honoraria from ISMIE Mutual Insurance Company and Physicians’ Reciprocal Insurers. All other authors have nothing to disclose.

A 34-year-old, previously healthy Japanese man developed a dry cough. He did not have dyspnea, nasal discharge, sore throat, facial pain, nasal congestion, or postnasal drip. His symptoms persisted despite several courses of antibiotics (from different physicians), including clarithromycin, minocycline, and levofloxacin. A chest x-ray after 2 months of symptoms and a noncontrast chest computed tomography (CT) after 4 months of symptoms were normal, and bacterial and mycobacterial sputum cultures were sterile. Treatment with salmeterol and fluticasone was ineffective.

The persistence of a cough for longer than 8 weeks constitutes chronic cough. The initial negative review of systems argues against several of the usual etiologies. The lack of nasal discharge, sore throat, facial pain, nasal congestion, and postnasal drip lessens the probability of upper airway cough syndrome. The absence of dyspnea decreases the likelihood of congestive heart failure, asthma, or chronic obstructive pulmonary disease. Additional history should include whether the patient has orthopnea, paroxysmal nocturnal dyspnea, or a reduced exercise tolerance.

The persistence of symptoms despite multiple courses of antibiotics suggests that the process is inflammatory but not infectious, that the infection is not susceptible to the selected antibiotics, that the antibiotics cannot penetrate the site of infection, or that the ongoing symptoms are related to the antibiotics themselves. Pathogens that may cause chronic cough for months include mycobacteria, fungi (eg, Aspergillus , endemic mycoses), and parasites (eg, Strongyloides , Paragonimus ). Even when appropriately treated, many infections may result in a prolonged cough (eg, pertussis). The fluoroquinolone and macrolide exposure may have suppressed the mycobacterial cultures. The lack of response to salmeterol and fluticasone lessens the probability of asthma.

After 4 months of symptoms, his cough worsened, and he developed dysphagia and odynophagia, particularly when he initiated swallowing. He experienced daily fevers with temperatures between 38.0°C and 38.5°C. A repeat chest x-ray was normal. His white blood cell count was 14,200 per μL, and the C-reactive protein (CRP) was 12.91 mg/dL (normal <0.24 mg/dL). His symptoms did not improve with additional courses of clarithromycin, levofloxacin, or moxifloxacin. After 5 months of symptoms, he was referred to the internal medicine clinic of a teaching hospital in Japan.

The patient’s fevers, leukocytosis, and elevated CRP signal an inflammatory process, but whether it is infectious or not remains uncertain. The normal repeat chest x-ray lessens the likelihood of a pulmonary infection. Difficulty with initiating a swallow characterizes oropharyngeal dysphagia which features coughing or choking with oral intake and is typically caused by neuromuscular conditions like stroke, amyotrophic lateral sclerosis, or myasthenia gravis. The coexistence of oropharyngeal dysphagia and odynophagia may indicate pharyngitis, a retropharyngeal or parapharyngeal abscess, or oropharyngeal cancer.

Esophageal dysphagia occurs several seconds following swallow initiation and may arise with mucosal, smooth muscle, or neuromuscular diseases of the esophagus. Concomitant dysphagia and odynophagia may indicate esophageal spasm or esophagitis. Causes of esophagitis include infection (eg, candidiasis, herpes simplex virus [HSV], cytomegalovirus [CMV], or human immunodeficiency virus [HIV]), infiltration (eg, eosinophilic esophagitis), or irritation (eg, from medication, caustic ingestion, or gastroesophageal reflux). He is at risk for esophageal candidiasis following multiple courses of antibiotics. Esophageal dysphagia occurring with liquids and solids may indicate disordered motility, as opposed to dysphagia with solids alone, which may signal endoluminal obstruction.

At his outpatient evaluation, he denied headache, vision changes, chest pain, hemoptysis, palpitations, abdominal pain, dysuria, musculoskeletal symptoms, anorexia, or symptoms of gastroesophageal reflux. He did not have chills, rigors, or night sweats, but he had lost 3.4 kg in 5 months. He had not traveled within or outside of Japan in many years and was not involved in outdoor activities. He was engaged to and monogamous with his female partner of 5 years. He smoked 10 cigarettes per day for 14 years but stopped smoking during the last 2 months on account of his symptoms. He drank 6 beers per month and worked as a researcher at a chemical company but did not have any inhalational exposures.

His weight loss could be from reduced caloric intake due to dysphagia and odynophagia or may reflect an energy deficit related to chronic illness and inflammatory state. His smoking history increases his risk of bronchopulmonary infection and malignancy. Bronchogenic carcinoma may present with chronic cough, fevers, weight loss, or dysphagia from external compression by lymphadenopathy or mediastinal disease; however, his young age and recent chest CT results make lung cancer unlikely.

The initial diagnostic branch point for nontraumatic oral ulcers is infectious versus noninfectious. Infections that cause oral ulcers include HSV, CMV, and syphilis. The appearance and occurrence of the ulcers on freely moveable mucosa are consistent with aphthous stomatitis. Recurrent aphthous ulcers may occur in autoimmune diseases, including Behçet disease, Crohn disease, celiac sprue, and reactive arthritis. An endoscopy should be considered to detect esophageal ulcerations or esophageal candidiasis.

The rash may indicate folliculitis, usually attributable to Staphylococcus aureus or to Pseudomonas in the setting of recreational water exposure. Broad-spectrum antibiotics or immunodeficiency predisposes to candida folliculitis, while systemic candidiasis may cause metastatic skin lesions. The most common cutaneous manifestation of Behçet disease is erythema nodosum, but follicular and papulopustular lesions are also characteristic.

Thickening of the aorta and left pulmonary artery may arise from an infectious, infiltrative, or inflammatory process. Arterial infections arise from direct inoculation, such as catheterization, trauma, or a contiguous site of infection, or from embolic seeding of atherosclerotic plaques or aneurysms. Malignant and nonmalignant processes, including sarcomas, lymphomas, histiocytoses (eg, Erdheim–Chester disease), and IgG4-related disease, may infiltrate the vascular walls. He has no evidence of visceral organ involvement to suggest these multisystem diagnoses.

The combined involvement of the aorta and pulmonary artery suggest a large-vessel vasculitis. Giant cell arteritis is exceedingly rare in patients younger than 50. Takayasu arteritis is a large-vessel vasculitis that predominantly affects women and may present with hypertension, arterial bruits, or discrepant blood pressure between arms, none of which were reported in this case. Behçet disease affects blood vessels of all sizes, including the aorta and pulmonary vasculature. His fevers, oral ulcers, perifollicular rash, and lymphadenopathy are consistent with this diagnosis, although he lacks the genital ulcers that occur in the majority of patients. Pulmonary nodules in Behçet disease arise from pulmonary or pleural vasculitis, resulting in focal inflammation, hemorrhage, or infarction. An ophthalmologic examination for uveitis and a pathergy test would support this diagnosis.

FDG accumulation in the aorta and pulmonary arteries signals large-vessel inflammation. The lack of FDG-avidity of the ground-glass opacities and nodular lesion suggests that these are not metabolically active tumors or infections but may be sequelae of the underlying disease, such as a hemorrhage or infarction from vasculitis. Sarcoidosis could account for the lung findings, but large-vessel vasculopathy would be exceedingly uncommon. Microscopic polyangiitis and granulomatosis with polyangiitis also cause pulmonary and vascular inflammation, but the nonreactive ANCA, absence of sinus disease, and normal urinalysis and kidney function make pauci-immune vasculitis unlikely. While the large-vessel involvement is consistent with Takayasu arteritis, the oral ulcers and rash are not.

Despite the absence of uveitis and the negative pathergy test, his oral aphthosis, papulopustular rash, and large-vessel vasculitis make Behçet disease the likely diagnosis. Behçet disease is most strongly associated with HLA B51, although other HLA haplotypes (including HLA A26 and HLA B52) are frequent in Behçet disease as well. As aortitis and pulmonary vasculitis can be associated with substantial morbidity and mortality, an urgent consultation with a rheumatologist regarding the initiation of immunosuppression is warranted.

Based on the mucocutaneous lesions, radiologic findings consistent with large-vessel vasculitis, and positive HLA A26 and HLA B52, he was diagnosed with Behçet disease. After 1 week of treatment with prednisolone 60 mg daily, his cough resolved and the oral aphthous ulcers and papulopustular rash improved. One month later, a chest CT showed significant reduction of the wall thickening of the aorta, its branches, and of the left pulmonary artery. The nodular lesion in the left lower lobe was unchanged, but the ground-glass opacities in the left upper lobe had disappeared.

When prednisolone was tapered down to 17.5 mg, his dry cough and low-grade fevers recurred, along with a slight elevation of inflammatory markers, and a ground-glass opacity appeared on the periphery of the left upper lobe. A sputum culture and fungal antigens were negative. His cough improved with the resumption of the previous dose of prednisolone. He remained symptom-free after 2 years of treatment with azathioprine 150 mg daily and prednisolone 2 mg daily and is now only treated with azathioprine.

Behçet disease is a multisystem vasculitis involving blood vessels of all sizes in the arterial and venous circulation that presents with oral and genital ulcers, ocular abnormalities (uveitis, retinitis), skin lesions (erythema nodosum, nonfollicular papulopustular lesions, or “pseudofolliculitis”), pathergy, and vascular lesions (thrombophlebitis, thrombosis, and aneurysm).

This patient presented with a chronic cough from pulmonary involvement by Behçet disease. The most common presenting symptom in a study of 47 patients with Behçet disease with pulmonary arteriopathy was hemoptysis followed by a nonbloody cough.² Among these patients with pulmonary artery aneurysm, thrombosis, or both, 40 (85%) had nodules caused by infarction or inflammation and 21 (45%) had ground-glass opacities attributed to intraparenchymal hemorrhage. There are several case reports of chronic cough attributed to large-vessel vasculitis.^3-5 Although the pathology of vasculitis-related cough is not fully understood, the inflammation of large vessels (aorta and pulmonary arteries) adjacent to the tracheobronchial tree may irritate regional cough receptors.³

Disease classification criteria are common in rheumatologic diseases; these criteria are developed to categorize patients for research studies and are not intended to diagnose individual patients.⁶ The classification criteria favor increased specificity at the expense of sensitivity to avoid misclassifying patients as having a disease, which would compromise the results of research studies. For instance, a study assessing a treatment for Behçet disease must exclude patients with inflammatory bowel disease, as these distinct patient populations may demonstrate discrepant responses to the investigative therapy. The specificity and homogeneity favored by classification criteria make those criteria inappropriate to rely on exclusively for the diagnosis of individual patients.⁷ The symptoms of many autoimmune diseases develop sequentially over time. Waiting for a patient with active, multisystem vasculitis to fulfill all of the Behçet disease classification criteria can lead to the harmful withholding of disease-modifying treatment.

• Large-vessel vasculitis is a rare cause of chronic cough.
• Although the most well-recognized signs of Behçet disease include genital and oral ulcers and uveitis, patients may also present with less common manifestations such as skin lesions (erythema nodosum, nonfollicular papulopustular lesions, or “pseudofolliculitis”) and vascular lesions of the artery (arteritis and aneurysm) and veins (thrombophlebitis and thrombosis).
• Classification criteria capture cardinal features of a disease but favor specificity over sensitivity and should not serve as a checklist for diagnosing a patient.

Acknowledgment

A brief version of this case was published as a case report in the Journal of Integrated Medicine 2013;23(12):1014-1017. Images from that publication were republished here with the permission of the publisher (Igaku-Shoin Ltd).

Disclosure 

Dr. Dhaliwal reports receiving honoraria from ISMIE Mutual Insurance Company and Physicians’ Reciprocal Insurers. All other authors have nothing to disclose.

A 34-year-old, previously healthy Japanese man developed a dry cough. He did not have dyspnea, nasal discharge, sore throat, facial pain, nasal congestion, or postnasal drip. His symptoms persisted despite several courses of antibiotics (from different physicians), including clarithromycin, minocycline, and levofloxacin. A chest x-ray after 2 months of symptoms and a noncontrast chest computed tomography (CT) after 4 months of symptoms were normal, and bacterial and mycobacterial sputum cultures were sterile. Treatment with salmeterol and fluticasone was ineffective.

The persistence of a cough for longer than 8 weeks constitutes chronic cough. The initial negative review of systems argues against several of the usual etiologies. The lack of nasal discharge, sore throat, facial pain, nasal congestion, and postnasal drip lessens the probability of upper airway cough syndrome. The absence of dyspnea decreases the likelihood of congestive heart failure, asthma, or chronic obstructive pulmonary disease. Additional history should include whether the patient has orthopnea, paroxysmal nocturnal dyspnea, or a reduced exercise tolerance.

The persistence of symptoms despite multiple courses of antibiotics suggests that the process is inflammatory but not infectious, that the infection is not susceptible to the selected antibiotics, that the antibiotics cannot penetrate the site of infection, or that the ongoing symptoms are related to the antibiotics themselves. Pathogens that may cause chronic cough for months include mycobacteria, fungi (eg, Aspergillus , endemic mycoses), and parasites (eg, Strongyloides , Paragonimus ). Even when appropriately treated, many infections may result in a prolonged cough (eg, pertussis). The fluoroquinolone and macrolide exposure may have suppressed the mycobacterial cultures. The lack of response to salmeterol and fluticasone lessens the probability of asthma.

After 4 months of symptoms, his cough worsened, and he developed dysphagia and odynophagia, particularly when he initiated swallowing. He experienced daily fevers with temperatures between 38.0°C and 38.5°C. A repeat chest x-ray was normal. His white blood cell count was 14,200 per μL, and the C-reactive protein (CRP) was 12.91 mg/dL (normal <0.24 mg/dL). His symptoms did not improve with additional courses of clarithromycin, levofloxacin, or moxifloxacin. After 5 months of symptoms, he was referred to the internal medicine clinic of a teaching hospital in Japan.

The patient’s fevers, leukocytosis, and elevated CRP signal an inflammatory process, but whether it is infectious or not remains uncertain. The normal repeat chest x-ray lessens the likelihood of a pulmonary infection. Difficulty with initiating a swallow characterizes oropharyngeal dysphagia which features coughing or choking with oral intake and is typically caused by neuromuscular conditions like stroke, amyotrophic lateral sclerosis, or myasthenia gravis. The coexistence of oropharyngeal dysphagia and odynophagia may indicate pharyngitis, a retropharyngeal or parapharyngeal abscess, or oropharyngeal cancer.

Esophageal dysphagia occurs several seconds following swallow initiation and may arise with mucosal, smooth muscle, or neuromuscular diseases of the esophagus. Concomitant dysphagia and odynophagia may indicate esophageal spasm or esophagitis. Causes of esophagitis include infection (eg, candidiasis, herpes simplex virus [HSV], cytomegalovirus [CMV], or human immunodeficiency virus [HIV]), infiltration (eg, eosinophilic esophagitis), or irritation (eg, from medication, caustic ingestion, or gastroesophageal reflux). He is at risk for esophageal candidiasis following multiple courses of antibiotics. Esophageal dysphagia occurring with liquids and solids may indicate disordered motility, as opposed to dysphagia with solids alone, which may signal endoluminal obstruction.

At his outpatient evaluation, he denied headache, vision changes, chest pain, hemoptysis, palpitations, abdominal pain, dysuria, musculoskeletal symptoms, anorexia, or symptoms of gastroesophageal reflux. He did not have chills, rigors, or night sweats, but he had lost 3.4 kg in 5 months. He had not traveled within or outside of Japan in many years and was not involved in outdoor activities. He was engaged to and monogamous with his female partner of 5 years. He smoked 10 cigarettes per day for 14 years but stopped smoking during the last 2 months on account of his symptoms. He drank 6 beers per month and worked as a researcher at a chemical company but did not have any inhalational exposures.

His weight loss could be from reduced caloric intake due to dysphagia and odynophagia or may reflect an energy deficit related to chronic illness and inflammatory state. His smoking history increases his risk of bronchopulmonary infection and malignancy. Bronchogenic carcinoma may present with chronic cough, fevers, weight loss, or dysphagia from external compression by lymphadenopathy or mediastinal disease; however, his young age and recent chest CT results make lung cancer unlikely.

The initial diagnostic branch point for nontraumatic oral ulcers is infectious versus noninfectious. Infections that cause oral ulcers include HSV, CMV, and syphilis. The appearance and occurrence of the ulcers on freely moveable mucosa are consistent with aphthous stomatitis. Recurrent aphthous ulcers may occur in autoimmune diseases, including Behçet disease, Crohn disease, celiac sprue, and reactive arthritis. An endoscopy should be considered to detect esophageal ulcerations or esophageal candidiasis.

The rash may indicate folliculitis, usually attributable to Staphylococcus aureus or to Pseudomonas in the setting of recreational water exposure. Broad-spectrum antibiotics or immunodeficiency predisposes to candida folliculitis, while systemic candidiasis may cause metastatic skin lesions. The most common cutaneous manifestation of Behçet disease is erythema nodosum, but follicular and papulopustular lesions are also characteristic.

Thickening of the aorta and left pulmonary artery may arise from an infectious, infiltrative, or inflammatory process. Arterial infections arise from direct inoculation, such as catheterization, trauma, or a contiguous site of infection, or from embolic seeding of atherosclerotic plaques or aneurysms. Malignant and nonmalignant processes, including sarcomas, lymphomas, histiocytoses (eg, Erdheim–Chester disease), and IgG4-related disease, may infiltrate the vascular walls. He has no evidence of visceral organ involvement to suggest these multisystem diagnoses.

The combined involvement of the aorta and pulmonary artery suggest a large-vessel vasculitis. Giant cell arteritis is exceedingly rare in patients younger than 50. Takayasu arteritis is a large-vessel vasculitis that predominantly affects women and may present with hypertension, arterial bruits, or discrepant blood pressure between arms, none of which were reported in this case. Behçet disease affects blood vessels of all sizes, including the aorta and pulmonary vasculature. His fevers, oral ulcers, perifollicular rash, and lymphadenopathy are consistent with this diagnosis, although he lacks the genital ulcers that occur in the majority of patients. Pulmonary nodules in Behçet disease arise from pulmonary or pleural vasculitis, resulting in focal inflammation, hemorrhage, or infarction. An ophthalmologic examination for uveitis and a pathergy test would support this diagnosis.

FDG accumulation in the aorta and pulmonary arteries signals large-vessel inflammation. The lack of FDG-avidity of the ground-glass opacities and nodular lesion suggests that these are not metabolically active tumors or infections but may be sequelae of the underlying disease, such as a hemorrhage or infarction from vasculitis. Sarcoidosis could account for the lung findings, but large-vessel vasculopathy would be exceedingly uncommon. Microscopic polyangiitis and granulomatosis with polyangiitis also cause pulmonary and vascular inflammation, but the nonreactive ANCA, absence of sinus disease, and normal urinalysis and kidney function make pauci-immune vasculitis unlikely. While the large-vessel involvement is consistent with Takayasu arteritis, the oral ulcers and rash are not.

Despite the absence of uveitis and the negative pathergy test, his oral aphthosis, papulopustular rash, and large-vessel vasculitis make Behçet disease the likely diagnosis. Behçet disease is most strongly associated with HLA B51, although other HLA haplotypes (including HLA A26 and HLA B52) are frequent in Behçet disease as well. As aortitis and pulmonary vasculitis can be associated with substantial morbidity and mortality, an urgent consultation with a rheumatologist regarding the initiation of immunosuppression is warranted.

Based on the mucocutaneous lesions, radiologic findings consistent with large-vessel vasculitis, and positive HLA A26 and HLA B52, he was diagnosed with Behçet disease. After 1 week of treatment with prednisolone 60 mg daily, his cough resolved and the oral aphthous ulcers and papulopustular rash improved. One month later, a chest CT showed significant reduction of the wall thickening of the aorta, its branches, and of the left pulmonary artery. The nodular lesion in the left lower lobe was unchanged, but the ground-glass opacities in the left upper lobe had disappeared.

When prednisolone was tapered down to 17.5 mg, his dry cough and low-grade fevers recurred, along with a slight elevation of inflammatory markers, and a ground-glass opacity appeared on the periphery of the left upper lobe. A sputum culture and fungal antigens were negative. His cough improved with the resumption of the previous dose of prednisolone. He remained symptom-free after 2 years of treatment with azathioprine 150 mg daily and prednisolone 2 mg daily and is now only treated with azathioprine.

Behçet disease is a multisystem vasculitis involving blood vessels of all sizes in the arterial and venous circulation that presents with oral and genital ulcers, ocular abnormalities (uveitis, retinitis), skin lesions (erythema nodosum, nonfollicular papulopustular lesions, or “pseudofolliculitis”), pathergy, and vascular lesions (thrombophlebitis, thrombosis, and aneurysm).

This patient presented with a chronic cough from pulmonary involvement by Behçet disease. The most common presenting symptom in a study of 47 patients with Behçet disease with pulmonary arteriopathy was hemoptysis followed by a nonbloody cough.² Among these patients with pulmonary artery aneurysm, thrombosis, or both, 40 (85%) had nodules caused by infarction or inflammation and 21 (45%) had ground-glass opacities attributed to intraparenchymal hemorrhage. There are several case reports of chronic cough attributed to large-vessel vasculitis.^3-5 Although the pathology of vasculitis-related cough is not fully understood, the inflammation of large vessels (aorta and pulmonary arteries) adjacent to the tracheobronchial tree may irritate regional cough receptors.³

Disease classification criteria are common in rheumatologic diseases; these criteria are developed to categorize patients for research studies and are not intended to diagnose individual patients.⁶ The classification criteria favor increased specificity at the expense of sensitivity to avoid misclassifying patients as having a disease, which would compromise the results of research studies. For instance, a study assessing a treatment for Behçet disease must exclude patients with inflammatory bowel disease, as these distinct patient populations may demonstrate discrepant responses to the investigative therapy. The specificity and homogeneity favored by classification criteria make those criteria inappropriate to rely on exclusively for the diagnosis of individual patients.⁷ The symptoms of many autoimmune diseases develop sequentially over time. Waiting for a patient with active, multisystem vasculitis to fulfill all of the Behçet disease classification criteria can lead to the harmful withholding of disease-modifying treatment.

• Large-vessel vasculitis is a rare cause of chronic cough.
• Although the most well-recognized signs of Behçet disease include genital and oral ulcers and uveitis, patients may also present with less common manifestations such as skin lesions (erythema nodosum, nonfollicular papulopustular lesions, or “pseudofolliculitis”) and vascular lesions of the artery (arteritis and aneurysm) and veins (thrombophlebitis and thrombosis).
• Classification criteria capture cardinal features of a disease but favor specificity over sensitivity and should not serve as a checklist for diagnosing a patient.

Acknowledgment

A brief version of this case was published as a case report in the Journal of Integrated Medicine 2013;23(12):1014-1017. Images from that publication were republished here with the permission of the publisher (Igaku-Shoin Ltd).

Disclosure 

Dr. Dhaliwal reports receiving honoraria from ISMIE Mutual Insurance Company and Physicians’ Reciprocal Insurers. All other authors have nothing to disclose.

Sepsis can be the result of single or multiple factors and sources of infection. Oral sources of sepsis and systemic infection are not commonly considered as the first potential source of infection when evaluating a septic patient. Oral infections of odontogenic or periodontal origin are frequently associated with localized or diffuse cellulitis of the head and neck region.¹ The patient’s health status and complicating problems, such as an immunocompromising condition, can further reduce the immune response for controlling chronic sources of infection. This in turn, can lead to acute manifestations such as cellulitis, sepsis, or necrotizing fasciitis. Necrotizing fasciitis is caused by a polymicrobial or mixed aerobic-anaerobic infection from a variety of sources, including Streptococcus pyogenes (S pyogenes).

Case Presentation

A 57-year-old female with a history of major depressive disorder, paroxysmal atrial fibrillation, and opioid dependence that was in remission for more than 3 years was brought to the emergency department (ED) by a family member after the patient developed confusion and lethargy. She was primarily experiencing right breast pain and swelling. The breast pain was associated with high fevers, nausea, vomiting, and chills. On examination the patient was noted to have a fever of 104° F, heart rate of 160 bpm, respirations of 22 breaths per minute, blood pressure (BP) 109/58, and a white blood cell count (WBC) of 8.7 X 10³. There was a noted skin abrasion on her right hand. She was lethargic and confused. Blood cultures were positive for S pyogenes, and a swab of the right breast was negative for bacterial growth.

The patient was admitted to the medical intensive care unit (MICU) and placed on 2 vasopressors for control of low BP and assistance with low urine output. After a 6 L fluid resuscitation, the patient was started on vancomycin and piperacillin/tazobactam for possible cellulitis causing sepsis. An echocardiogram was negative for endocarditis. The patient continued to decline the following day with continuing tachycardia and tachypnea with hypotension and was intubated. Pulmonology was consulted for possible acute respiratory distress syndrome secondary to sepsis. General surgery was consulted for possible necrotizing fasciitis of the chest wall, and cardiology was consulted for low cardiac output.

On day 4 of her hospitalization, the patient was taken to surgery for exploration, drainage, and debridement of the right axilla and breast; cultures with lack of organism growth was noted. While in the MICU, she was followed by the Infectious Disease service as her WBC remained elevated and peaking at 32.6 X 10³, while blood cultures were negative for bacterial growth. The dental service was consulted on day 5 to evaluate for other possible sources of infection.

The patient’s oral condition was noted as having advanced chronic periodontal disease that required full mouth extraction. The patient remained hemodynamically unstable with platelet counts below 50,000 until day 7, at which time she was taken for surgery for full mouth extraction and associated alveoloplasty. On extraction the patient continued to improve and was extubated on day 11 with platelets and WBC returning to normal levels by day 13 of her hospital stay. The patient remained hospitalized for a total MICU stay of 20 days and rehabilitation stay of more than 2 weeks.

Discussion

Oral infections most often present with acute onset and noted oral-facial cellulitis or abscess. Oral source of septicemia often are considered after ruling out most other potential sources. Although it is not certain that this case is directly related to the advanced chronic periodontal disease, S pyogenes has been noted to be a pathogen in periodontal disease progression.

According to the American Dental Association in 2012, dental visits to the ED cost the U.S. health care system $1.6 billion and an average cost of $749 per visit. There are more than 2 million ED visits each year for dental pain and infection, and 39% return due to nonresolution of the dental problem. Patients return to the ED due to lack of access and resources to routine and emergent dental care.² The average daily cost of an MICU stay with mechanical ventilation was $2,193 in 2002. This particular case consisted of 11 days of mechanical ventilation, 20 MICU days, and an additional 20 days of inpatient rehabilitation which resulted in costs that exceeded $50,000.³

Conclusion

This case demonstrates the successful collaboration of dentistry for the overall medical management of the patient. An integrated approach highlights the need for and the value of integrating dental programs within large tertiary hospital systems. Such integration will likely improve earlier recognition and better management of oral infections resulting in systemic illness and improve patient outcomes, reduced length of hospital stay, and reduction of overall costs.

Sepsis can be the result of single or multiple factors and sources of infection. Oral sources of sepsis and systemic infection are not commonly considered as the first potential source of infection when evaluating a septic patient. Oral infections of odontogenic or periodontal origin are frequently associated with localized or diffuse cellulitis of the head and neck region.¹ The patient’s health status and complicating problems, such as an immunocompromising condition, can further reduce the immune response for controlling chronic sources of infection. This in turn, can lead to acute manifestations such as cellulitis, sepsis, or necrotizing fasciitis. Necrotizing fasciitis is caused by a polymicrobial or mixed aerobic-anaerobic infection from a variety of sources, including Streptococcus pyogenes (S pyogenes).

Case Presentation

A 57-year-old female with a history of major depressive disorder, paroxysmal atrial fibrillation, and opioid dependence that was in remission for more than 3 years was brought to the emergency department (ED) by a family member after the patient developed confusion and lethargy. She was primarily experiencing right breast pain and swelling. The breast pain was associated with high fevers, nausea, vomiting, and chills. On examination the patient was noted to have a fever of 104° F, heart rate of 160 bpm, respirations of 22 breaths per minute, blood pressure (BP) 109/58, and a white blood cell count (WBC) of 8.7 X 10³. There was a noted skin abrasion on her right hand. She was lethargic and confused. Blood cultures were positive for S pyogenes, and a swab of the right breast was negative for bacterial growth.

The patient was admitted to the medical intensive care unit (MICU) and placed on 2 vasopressors for control of low BP and assistance with low urine output. After a 6 L fluid resuscitation, the patient was started on vancomycin and piperacillin/tazobactam for possible cellulitis causing sepsis. An echocardiogram was negative for endocarditis. The patient continued to decline the following day with continuing tachycardia and tachypnea with hypotension and was intubated. Pulmonology was consulted for possible acute respiratory distress syndrome secondary to sepsis. General surgery was consulted for possible necrotizing fasciitis of the chest wall, and cardiology was consulted for low cardiac output.

On day 4 of her hospitalization, the patient was taken to surgery for exploration, drainage, and debridement of the right axilla and breast; cultures with lack of organism growth was noted. While in the MICU, she was followed by the Infectious Disease service as her WBC remained elevated and peaking at 32.6 X 10³, while blood cultures were negative for bacterial growth. The dental service was consulted on day 5 to evaluate for other possible sources of infection.

The patient’s oral condition was noted as having advanced chronic periodontal disease that required full mouth extraction. The patient remained hemodynamically unstable with platelet counts below 50,000 until day 7, at which time she was taken for surgery for full mouth extraction and associated alveoloplasty. On extraction the patient continued to improve and was extubated on day 11 with platelets and WBC returning to normal levels by day 13 of her hospital stay. The patient remained hospitalized for a total MICU stay of 20 days and rehabilitation stay of more than 2 weeks.

Discussion

Oral infections most often present with acute onset and noted oral-facial cellulitis or abscess. Oral source of septicemia often are considered after ruling out most other potential sources. Although it is not certain that this case is directly related to the advanced chronic periodontal disease, S pyogenes has been noted to be a pathogen in periodontal disease progression.

According to the American Dental Association in 2012, dental visits to the ED cost the U.S. health care system $1.6 billion and an average cost of $749 per visit. There are more than 2 million ED visits each year for dental pain and infection, and 39% return due to nonresolution of the dental problem. Patients return to the ED due to lack of access and resources to routine and emergent dental care.² The average daily cost of an MICU stay with mechanical ventilation was $2,193 in 2002. This particular case consisted of 11 days of mechanical ventilation, 20 MICU days, and an additional 20 days of inpatient rehabilitation which resulted in costs that exceeded $50,000.³

Conclusion

This case demonstrates the successful collaboration of dentistry for the overall medical management of the patient. An integrated approach highlights the need for and the value of integrating dental programs within large tertiary hospital systems. Such integration will likely improve earlier recognition and better management of oral infections resulting in systemic illness and improve patient outcomes, reduced length of hospital stay, and reduction of overall costs.

Sepsis can be the result of single or multiple factors and sources of infection. Oral sources of sepsis and systemic infection are not commonly considered as the first potential source of infection when evaluating a septic patient. Oral infections of odontogenic or periodontal origin are frequently associated with localized or diffuse cellulitis of the head and neck region.¹ The patient’s health status and complicating problems, such as an immunocompromising condition, can further reduce the immune response for controlling chronic sources of infection. This in turn, can lead to acute manifestations such as cellulitis, sepsis, or necrotizing fasciitis. Necrotizing fasciitis is caused by a polymicrobial or mixed aerobic-anaerobic infection from a variety of sources, including Streptococcus pyogenes (S pyogenes).

Case Presentation

A 57-year-old female with a history of major depressive disorder, paroxysmal atrial fibrillation, and opioid dependence that was in remission for more than 3 years was brought to the emergency department (ED) by a family member after the patient developed confusion and lethargy. She was primarily experiencing right breast pain and swelling. The breast pain was associated with high fevers, nausea, vomiting, and chills. On examination the patient was noted to have a fever of 104° F, heart rate of 160 bpm, respirations of 22 breaths per minute, blood pressure (BP) 109/58, and a white blood cell count (WBC) of 8.7 X 10³. There was a noted skin abrasion on her right hand. She was lethargic and confused. Blood cultures were positive for S pyogenes, and a swab of the right breast was negative for bacterial growth.

The patient was admitted to the medical intensive care unit (MICU) and placed on 2 vasopressors for control of low BP and assistance with low urine output. After a 6 L fluid resuscitation, the patient was started on vancomycin and piperacillin/tazobactam for possible cellulitis causing sepsis. An echocardiogram was negative for endocarditis. The patient continued to decline the following day with continuing tachycardia and tachypnea with hypotension and was intubated. Pulmonology was consulted for possible acute respiratory distress syndrome secondary to sepsis. General surgery was consulted for possible necrotizing fasciitis of the chest wall, and cardiology was consulted for low cardiac output.

On day 4 of her hospitalization, the patient was taken to surgery for exploration, drainage, and debridement of the right axilla and breast; cultures with lack of organism growth was noted. While in the MICU, she was followed by the Infectious Disease service as her WBC remained elevated and peaking at 32.6 X 10³, while blood cultures were negative for bacterial growth. The dental service was consulted on day 5 to evaluate for other possible sources of infection.

The patient’s oral condition was noted as having advanced chronic periodontal disease that required full mouth extraction. The patient remained hemodynamically unstable with platelet counts below 50,000 until day 7, at which time she was taken for surgery for full mouth extraction and associated alveoloplasty. On extraction the patient continued to improve and was extubated on day 11 with platelets and WBC returning to normal levels by day 13 of her hospital stay. The patient remained hospitalized for a total MICU stay of 20 days and rehabilitation stay of more than 2 weeks.

Discussion

Oral infections most often present with acute onset and noted oral-facial cellulitis or abscess. Oral source of septicemia often are considered after ruling out most other potential sources. Although it is not certain that this case is directly related to the advanced chronic periodontal disease, S pyogenes has been noted to be a pathogen in periodontal disease progression.

According to the American Dental Association in 2012, dental visits to the ED cost the U.S. health care system $1.6 billion and an average cost of $749 per visit. There are more than 2 million ED visits each year for dental pain and infection, and 39% return due to nonresolution of the dental problem. Patients return to the ED due to lack of access and resources to routine and emergent dental care.² The average daily cost of an MICU stay with mechanical ventilation was $2,193 in 2002. This particular case consisted of 11 days of mechanical ventilation, 20 MICU days, and an additional 20 days of inpatient rehabilitation which resulted in costs that exceeded $50,000.³

Conclusion

This case demonstrates the successful collaboration of dentistry for the overall medical management of the patient. An integrated approach highlights the need for and the value of integrating dental programs within large tertiary hospital systems. Such integration will likely improve earlier recognition and better management of oral infections resulting in systemic illness and improve patient outcomes, reduced length of hospital stay, and reduction of overall costs.

A 15-year-old African American girl presented to the emergency department with 3 days of fever, sore throat, nausea, vomiting, and poor appetite. She reported a 4-week history of fatigue, right hand pain and swelling, and a 6-kilogram weight loss for which she had seen her primary care provider several times. She reported no recent travel, sick contacts, or new medications.

It appears that there are potentially at least 2 separate problems: an acute one (past 3 days) and a more chronic one (past 4 weeks). These 2 problems may be directly related (ie, acute worsening of the more chronic problem), indirectly related (ie, the more chronic problem is leading to increased susceptibility to the acute problem, for instance, an evolving immunodeficiency predisposing to an opportunistic infection), or “true, true, but unrelated.” The clinical challenge is to keep one’s mind open to each of these potential scenarios and to avoid the tendency to focus on one of the problems and not pay enough attention to the other. Occam’s razor likely does not apply here.

Numerous common and typically transient diseases could cause the symptoms of the past 3 days, particularly infectious etiologies such as streptococcal pharyngitis or a viral infection. One cannot forget about these possibilities while contemplating the more worrisome symptoms of the past 4 weeks, especially weight loss in a growing adolescent. Patients may unintentionally lose weight for a variety of reasons, which can be broadly categorized by decreased caloric supply, gastrointestinal losses or malabsorption, and increased caloric demand; these categories are not mutually exclusive.

Lastly, 1 symptom may provide a more specific direction: the right hand pain and swelling of the past 4 weeks. More specifics, including the extent of the hand swelling, other areas of involvement, and the nature of her pain, will be helpful.

Her temperature was 99.5°F, heart rate 100 beats per minute, respiratory rate 18 breaths per minute, oxygen saturation 95% while breathing ambient air, blood pressure 99/56 mmHg, weight 44 kilograms, height 161 centimeters, and body mass index 17. She appeared generally ill and underweight. She had edematous and violaceous eyelids, dry cracked lips, and pharyngeal erythema with ulcerations of the hard palate. She had nontender cervical and inguinal lymphadenopathy. Her abdomen was tender to palpation in the lower quadrants without guarding or rebound; there was no organomegaly. A right knee effusion with overlying warmth was present without redness or decreased range of motion. She also had an enlarged third proximal interphalangeal joint and loss of palpable metacarpal phalangeal joint landmarks on her right hand. She was noted to be using her arms to move her legs when repositioning in bed.

These exam findings clearly point toward a systemic process but not 1 specific diagnosis. The presence of at least 2 inflamed joints points toward rheumatologic/inflammatory or infectious diseases. Localized edema (eyelids and right metacarpal phalangeal joints), oral ulcers, possible myositis, and arthritis point toward a systemic vasculitis (eg, granulomatosis with polyangiitis, Behçet disease). While Kawasaki disease is also a systemic vasculitis, the presence of oral ulcers and generalized lymphadenopathy argues against it. Inflammatory myopathies like polymyositis, and especially juvenile dermatomyositis, fit many aspects of this presentation with the violaceous eyelids and possible myositis, though no other cutaneous stigmata of this disease are evident (eg, no Gottron’s papules). Polyarthritis, violaceous eyelids, and possible myositis could be consistent with systemic lupus erythematosus (SLE).

The presence of oral ulcers and arthritis make other systemic inflammatory conditions, such as inflammatory bowel disease with arthritis and autoimmune- or infection-related hepatitis, possible. Infectious etiologies alone or in combination with a rheumatologic process are also possible given fevers and lymphadenopathy. In particular, herpesvirus infections (Epstein-Barr virus [EBV], cytomegalovirus [CMV], herpes simplex virus, or human herpes virus 6), human immunodeficiency virus (HIV), hepatitis C virus (HCV), and syphilis can cause oral ulcers and lymphadenopathy. Other potential infectious etiologies include subacute bacterial endocarditis and disseminated gonococcal infection given the presence of polyarthritis, but these infections are less likely as they do not explain all of the symptoms.

In summary, the differential diagnosis is broad and should be prioritized to consider systemic inflammatory conditions, including autoimmune and infectious (especially viral) syndromes, and initial work-up should focus on these etiologies.

All of the infectious disease studies returned negative for active infection and were consistent with prior EBV and CMV infections with positive IgG testing. The bone marrow biopsy revealed trilineage hematopoiesis with hemophagocytosis, mild fibrosis, and no blasts (Figure 2). Antibody studies for SLE returned with elevated antidouble stranded DNA antibodies >200,000 IU/L. Reference labs ultimately confirmed the presence of decreased natural killer (NK) cell function, elevated soluble interleukin-2 receptors (IL-2R), and elevated soluble cluster of differentiation 163 (CD163).

Because the differential diagnosis for new-onset pancytopenia encompasses many diseases across several medical subspecialties, a thorough history and physical exam are necessary to form a tailored clinical approach.¹ The primary causes of pediatric pancytopenia vary depending on geographic location because of the local prevalence of infectious agents and nutritional deficiency patterns. A retrospective study investigating the primary cause of pancytopenia in children without existing malignancy presenting to a US tertiary care hospital found that 64% of cases were due to infection, 28% were due to hematologic disease (most frequently aplastic anemia), and 8% were due to miscellaneous etiologies, including adverse drug reactions and autoimmune diseases.² In contrast, the most common cause of pancytopenia in pediatric patients presenting to a tertiary care hospital in India was megaloblastic anemia (28%), followed by infections (21%), acute leukemia (21%), and aplastic anemia (20%).³ While clinicians do (and should) consider malignancy as a cause of pancytopenia, there is sparse literature regarding the frequency of pancytopenia associated with the presentations of childhood malignancies.⁴ A study of pediatric patients with acute lymphoblastic anemia found that only 11% of newly diagnosed patients had pancytopenia at initial presentation.⁴

There are no official guidelines for the work-up of pediatric pancytopenia from any of the academic societies. Depending on the clinical history, initial laboratory investigation for pediatric pancytopenia may include complete blood cell count with differential, reticulocyte count, peripheral blood smear, complete metabolic panel, hemolysis labs (haptoglobin, LDH, Coombs test) and inflammatory markers (ESR, CRP, fibrinogen). Further investigation to clarify the specific etiology of pancytopenia can be guided by the results of these initial tests.

• Children with SLE tend to have greater involvement of major organ systems and more rapid accrual of organ damage than adults with SLE. Therefore, it is sometimes necessary to initiate immunosuppressive therapies before full diagnostic criteria are met, provided that malignancy and infection have been ruled out.
• While pancytopenia is common in pediatric patients with SLE, providers should make sure to consider coexisting diagnoses such as infection and MAS, both of which require different treatment strategies.
• It is important to consider HLH/MAS early in the work-up of pancytopenia, because early diagnosis and treatment improves clinical outcomes. Obtaining a ferritin level can aid in the work-up of pancytopenia because it is both a sensitive and specific marker of HLH/MAS when dramatically elevated.

Disclosure

 The authors report no conflicts of interest.

A 15-year-old African American girl presented to the emergency department with 3 days of fever, sore throat, nausea, vomiting, and poor appetite. She reported a 4-week history of fatigue, right hand pain and swelling, and a 6-kilogram weight loss for which she had seen her primary care provider several times. She reported no recent travel, sick contacts, or new medications.

It appears that there are potentially at least 2 separate problems: an acute one (past 3 days) and a more chronic one (past 4 weeks). These 2 problems may be directly related (ie, acute worsening of the more chronic problem), indirectly related (ie, the more chronic problem is leading to increased susceptibility to the acute problem, for instance, an evolving immunodeficiency predisposing to an opportunistic infection), or “true, true, but unrelated.” The clinical challenge is to keep one’s mind open to each of these potential scenarios and to avoid the tendency to focus on one of the problems and not pay enough attention to the other. Occam’s razor likely does not apply here.

Numerous common and typically transient diseases could cause the symptoms of the past 3 days, particularly infectious etiologies such as streptococcal pharyngitis or a viral infection. One cannot forget about these possibilities while contemplating the more worrisome symptoms of the past 4 weeks, especially weight loss in a growing adolescent. Patients may unintentionally lose weight for a variety of reasons, which can be broadly categorized by decreased caloric supply, gastrointestinal losses or malabsorption, and increased caloric demand; these categories are not mutually exclusive.

Lastly, 1 symptom may provide a more specific direction: the right hand pain and swelling of the past 4 weeks. More specifics, including the extent of the hand swelling, other areas of involvement, and the nature of her pain, will be helpful.

Her temperature was 99.5°F, heart rate 100 beats per minute, respiratory rate 18 breaths per minute, oxygen saturation 95% while breathing ambient air, blood pressure 99/56 mmHg, weight 44 kilograms, height 161 centimeters, and body mass index 17. She appeared generally ill and underweight. She had edematous and violaceous eyelids, dry cracked lips, and pharyngeal erythema with ulcerations of the hard palate. She had nontender cervical and inguinal lymphadenopathy. Her abdomen was tender to palpation in the lower quadrants without guarding or rebound; there was no organomegaly. A right knee effusion with overlying warmth was present without redness or decreased range of motion. She also had an enlarged third proximal interphalangeal joint and loss of palpable metacarpal phalangeal joint landmarks on her right hand. She was noted to be using her arms to move her legs when repositioning in bed.

These exam findings clearly point toward a systemic process but not 1 specific diagnosis. The presence of at least 2 inflamed joints points toward rheumatologic/inflammatory or infectious diseases. Localized edema (eyelids and right metacarpal phalangeal joints), oral ulcers, possible myositis, and arthritis point toward a systemic vasculitis (eg, granulomatosis with polyangiitis, Behçet disease). While Kawasaki disease is also a systemic vasculitis, the presence of oral ulcers and generalized lymphadenopathy argues against it. Inflammatory myopathies like polymyositis, and especially juvenile dermatomyositis, fit many aspects of this presentation with the violaceous eyelids and possible myositis, though no other cutaneous stigmata of this disease are evident (eg, no Gottron’s papules). Polyarthritis, violaceous eyelids, and possible myositis could be consistent with systemic lupus erythematosus (SLE).

The presence of oral ulcers and arthritis make other systemic inflammatory conditions, such as inflammatory bowel disease with arthritis and autoimmune- or infection-related hepatitis, possible. Infectious etiologies alone or in combination with a rheumatologic process are also possible given fevers and lymphadenopathy. In particular, herpesvirus infections (Epstein-Barr virus [EBV], cytomegalovirus [CMV], herpes simplex virus, or human herpes virus 6), human immunodeficiency virus (HIV), hepatitis C virus (HCV), and syphilis can cause oral ulcers and lymphadenopathy. Other potential infectious etiologies include subacute bacterial endocarditis and disseminated gonococcal infection given the presence of polyarthritis, but these infections are less likely as they do not explain all of the symptoms.

In summary, the differential diagnosis is broad and should be prioritized to consider systemic inflammatory conditions, including autoimmune and infectious (especially viral) syndromes, and initial work-up should focus on these etiologies.

All of the infectious disease studies returned negative for active infection and were consistent with prior EBV and CMV infections with positive IgG testing. The bone marrow biopsy revealed trilineage hematopoiesis with hemophagocytosis, mild fibrosis, and no blasts (Figure 2). Antibody studies for SLE returned with elevated antidouble stranded DNA antibodies >200,000 IU/L. Reference labs ultimately confirmed the presence of decreased natural killer (NK) cell function, elevated soluble interleukin-2 receptors (IL-2R), and elevated soluble cluster of differentiation 163 (CD163).

Because the differential diagnosis for new-onset pancytopenia encompasses many diseases across several medical subspecialties, a thorough history and physical exam are necessary to form a tailored clinical approach.¹ The primary causes of pediatric pancytopenia vary depending on geographic location because of the local prevalence of infectious agents and nutritional deficiency patterns. A retrospective study investigating the primary cause of pancytopenia in children without existing malignancy presenting to a US tertiary care hospital found that 64% of cases were due to infection, 28% were due to hematologic disease (most frequently aplastic anemia), and 8% were due to miscellaneous etiologies, including adverse drug reactions and autoimmune diseases.² In contrast, the most common cause of pancytopenia in pediatric patients presenting to a tertiary care hospital in India was megaloblastic anemia (28%), followed by infections (21%), acute leukemia (21%), and aplastic anemia (20%).³ While clinicians do (and should) consider malignancy as a cause of pancytopenia, there is sparse literature regarding the frequency of pancytopenia associated with the presentations of childhood malignancies.⁴ A study of pediatric patients with acute lymphoblastic anemia found that only 11% of newly diagnosed patients had pancytopenia at initial presentation.⁴

There are no official guidelines for the work-up of pediatric pancytopenia from any of the academic societies. Depending on the clinical history, initial laboratory investigation for pediatric pancytopenia may include complete blood cell count with differential, reticulocyte count, peripheral blood smear, complete metabolic panel, hemolysis labs (haptoglobin, LDH, Coombs test) and inflammatory markers (ESR, CRP, fibrinogen). Further investigation to clarify the specific etiology of pancytopenia can be guided by the results of these initial tests.

• Children with SLE tend to have greater involvement of major organ systems and more rapid accrual of organ damage than adults with SLE. Therefore, it is sometimes necessary to initiate immunosuppressive therapies before full diagnostic criteria are met, provided that malignancy and infection have been ruled out.
• While pancytopenia is common in pediatric patients with SLE, providers should make sure to consider coexisting diagnoses such as infection and MAS, both of which require different treatment strategies.
• It is important to consider HLH/MAS early in the work-up of pancytopenia, because early diagnosis and treatment improves clinical outcomes. Obtaining a ferritin level can aid in the work-up of pancytopenia because it is both a sensitive and specific marker of HLH/MAS when dramatically elevated.

Disclosure

 The authors report no conflicts of interest.

A 15-year-old African American girl presented to the emergency department with 3 days of fever, sore throat, nausea, vomiting, and poor appetite. She reported a 4-week history of fatigue, right hand pain and swelling, and a 6-kilogram weight loss for which she had seen her primary care provider several times. She reported no recent travel, sick contacts, or new medications.

It appears that there are potentially at least 2 separate problems: an acute one (past 3 days) and a more chronic one (past 4 weeks). These 2 problems may be directly related (ie, acute worsening of the more chronic problem), indirectly related (ie, the more chronic problem is leading to increased susceptibility to the acute problem, for instance, an evolving immunodeficiency predisposing to an opportunistic infection), or “true, true, but unrelated.” The clinical challenge is to keep one’s mind open to each of these potential scenarios and to avoid the tendency to focus on one of the problems and not pay enough attention to the other. Occam’s razor likely does not apply here.

Numerous common and typically transient diseases could cause the symptoms of the past 3 days, particularly infectious etiologies such as streptococcal pharyngitis or a viral infection. One cannot forget about these possibilities while contemplating the more worrisome symptoms of the past 4 weeks, especially weight loss in a growing adolescent. Patients may unintentionally lose weight for a variety of reasons, which can be broadly categorized by decreased caloric supply, gastrointestinal losses or malabsorption, and increased caloric demand; these categories are not mutually exclusive.

Lastly, 1 symptom may provide a more specific direction: the right hand pain and swelling of the past 4 weeks. More specifics, including the extent of the hand swelling, other areas of involvement, and the nature of her pain, will be helpful.

Her temperature was 99.5°F, heart rate 100 beats per minute, respiratory rate 18 breaths per minute, oxygen saturation 95% while breathing ambient air, blood pressure 99/56 mmHg, weight 44 kilograms, height 161 centimeters, and body mass index 17. She appeared generally ill and underweight. She had edematous and violaceous eyelids, dry cracked lips, and pharyngeal erythema with ulcerations of the hard palate. She had nontender cervical and inguinal lymphadenopathy. Her abdomen was tender to palpation in the lower quadrants without guarding or rebound; there was no organomegaly. A right knee effusion with overlying warmth was present without redness or decreased range of motion. She also had an enlarged third proximal interphalangeal joint and loss of palpable metacarpal phalangeal joint landmarks on her right hand. She was noted to be using her arms to move her legs when repositioning in bed.

These exam findings clearly point toward a systemic process but not 1 specific diagnosis. The presence of at least 2 inflamed joints points toward rheumatologic/inflammatory or infectious diseases. Localized edema (eyelids and right metacarpal phalangeal joints), oral ulcers, possible myositis, and arthritis point toward a systemic vasculitis (eg, granulomatosis with polyangiitis, Behçet disease). While Kawasaki disease is also a systemic vasculitis, the presence of oral ulcers and generalized lymphadenopathy argues against it. Inflammatory myopathies like polymyositis, and especially juvenile dermatomyositis, fit many aspects of this presentation with the violaceous eyelids and possible myositis, though no other cutaneous stigmata of this disease are evident (eg, no Gottron’s papules). Polyarthritis, violaceous eyelids, and possible myositis could be consistent with systemic lupus erythematosus (SLE).

The presence of oral ulcers and arthritis make other systemic inflammatory conditions, such as inflammatory bowel disease with arthritis and autoimmune- or infection-related hepatitis, possible. Infectious etiologies alone or in combination with a rheumatologic process are also possible given fevers and lymphadenopathy. In particular, herpesvirus infections (Epstein-Barr virus [EBV], cytomegalovirus [CMV], herpes simplex virus, or human herpes virus 6), human immunodeficiency virus (HIV), hepatitis C virus (HCV), and syphilis can cause oral ulcers and lymphadenopathy. Other potential infectious etiologies include subacute bacterial endocarditis and disseminated gonococcal infection given the presence of polyarthritis, but these infections are less likely as they do not explain all of the symptoms.

In summary, the differential diagnosis is broad and should be prioritized to consider systemic inflammatory conditions, including autoimmune and infectious (especially viral) syndromes, and initial work-up should focus on these etiologies.

All of the infectious disease studies returned negative for active infection and were consistent with prior EBV and CMV infections with positive IgG testing. The bone marrow biopsy revealed trilineage hematopoiesis with hemophagocytosis, mild fibrosis, and no blasts (Figure 2). Antibody studies for SLE returned with elevated antidouble stranded DNA antibodies >200,000 IU/L. Reference labs ultimately confirmed the presence of decreased natural killer (NK) cell function, elevated soluble interleukin-2 receptors (IL-2R), and elevated soluble cluster of differentiation 163 (CD163).

Because the differential diagnosis for new-onset pancytopenia encompasses many diseases across several medical subspecialties, a thorough history and physical exam are necessary to form a tailored clinical approach.¹ The primary causes of pediatric pancytopenia vary depending on geographic location because of the local prevalence of infectious agents and nutritional deficiency patterns. A retrospective study investigating the primary cause of pancytopenia in children without existing malignancy presenting to a US tertiary care hospital found that 64% of cases were due to infection, 28% were due to hematologic disease (most frequently aplastic anemia), and 8% were due to miscellaneous etiologies, including adverse drug reactions and autoimmune diseases.² In contrast, the most common cause of pancytopenia in pediatric patients presenting to a tertiary care hospital in India was megaloblastic anemia (28%), followed by infections (21%), acute leukemia (21%), and aplastic anemia (20%).³ While clinicians do (and should) consider malignancy as a cause of pancytopenia, there is sparse literature regarding the frequency of pancytopenia associated with the presentations of childhood malignancies.⁴ A study of pediatric patients with acute lymphoblastic anemia found that only 11% of newly diagnosed patients had pancytopenia at initial presentation.⁴

There are no official guidelines for the work-up of pediatric pancytopenia from any of the academic societies. Depending on the clinical history, initial laboratory investigation for pediatric pancytopenia may include complete blood cell count with differential, reticulocyte count, peripheral blood smear, complete metabolic panel, hemolysis labs (haptoglobin, LDH, Coombs test) and inflammatory markers (ESR, CRP, fibrinogen). Further investigation to clarify the specific etiology of pancytopenia can be guided by the results of these initial tests.

• Children with SLE tend to have greater involvement of major organ systems and more rapid accrual of organ damage than adults with SLE. Therefore, it is sometimes necessary to initiate immunosuppressive therapies before full diagnostic criteria are met, provided that malignancy and infection have been ruled out.
• While pancytopenia is common in pediatric patients with SLE, providers should make sure to consider coexisting diagnoses such as infection and MAS, both of which require different treatment strategies.
• It is important to consider HLH/MAS early in the work-up of pancytopenia, because early diagnosis and treatment improves clinical outcomes. Obtaining a ferritin level can aid in the work-up of pancytopenia because it is both a sensitive and specific marker of HLH/MAS when dramatically elevated.

Disclosure

 The authors report no conflicts of interest.

Pediatric hospital medicine (PHM) is one of the most rapidly growing disciplines in pediatrics,¹ with 8% of pediatric residency graduates each year entering the field.² Research plays an important role in advancing care in the field and is a critical component for board certification and fellowship accreditation.^3-6 The annual PHM conference, which has been jointly sponsored by the Academic Pediatric Association, the American Academy of Pediatrics, and the Society of Hospital Medicine, is an important venue for the dissemination of research findings. Abstract selection is determined by peer review; however, reviewers are provided with only a brief snapshot of the research, which may not contain sufficient information to fully evaluate the methodological quality of the work.^7-10 Additionally, while instructions are provided, reviewers often lack formal training in abstract review. Consequently, scores may vary.⁹

Publication in a peer-reviewed journal is considered a measure of research success because it requires more rigorous peer review than the abstract selection process at scientific meetings.^11-16 Rates of subsequent journal publication differ based on specialty and meeting, and they have been reported at 23% to 78%.^10,12,14-18 In pediatrics, publication rates after presentation at scientific meetings range from 36% to 63%, with mean time to publication ranging from 20 to 26 months following the meeting.^11,19,20 No studies have reviewed abstract submissions to the annual PHM meeting to determine if selection or presentation format is associated with subsequent publication in a peer-reviewed journal.

We sought to identify the publication rate of abstracts submitted to the 2014 PHM conference and determine whether presentation format was associated with the likelihood of subsequent journal publication or time to publication.

Study Design

Data for this retrospective cohort study were obtained from a database of all abstracts submitted for presentation at the 2014 PHM conference in Lake Buena Vista, Florida.

Main Exposures

The main exposure was presentation format, which was categorized as not presented (ie, rejected), poster presentation, or oral presentation. PHM has a blinded abstract peer-review process; in 2014, an average of 10 reviewers scored each abstract. Reviewers graded abstracts on a scale of 1 (best in category) to 7 (unacceptable for presentation) according to the following criteria: originality, scientific importance, methodological rigor, and quality of presentation. Abstracts with the lowest average scores in each content area, usually less than or equal to 3, were accepted as oral presentations while most abstracts with scores greater than 5 were rejected. For this study, information collected from each abstract included authors, if the primary author was a trainee, title, content area, and presentation format. Content areas included clinical research, educational research, health services research (HSR) and/or epidemiology, practice management research, and quality improvement. Abstracts were then grouped by presentation format and content area for analysis. The Pediatric Academic Societies (PAS) annual meeting, another common venue for the presentation of pediatric research, precedes the PHM conference. Because acceptance for PAS presentation may represent more strongly developed abstract submissions for PHM, we identified which abstracts had also been presented at the PAS conference that same year by cross-referencing authors and abstract titles with the PAS 2014 program.

Main Outcome Measures

All submissions were assessed for subsequent publication in peer-reviewed journals through January 2017 (30 months following the July 2014 PHM conference). To identify abstracts that went on to full publication, 2 authors (JC and LEH) independently searched for the lead author’s name and the presentation title in PubMed, Google Scholar, and MedEdPORTAL in January 2017. PubMed was searched using both the general search box and an advanced search for author and title. Google Scholar was added to capture manuscripts that may not have been indexed in PubMed at the time of our search. MedEdPORTAL, a common venue for the publication of educational initiatives that are not currently indexed in PubMed, was searched by lead author name via the general search box. If a full manuscript was published discussing similar outcomes or results and was written by the same authors who had submitted a PHM conference abstract, it was considered to have been published. The journal, month, and year of publication were recorded. For journals published every 2 months, the date of publication was recorded as falling between the 2 months. For those journals with biannual publication in the spring and fall, the months of March and October were used, respectively. The impact factor of the publication journal was also recorded for the year preceding publication. A journal’s impact factor is frequently used as a quantitative measure of journal quality and reflects the frequency with which a journal’s articles are cited in the scientific literature.²¹ Journals without an impact factor (eg, newer journals) were assigned a 0.

Data Analysis

All abstracts submitted to the PHM conference were analyzed based on content area and presentation format. The proportion of all abstracts subsequently published was determined for each format type and content area, and the odds ratio (OR) for publication after abstract submission was calculated using logistic regression. We calculated an adjusted OR for subsequent publication controlling for PAS presentation and the trainee status of the primary author. The journals most frequently publishing abstracts submitted to the PHM conference were identified. Median time to publication was calculated using the number of months elapsed between the PHM conference and publication date and compared across all abstract formats using Cox proportional hazards models adjusted for PAS presentation and trainee status. Kaplan-Meier survival curves were also generated for each of the 3 formats and compared using log-rank tests. The median impact factor was determined for each abstract format and compared using Wilcoxon rank-sum tests. Median impact factor by content area was compared using a Kruskal-Wallis test. All statistical analyses were performed using SAS version 9.2 (SAS Institute, Cary, NC). P values < 0.05 were considered statistically significant. In accordance with the Common Rule²² and the policies of the Cincinnati Children’s Hospital Medical Center Institutional Review Board, this research was not considered human subjects research.

For the 2014 PHM meeting, 226 abstracts were submitted, of which 183 (81.0%) were selected for presentation, including 154 (68.0%) as poster presentations and 29 (12.8%) as oral presentations. Of all submitted abstracts, 82 (36.3%) were published within 30 months following the meeting. Eighty-one of these (98.8%) were identified via PubMed, and 1 was found only in MedEdPORTAL. No additional publications were found via Google Scholar. The presenting author for the PHM abstract was the first author for 87.8% (n = 72) of the publications. A trainee was the presenting author for only 2 of these abstracts. For the publications in which the first author was not the presenting author, the presenting author was the senior author in 2 of the publications and the second or third author on the remaining 8. Of the abstracts accepted for presentation, 70 (38.3%) were subsequently published. Abstracts accepted for oral presentation had almost 7-fold greater odds of subsequent publication than those that were rejected (Table 1; OR 6.8; 95% confidence interval [CI], 2.4-19.4). Differences in the odds of publication for rejected abstracts compared with those accepted for poster presentation were not statistically significant (OR 1.2; 95% CI, 0.5-2.5).

About one-third of abstracts submitted to the 2014 PHM conference were subsequently published in peer-reviewed journals within 30 months of the conference. Compared with rejected abstracts, the rate of publication was significantly higher for abstracts selected for oral presentation but not for those selected for poster presentation. For abstracts ultimately published in journals, selection for oral presentation was significantly associated with both a shorter time to publication and a higher median journal impact factor compared with rejected abstracts. Time to publication and median journal impact factor were similar between rejected abstracts and those accepted for poster presentation. Our findings suggest that abstract reviewers may be able to identify which abstracts will ultimately withstand more stringent peer review in the publication process when accepting abstracts for oral presentation. However, the selection for poster presentation versus rejection may not be indicative of future publication or the impact factor of the subsequent publication journal.

Previous studies have reviewed publication rates after meetings of the European Society for Pediatric Urology (publication rate of 47%),¹¹ the Ambulatory Pediatric Association (now the Academic Pediatric Association; publication rate of 47%), the American Pediatric Society/Society for Pediatric Research (publication rate of 54%), and the PAS (publication rate of 45%).^19,20 Our lower publication rate of 36.3% may be attributed to the shorter follow-up time in our study (30 months from the PHM conference), whereas prior studies monitored for publication up to 60 months after the PAS conference.²⁰ Factors associated with subsequent publication include statistically significant results, a large sample size, and a randomized controlled trial study design.^15,16 The primary reason for nonpublication for up to 80% of abstracts is failure to submit a manuscript for publication.²³ A lack of time and fear of rejection after peer review are commonly cited explanations.^18,23,24 Individuals may view acceptance for an oral presentation as positive reinforcement and be more motivated to pursue subsequent manuscript publication than individuals whose abstracts are offered poster presentations or are rejected. Trainees frequently present abstracts at scientific meetings, representing 40.3% of primary authors submitting abstracts to PHM in 2014, but may not have sufficient time or mentorship to develop a complete manuscript.¹⁸ To our knowledge, there have been no publications that assess the impact of trainee status on subsequent publication after conference submission.

Our study demonstrated that selection for oral presentation was associated with subsequent publication, shorter time to publication, and publication in journals with higher impact factors. A 2005 Cochrane review also demonstrated that selection for oral presentation was associated with subsequent journal publication.¹⁶ Abstracts accepted for oral publication may represent work further along in the research process, with more developed methodology and results. The shorter time to publication for abstracts accepted for oral presentation could also reflect feedback provided by conference attendees after the presentation, whereas poster sessions frequently lack a formalized process for critique.

Carroll et al. found no difference in time to publication between abstracts accepted for presentation at the PAS and rejected abstracts.²⁰ Previous studies demonstrate that most abstracts presented at scientific meetings that are subsequently accepted for publication are published within 2 to 3 years of the meeting,¹² with publication rates as high as 98% within 3 years of presentation.¹⁷ In contrast to Carroll et al., we found that abstracts accepted for oral presentation had a 4-fold greater likelihood of publication at each month than rejected abstracts. However, abstracts accepted for poster presentation did not have a significant difference in the proportional hazard ratio models for publication compared with rejected abstracts. Because space considerations limit the number of abstracts that can be accepted for presentation at a conference, some abstracts that are suitable for future publication may have been rejected due to a lack of space. Because researchers often use scientific meetings as a forum to receive peer feedback,¹² authors who present at conferences may take more time to write a manuscript in order to incorporate this feedback.

The most common journal in which submitted abstracts were subsequently published was Hospital Pediatrics, representing twice as many published manuscripts as the second most frequent journal, Pediatrics. Hospital Pediatrics, which was first published in 2011, did not have an impact factor assigned during the study period. Yet, as a peer-reviewed journal dedicated to the field of PHM, it is well aligned with the research presented at the PHM meeting. It is unclear if Hospital Pediatrics is a journal to which pediatric hospitalists tend to submit manuscripts initially or if manuscripts are frequently submitted elsewhere prior to their publication in Hospital Pediatrics. Submission to other journals first likely extends the time to publication, especially for abstracts accepted for poster presentation, which may describe studies with less developed methods or results.

This study has several limitations. Previous studies have demonstrated mean time to publication of 12 to 32 months following abstract presentation with a median time of 19.6 months.¹⁶ Because we only have a 30-month follow-up, there may be abstracts still in the review process that are yet to be published, especially because the length of the review process varies by journal. We based our literature search on the first author of each PHM conference abstract submission, assuming that this presenting author would be one of the publishing authors even if not remaining first author; if this was not the case, we may have missed some abstracts that were subsequently published in full. Likewise, if a presenting author’s last name changed prior to the publication of a manuscript, a publication may have been missed. This limitation would cause us to underestimate the overall publication rate. It is not clear whether this would differentially affect the method of presentation. However, in this study, there was concordance between the presenting author and the publication’s first author in 87.8% of the abstracts subsequently published in full. Presenting authors who did not remain the first author on the published manuscript maintained authorship as either the senior author or second or third author, which may represent changes in the degree of involvement or a division of responsibilities for individuals working on a project together. While our search methods were comprehensive, there is a possibility that abstracts may have been published in a venue that was not searched. Additionally, we only reviewed abstracts submitted to PHM for 1 year. As the field matures and the number of fellowship programs increases, the quality of submitted abstracts may increase, leading to higher publication rates or shorter times to publication. It is also possible that the publication rate may not be reflective of PHM as a field because hospitalists may submit their work to conferences other than the PHM. Lastly, it may be more challenging to interpret any differences in impact factor because some journals, including Hospital Pediatrics (which represented a plurality of poster presentation abstracts that were subsequently published and is a relatively new journal), did not have an impact factor assigned during the study period. Assigning a 0 to journals without an impact factor may artificially lower the average impact factor reported. Furthermore, an impact factor, which is based on the frequency with which an individual journal’s articles are cited in scientific or medical publications, may not necessarily reflect a journal’s quality.

Of the 226 abstracts submitted to the 2014 PHM conference, approximately one-third were published in peer-reviewed journals within 30 months of the conference. Selection for oral presentation was found to be associated with subsequent publication as well as publication in journals with higher impact factors. The overall low publication rate may indicate a need for increased mentorship and resources for research development in this growing specialty. Improved mechanisms for author feedback at poster sessions may provide constructive suggestions for further development of these projects into full manuscripts or opportunities for trainees and early-career hospitalists to network with more experienced researchers in the field.

Disclosure

Drs. Herrmann, Hall, Kyler, Andrews, Williams, and Shah and Mr. Cochran have nothing to disclose. Dr. Wilson reports personal fees from the American Academy of Pediatrics during the conduct of the study. The authors have no financial relationships relevant to this article to disclose.

Pediatric hospital medicine (PHM) is one of the most rapidly growing disciplines in pediatrics,¹ with 8% of pediatric residency graduates each year entering the field.² Research plays an important role in advancing care in the field and is a critical component for board certification and fellowship accreditation.^3-6 The annual PHM conference, which has been jointly sponsored by the Academic Pediatric Association, the American Academy of Pediatrics, and the Society of Hospital Medicine, is an important venue for the dissemination of research findings. Abstract selection is determined by peer review; however, reviewers are provided with only a brief snapshot of the research, which may not contain sufficient information to fully evaluate the methodological quality of the work.^7-10 Additionally, while instructions are provided, reviewers often lack formal training in abstract review. Consequently, scores may vary.⁹

Publication in a peer-reviewed journal is considered a measure of research success because it requires more rigorous peer review than the abstract selection process at scientific meetings.^11-16 Rates of subsequent journal publication differ based on specialty and meeting, and they have been reported at 23% to 78%.^10,12,14-18 In pediatrics, publication rates after presentation at scientific meetings range from 36% to 63%, with mean time to publication ranging from 20 to 26 months following the meeting.^11,19,20 No studies have reviewed abstract submissions to the annual PHM meeting to determine if selection or presentation format is associated with subsequent publication in a peer-reviewed journal.

We sought to identify the publication rate of abstracts submitted to the 2014 PHM conference and determine whether presentation format was associated with the likelihood of subsequent journal publication or time to publication.

Study Design

Data for this retrospective cohort study were obtained from a database of all abstracts submitted for presentation at the 2014 PHM conference in Lake Buena Vista, Florida.

Main Exposures

The main exposure was presentation format, which was categorized as not presented (ie, rejected), poster presentation, or oral presentation. PHM has a blinded abstract peer-review process; in 2014, an average of 10 reviewers scored each abstract. Reviewers graded abstracts on a scale of 1 (best in category) to 7 (unacceptable for presentation) according to the following criteria: originality, scientific importance, methodological rigor, and quality of presentation. Abstracts with the lowest average scores in each content area, usually less than or equal to 3, were accepted as oral presentations while most abstracts with scores greater than 5 were rejected. For this study, information collected from each abstract included authors, if the primary author was a trainee, title, content area, and presentation format. Content areas included clinical research, educational research, health services research (HSR) and/or epidemiology, practice management research, and quality improvement. Abstracts were then grouped by presentation format and content area for analysis. The Pediatric Academic Societies (PAS) annual meeting, another common venue for the presentation of pediatric research, precedes the PHM conference. Because acceptance for PAS presentation may represent more strongly developed abstract submissions for PHM, we identified which abstracts had also been presented at the PAS conference that same year by cross-referencing authors and abstract titles with the PAS 2014 program.

Main Outcome Measures

All submissions were assessed for subsequent publication in peer-reviewed journals through January 2017 (30 months following the July 2014 PHM conference). To identify abstracts that went on to full publication, 2 authors (JC and LEH) independently searched for the lead author’s name and the presentation title in PubMed, Google Scholar, and MedEdPORTAL in January 2017. PubMed was searched using both the general search box and an advanced search for author and title. Google Scholar was added to capture manuscripts that may not have been indexed in PubMed at the time of our search. MedEdPORTAL, a common venue for the publication of educational initiatives that are not currently indexed in PubMed, was searched by lead author name via the general search box. If a full manuscript was published discussing similar outcomes or results and was written by the same authors who had submitted a PHM conference abstract, it was considered to have been published. The journal, month, and year of publication were recorded. For journals published every 2 months, the date of publication was recorded as falling between the 2 months. For those journals with biannual publication in the spring and fall, the months of March and October were used, respectively. The impact factor of the publication journal was also recorded for the year preceding publication. A journal’s impact factor is frequently used as a quantitative measure of journal quality and reflects the frequency with which a journal’s articles are cited in the scientific literature.²¹ Journals without an impact factor (eg, newer journals) were assigned a 0.

Data Analysis

All abstracts submitted to the PHM conference were analyzed based on content area and presentation format. The proportion of all abstracts subsequently published was determined for each format type and content area, and the odds ratio (OR) for publication after abstract submission was calculated using logistic regression. We calculated an adjusted OR for subsequent publication controlling for PAS presentation and the trainee status of the primary author. The journals most frequently publishing abstracts submitted to the PHM conference were identified. Median time to publication was calculated using the number of months elapsed between the PHM conference and publication date and compared across all abstract formats using Cox proportional hazards models adjusted for PAS presentation and trainee status. Kaplan-Meier survival curves were also generated for each of the 3 formats and compared using log-rank tests. The median impact factor was determined for each abstract format and compared using Wilcoxon rank-sum tests. Median impact factor by content area was compared using a Kruskal-Wallis test. All statistical analyses were performed using SAS version 9.2 (SAS Institute, Cary, NC). P values < 0.05 were considered statistically significant. In accordance with the Common Rule²² and the policies of the Cincinnati Children’s Hospital Medical Center Institutional Review Board, this research was not considered human subjects research.

For the 2014 PHM meeting, 226 abstracts were submitted, of which 183 (81.0%) were selected for presentation, including 154 (68.0%) as poster presentations and 29 (12.8%) as oral presentations. Of all submitted abstracts, 82 (36.3%) were published within 30 months following the meeting. Eighty-one of these (98.8%) were identified via PubMed, and 1 was found only in MedEdPORTAL. No additional publications were found via Google Scholar. The presenting author for the PHM abstract was the first author for 87.8% (n = 72) of the publications. A trainee was the presenting author for only 2 of these abstracts. For the publications in which the first author was not the presenting author, the presenting author was the senior author in 2 of the publications and the second or third author on the remaining 8. Of the abstracts accepted for presentation, 70 (38.3%) were subsequently published. Abstracts accepted for oral presentation had almost 7-fold greater odds of subsequent publication than those that were rejected (Table 1; OR 6.8; 95% confidence interval [CI], 2.4-19.4). Differences in the odds of publication for rejected abstracts compared with those accepted for poster presentation were not statistically significant (OR 1.2; 95% CI, 0.5-2.5).

About one-third of abstracts submitted to the 2014 PHM conference were subsequently published in peer-reviewed journals within 30 months of the conference. Compared with rejected abstracts, the rate of publication was significantly higher for abstracts selected for oral presentation but not for those selected for poster presentation. For abstracts ultimately published in journals, selection for oral presentation was significantly associated with both a shorter time to publication and a higher median journal impact factor compared with rejected abstracts. Time to publication and median journal impact factor were similar between rejected abstracts and those accepted for poster presentation. Our findings suggest that abstract reviewers may be able to identify which abstracts will ultimately withstand more stringent peer review in the publication process when accepting abstracts for oral presentation. However, the selection for poster presentation versus rejection may not be indicative of future publication or the impact factor of the subsequent publication journal.

Previous studies have reviewed publication rates after meetings of the European Society for Pediatric Urology (publication rate of 47%),¹¹ the Ambulatory Pediatric Association (now the Academic Pediatric Association; publication rate of 47%), the American Pediatric Society/Society for Pediatric Research (publication rate of 54%), and the PAS (publication rate of 45%).^19,20 Our lower publication rate of 36.3% may be attributed to the shorter follow-up time in our study (30 months from the PHM conference), whereas prior studies monitored for publication up to 60 months after the PAS conference.²⁰ Factors associated with subsequent publication include statistically significant results, a large sample size, and a randomized controlled trial study design.^15,16 The primary reason for nonpublication for up to 80% of abstracts is failure to submit a manuscript for publication.²³ A lack of time and fear of rejection after peer review are commonly cited explanations.^18,23,24 Individuals may view acceptance for an oral presentation as positive reinforcement and be more motivated to pursue subsequent manuscript publication than individuals whose abstracts are offered poster presentations or are rejected. Trainees frequently present abstracts at scientific meetings, representing 40.3% of primary authors submitting abstracts to PHM in 2014, but may not have sufficient time or mentorship to develop a complete manuscript.¹⁸ To our knowledge, there have been no publications that assess the impact of trainee status on subsequent publication after conference submission.

Our study demonstrated that selection for oral presentation was associated with subsequent publication, shorter time to publication, and publication in journals with higher impact factors. A 2005 Cochrane review also demonstrated that selection for oral presentation was associated with subsequent journal publication.¹⁶ Abstracts accepted for oral publication may represent work further along in the research process, with more developed methodology and results. The shorter time to publication for abstracts accepted for oral presentation could also reflect feedback provided by conference attendees after the presentation, whereas poster sessions frequently lack a formalized process for critique.

Carroll et al. found no difference in time to publication between abstracts accepted for presentation at the PAS and rejected abstracts.²⁰ Previous studies demonstrate that most abstracts presented at scientific meetings that are subsequently accepted for publication are published within 2 to 3 years of the meeting,¹² with publication rates as high as 98% within 3 years of presentation.¹⁷ In contrast to Carroll et al., we found that abstracts accepted for oral presentation had a 4-fold greater likelihood of publication at each month than rejected abstracts. However, abstracts accepted for poster presentation did not have a significant difference in the proportional hazard ratio models for publication compared with rejected abstracts. Because space considerations limit the number of abstracts that can be accepted for presentation at a conference, some abstracts that are suitable for future publication may have been rejected due to a lack of space. Because researchers often use scientific meetings as a forum to receive peer feedback,¹² authors who present at conferences may take more time to write a manuscript in order to incorporate this feedback.

The most common journal in which submitted abstracts were subsequently published was Hospital Pediatrics, representing twice as many published manuscripts as the second most frequent journal, Pediatrics. Hospital Pediatrics, which was first published in 2011, did not have an impact factor assigned during the study period. Yet, as a peer-reviewed journal dedicated to the field of PHM, it is well aligned with the research presented at the PHM meeting. It is unclear if Hospital Pediatrics is a journal to which pediatric hospitalists tend to submit manuscripts initially or if manuscripts are frequently submitted elsewhere prior to their publication in Hospital Pediatrics. Submission to other journals first likely extends the time to publication, especially for abstracts accepted for poster presentation, which may describe studies with less developed methods or results.

This study has several limitations. Previous studies have demonstrated mean time to publication of 12 to 32 months following abstract presentation with a median time of 19.6 months.¹⁶ Because we only have a 30-month follow-up, there may be abstracts still in the review process that are yet to be published, especially because the length of the review process varies by journal. We based our literature search on the first author of each PHM conference abstract submission, assuming that this presenting author would be one of the publishing authors even if not remaining first author; if this was not the case, we may have missed some abstracts that were subsequently published in full. Likewise, if a presenting author’s last name changed prior to the publication of a manuscript, a publication may have been missed. This limitation would cause us to underestimate the overall publication rate. It is not clear whether this would differentially affect the method of presentation. However, in this study, there was concordance between the presenting author and the publication’s first author in 87.8% of the abstracts subsequently published in full. Presenting authors who did not remain the first author on the published manuscript maintained authorship as either the senior author or second or third author, which may represent changes in the degree of involvement or a division of responsibilities for individuals working on a project together. While our search methods were comprehensive, there is a possibility that abstracts may have been published in a venue that was not searched. Additionally, we only reviewed abstracts submitted to PHM for 1 year. As the field matures and the number of fellowship programs increases, the quality of submitted abstracts may increase, leading to higher publication rates or shorter times to publication. It is also possible that the publication rate may not be reflective of PHM as a field because hospitalists may submit their work to conferences other than the PHM. Lastly, it may be more challenging to interpret any differences in impact factor because some journals, including Hospital Pediatrics (which represented a plurality of poster presentation abstracts that were subsequently published and is a relatively new journal), did not have an impact factor assigned during the study period. Assigning a 0 to journals without an impact factor may artificially lower the average impact factor reported. Furthermore, an impact factor, which is based on the frequency with which an individual journal’s articles are cited in scientific or medical publications, may not necessarily reflect a journal’s quality.

Of the 226 abstracts submitted to the 2014 PHM conference, approximately one-third were published in peer-reviewed journals within 30 months of the conference. Selection for oral presentation was found to be associated with subsequent publication as well as publication in journals with higher impact factors. The overall low publication rate may indicate a need for increased mentorship and resources for research development in this growing specialty. Improved mechanisms for author feedback at poster sessions may provide constructive suggestions for further development of these projects into full manuscripts or opportunities for trainees and early-career hospitalists to network with more experienced researchers in the field.

Disclosure

Drs. Herrmann, Hall, Kyler, Andrews, Williams, and Shah and Mr. Cochran have nothing to disclose. Dr. Wilson reports personal fees from the American Academy of Pediatrics during the conduct of the study. The authors have no financial relationships relevant to this article to disclose.

Pediatric hospital medicine (PHM) is one of the most rapidly growing disciplines in pediatrics,¹ with 8% of pediatric residency graduates each year entering the field.² Research plays an important role in advancing care in the field and is a critical component for board certification and fellowship accreditation.^3-6 The annual PHM conference, which has been jointly sponsored by the Academic Pediatric Association, the American Academy of Pediatrics, and the Society of Hospital Medicine, is an important venue for the dissemination of research findings. Abstract selection is determined by peer review; however, reviewers are provided with only a brief snapshot of the research, which may not contain sufficient information to fully evaluate the methodological quality of the work.^7-10 Additionally, while instructions are provided, reviewers often lack formal training in abstract review. Consequently, scores may vary.⁹

Publication in a peer-reviewed journal is considered a measure of research success because it requires more rigorous peer review than the abstract selection process at scientific meetings.^11-16 Rates of subsequent journal publication differ based on specialty and meeting, and they have been reported at 23% to 78%.^10,12,14-18 In pediatrics, publication rates after presentation at scientific meetings range from 36% to 63%, with mean time to publication ranging from 20 to 26 months following the meeting.^11,19,20 No studies have reviewed abstract submissions to the annual PHM meeting to determine if selection or presentation format is associated with subsequent publication in a peer-reviewed journal.

We sought to identify the publication rate of abstracts submitted to the 2014 PHM conference and determine whether presentation format was associated with the likelihood of subsequent journal publication or time to publication.

Study Design

Data for this retrospective cohort study were obtained from a database of all abstracts submitted for presentation at the 2014 PHM conference in Lake Buena Vista, Florida.

Main Exposures

The main exposure was presentation format, which was categorized as not presented (ie, rejected), poster presentation, or oral presentation. PHM has a blinded abstract peer-review process; in 2014, an average of 10 reviewers scored each abstract. Reviewers graded abstracts on a scale of 1 (best in category) to 7 (unacceptable for presentation) according to the following criteria: originality, scientific importance, methodological rigor, and quality of presentation. Abstracts with the lowest average scores in each content area, usually less than or equal to 3, were accepted as oral presentations while most abstracts with scores greater than 5 were rejected. For this study, information collected from each abstract included authors, if the primary author was a trainee, title, content area, and presentation format. Content areas included clinical research, educational research, health services research (HSR) and/or epidemiology, practice management research, and quality improvement. Abstracts were then grouped by presentation format and content area for analysis. The Pediatric Academic Societies (PAS) annual meeting, another common venue for the presentation of pediatric research, precedes the PHM conference. Because acceptance for PAS presentation may represent more strongly developed abstract submissions for PHM, we identified which abstracts had also been presented at the PAS conference that same year by cross-referencing authors and abstract titles with the PAS 2014 program.

Main Outcome Measures

All submissions were assessed for subsequent publication in peer-reviewed journals through January 2017 (30 months following the July 2014 PHM conference). To identify abstracts that went on to full publication, 2 authors (JC and LEH) independently searched for the lead author’s name and the presentation title in PubMed, Google Scholar, and MedEdPORTAL in January 2017. PubMed was searched using both the general search box and an advanced search for author and title. Google Scholar was added to capture manuscripts that may not have been indexed in PubMed at the time of our search. MedEdPORTAL, a common venue for the publication of educational initiatives that are not currently indexed in PubMed, was searched by lead author name via the general search box. If a full manuscript was published discussing similar outcomes or results and was written by the same authors who had submitted a PHM conference abstract, it was considered to have been published. The journal, month, and year of publication were recorded. For journals published every 2 months, the date of publication was recorded as falling between the 2 months. For those journals with biannual publication in the spring and fall, the months of March and October were used, respectively. The impact factor of the publication journal was also recorded for the year preceding publication. A journal’s impact factor is frequently used as a quantitative measure of journal quality and reflects the frequency with which a journal’s articles are cited in the scientific literature.²¹ Journals without an impact factor (eg, newer journals) were assigned a 0.

Data Analysis

All abstracts submitted to the PHM conference were analyzed based on content area and presentation format. The proportion of all abstracts subsequently published was determined for each format type and content area, and the odds ratio (OR) for publication after abstract submission was calculated using logistic regression. We calculated an adjusted OR for subsequent publication controlling for PAS presentation and the trainee status of the primary author. The journals most frequently publishing abstracts submitted to the PHM conference were identified. Median time to publication was calculated using the number of months elapsed between the PHM conference and publication date and compared across all abstract formats using Cox proportional hazards models adjusted for PAS presentation and trainee status. Kaplan-Meier survival curves were also generated for each of the 3 formats and compared using log-rank tests. The median impact factor was determined for each abstract format and compared using Wilcoxon rank-sum tests. Median impact factor by content area was compared using a Kruskal-Wallis test. All statistical analyses were performed using SAS version 9.2 (SAS Institute, Cary, NC). P values < 0.05 were considered statistically significant. In accordance with the Common Rule²² and the policies of the Cincinnati Children’s Hospital Medical Center Institutional Review Board, this research was not considered human subjects research.

For the 2014 PHM meeting, 226 abstracts were submitted, of which 183 (81.0%) were selected for presentation, including 154 (68.0%) as poster presentations and 29 (12.8%) as oral presentations. Of all submitted abstracts, 82 (36.3%) were published within 30 months following the meeting. Eighty-one of these (98.8%) were identified via PubMed, and 1 was found only in MedEdPORTAL. No additional publications were found via Google Scholar. The presenting author for the PHM abstract was the first author for 87.8% (n = 72) of the publications. A trainee was the presenting author for only 2 of these abstracts. For the publications in which the first author was not the presenting author, the presenting author was the senior author in 2 of the publications and the second or third author on the remaining 8. Of the abstracts accepted for presentation, 70 (38.3%) were subsequently published. Abstracts accepted for oral presentation had almost 7-fold greater odds of subsequent publication than those that were rejected (Table 1; OR 6.8; 95% confidence interval [CI], 2.4-19.4). Differences in the odds of publication for rejected abstracts compared with those accepted for poster presentation were not statistically significant (OR 1.2; 95% CI, 0.5-2.5).

About one-third of abstracts submitted to the 2014 PHM conference were subsequently published in peer-reviewed journals within 30 months of the conference. Compared with rejected abstracts, the rate of publication was significantly higher for abstracts selected for oral presentation but not for those selected for poster presentation. For abstracts ultimately published in journals, selection for oral presentation was significantly associated with both a shorter time to publication and a higher median journal impact factor compared with rejected abstracts. Time to publication and median journal impact factor were similar between rejected abstracts and those accepted for poster presentation. Our findings suggest that abstract reviewers may be able to identify which abstracts will ultimately withstand more stringent peer review in the publication process when accepting abstracts for oral presentation. However, the selection for poster presentation versus rejection may not be indicative of future publication or the impact factor of the subsequent publication journal.

Previous studies have reviewed publication rates after meetings of the European Society for Pediatric Urology (publication rate of 47%),¹¹ the Ambulatory Pediatric Association (now the Academic Pediatric Association; publication rate of 47%), the American Pediatric Society/Society for Pediatric Research (publication rate of 54%), and the PAS (publication rate of 45%).^19,20 Our lower publication rate of 36.3% may be attributed to the shorter follow-up time in our study (30 months from the PHM conference), whereas prior studies monitored for publication up to 60 months after the PAS conference.²⁰ Factors associated with subsequent publication include statistically significant results, a large sample size, and a randomized controlled trial study design.^15,16 The primary reason for nonpublication for up to 80% of abstracts is failure to submit a manuscript for publication.²³ A lack of time and fear of rejection after peer review are commonly cited explanations.^18,23,24 Individuals may view acceptance for an oral presentation as positive reinforcement and be more motivated to pursue subsequent manuscript publication than individuals whose abstracts are offered poster presentations or are rejected. Trainees frequently present abstracts at scientific meetings, representing 40.3% of primary authors submitting abstracts to PHM in 2014, but may not have sufficient time or mentorship to develop a complete manuscript.¹⁸ To our knowledge, there have been no publications that assess the impact of trainee status on subsequent publication after conference submission.

Our study demonstrated that selection for oral presentation was associated with subsequent publication, shorter time to publication, and publication in journals with higher impact factors. A 2005 Cochrane review also demonstrated that selection for oral presentation was associated with subsequent journal publication.¹⁶ Abstracts accepted for oral publication may represent work further along in the research process, with more developed methodology and results. The shorter time to publication for abstracts accepted for oral presentation could also reflect feedback provided by conference attendees after the presentation, whereas poster sessions frequently lack a formalized process for critique.

Carroll et al. found no difference in time to publication between abstracts accepted for presentation at the PAS and rejected abstracts.²⁰ Previous studies demonstrate that most abstracts presented at scientific meetings that are subsequently accepted for publication are published within 2 to 3 years of the meeting,¹² with publication rates as high as 98% within 3 years of presentation.¹⁷ In contrast to Carroll et al., we found that abstracts accepted for oral presentation had a 4-fold greater likelihood of publication at each month than rejected abstracts. However, abstracts accepted for poster presentation did not have a significant difference in the proportional hazard ratio models for publication compared with rejected abstracts. Because space considerations limit the number of abstracts that can be accepted for presentation at a conference, some abstracts that are suitable for future publication may have been rejected due to a lack of space. Because researchers often use scientific meetings as a forum to receive peer feedback,¹² authors who present at conferences may take more time to write a manuscript in order to incorporate this feedback.

The most common journal in which submitted abstracts were subsequently published was Hospital Pediatrics, representing twice as many published manuscripts as the second most frequent journal, Pediatrics. Hospital Pediatrics, which was first published in 2011, did not have an impact factor assigned during the study period. Yet, as a peer-reviewed journal dedicated to the field of PHM, it is well aligned with the research presented at the PHM meeting. It is unclear if Hospital Pediatrics is a journal to which pediatric hospitalists tend to submit manuscripts initially or if manuscripts are frequently submitted elsewhere prior to their publication in Hospital Pediatrics. Submission to other journals first likely extends the time to publication, especially for abstracts accepted for poster presentation, which may describe studies with less developed methods or results.

This study has several limitations. Previous studies have demonstrated mean time to publication of 12 to 32 months following abstract presentation with a median time of 19.6 months.¹⁶ Because we only have a 30-month follow-up, there may be abstracts still in the review process that are yet to be published, especially because the length of the review process varies by journal. We based our literature search on the first author of each PHM conference abstract submission, assuming that this presenting author would be one of the publishing authors even if not remaining first author; if this was not the case, we may have missed some abstracts that were subsequently published in full. Likewise, if a presenting author’s last name changed prior to the publication of a manuscript, a publication may have been missed. This limitation would cause us to underestimate the overall publication rate. It is not clear whether this would differentially affect the method of presentation. However, in this study, there was concordance between the presenting author and the publication’s first author in 87.8% of the abstracts subsequently published in full. Presenting authors who did not remain the first author on the published manuscript maintained authorship as either the senior author or second or third author, which may represent changes in the degree of involvement or a division of responsibilities for individuals working on a project together. While our search methods were comprehensive, there is a possibility that abstracts may have been published in a venue that was not searched. Additionally, we only reviewed abstracts submitted to PHM for 1 year. As the field matures and the number of fellowship programs increases, the quality of submitted abstracts may increase, leading to higher publication rates or shorter times to publication. It is also possible that the publication rate may not be reflective of PHM as a field because hospitalists may submit their work to conferences other than the PHM. Lastly, it may be more challenging to interpret any differences in impact factor because some journals, including Hospital Pediatrics (which represented a plurality of poster presentation abstracts that were subsequently published and is a relatively new journal), did not have an impact factor assigned during the study period. Assigning a 0 to journals without an impact factor may artificially lower the average impact factor reported. Furthermore, an impact factor, which is based on the frequency with which an individual journal’s articles are cited in scientific or medical publications, may not necessarily reflect a journal’s quality.

Of the 226 abstracts submitted to the 2014 PHM conference, approximately one-third were published in peer-reviewed journals within 30 months of the conference. Selection for oral presentation was found to be associated with subsequent publication as well as publication in journals with higher impact factors. The overall low publication rate may indicate a need for increased mentorship and resources for research development in this growing specialty. Improved mechanisms for author feedback at poster sessions may provide constructive suggestions for further development of these projects into full manuscripts or opportunities for trainees and early-career hospitalists to network with more experienced researchers in the field.

Disclosure

Drs. Herrmann, Hall, Kyler, Andrews, Williams, and Shah and Mr. Cochran have nothing to disclose. Dr. Wilson reports personal fees from the American Academy of Pediatrics during the conduct of the study. The authors have no financial relationships relevant to this article to disclose.

Healthcare systems are targeting effective strategies to improve patient safety and reduce hospital readmissions. Hospital readmissions can be detrimental to patients’ health, a source of avoidable healthcare costs, and are frequently a reflection of the quality of patient care during transitions of care. Medication reconciliation (Med Rec) was identified as 1 of 12 interventions that may reduce 30-day readmissions; however, rigorously designed studies are scarce.^1,2 Published systematic reviews and meta-analyses have produced mixed conclusions regarding the impact of Med Rec on unplanned 30-day readmissions.^2-4

In several studies, researchers have established the positive impact of Med Rec on reducing patient medication discrepancies and potential adverse drug events.^4-8 Pharmacy-led Med Rec interventions have been shown to easily identify more clinically relevant and higher impact medication discrepancies when compared to usual care.⁸ In a systematic review, Mueller et al.² suggest that there are several interrelated elements that determine if a Med Rec intervention will influence hospital readmissions. These elements form a multicomponent “bundle” of interventions, including a systematic medication history process, admission reconciliation, patient education on discharge, discharge reconciliation, and communication to outpatient providers.⁹ Several prospective randomized controlled studies have demonstrated lower readmission rates and fewer visits to the emergency department (ED) after implementing a comprehensive, interprofessional, bundled intervention (including Med Rec) from admission to discharge.^10-13 A 2016 systematic review and meta-analysis specifically evaluated pharmacy-led Med Rec programs (the majority of which included interventions involving multicomponent bundles) and demonstrated a significant reduction in posthospital healthcare utilization.¹⁴

Although comprehensive, interprofessional, bundled interventions have been shown to reduce readmission rates and ED visits in randomized controlled trials (RCTs), limited resources often prevent hospitals from consistently implementing all aspects of these multicomponent interventions. In practice, clinicians may provide varying components of the bundle, such as the combination of admission medication history by the pharmacist and discharge Med Rec completed by the physician alone. The unique impact of combined pharmacist and prescriber Med Rec interventions from admission to discharge on readmissions remains inconclusive. Further, it is unclear which high-risk patient groups will benefit the most from these interventions. We set out to evaluate the impact of an enhanced, interprofessional Med Rec process from admission to discharge (characterized within the context of a novel taxonomy continuum that specifies clinician involvement and intensity of services) on readmissions to hospital and ED visits within 30 days of discharge.

We conducted a retrospective, observational, analytical cohort study using QuadraMed’s Computerized Patient Record and the EMITT (Electronic Medication Information Transfer Tool)¹⁵ to collect data from 2007 to 2011.

Setting

The study was conducted at a 417-bed tertiary care teaching hospital in Toronto, Ontario, Canada.

Med Rec Process and Description of Exposure (Intervention)

The targeted clinical areas had sustained interprofessional models of patient care in place from admission to discharge. They also were actively using an in-house EMITT to facilitate the documentation and tracking of Med Rec efforts throughout patient admission, transfer, and discharge.¹⁵ On admission, the pharmacist conducted a best possible medication history (BPMH). A BPMH provides the cornerstone for Med Rec. It differs from a routine medication history in that it involves (1) a systematic process for interviewing the patient (or family) and (2) a review of at least one other reliable source of information (eg, a provincial medication database, an inspection of medication vials, or contact with the community pharmacy) to obtain and verify patient medications (prescribed and nonprescribed). The pharmacist recorded the BPMH in the electronic patient record. The application supported admission and discharge Med Rec. On discharge, there were 2 options: (1) the prescriber alone would review and complete the discharge Med Rec and generate electronic prescriptions (Table 1, Silver level care) or (2) the pharmacist would collaborate with the prescriber to complete the discharge reconciliation and the prescriber would electronically generate prescriptions (Table 1, Gold level care). All clinical areas had a combined pharmacist and prescriber Med Rec model in place at admission, but the proportion of patients receiving discharge reconciliation completed by pharmacist and prescriber versus the prescriber-alone varied based on the individual clinician’s practices.

Patient Selection

All consecutive hospitalized patients admitted and discharged by the general internal medicine [GIM] service from March 2007 to December 2011 were included. The GIM service was chosen for the main analysis because they had been performing the intervention for the longest period of time and had the largest population of patients. Patients were identified via their hospital-specific medical record identification number and specific hospital-visit number. Patients were excluded if any of the following occurred: (1) the length of stay of their index admission was less than 24 hours; (2) they died during the visit; (3) they were transferred to a separate acute care inpatient facility; or (4) they left hospital against medical advice. Patient visits were excluded as index cases from the analysis if they were returning within 90 days of a previous discharge.

Outcomes

The primary study outcome was the occurrence of an inpatient readmission or ED visit within 30 days of discharge. In our secondary analyses, we examined the impact of the intervention on high-risk patient populations, such as those ≥65 years of age, with a length of stay, acuity of admission, Charlson comorbidity index, and emergency department visits in past 6 months (LACE) index score ≥10 (see supplementary Appendix 1 for LACE score description), on high-alert medications (1 or more of warfarin, insulin, digoxin, and opioids), and on ≥10 medications.

Data Collection

Identification of Exposure of Interest

We used the electronic database to capture all patients who received pharmacist and prescriber supported admission-to-discharge reconciliation. We explicitly defined increasing intensity of Med Rec care in categories of Bronze, Silver, and Gold care levels (Table 1). The exposed (intervention) group received an enhanced Med Rec bundle (patients receiving Gold level care). The control group was made of patients receiving a partial Med Rec Bundle (patients receiving Silver or Bronze level of care or below).

Determination of Hospital Visits

A search of administrative databases was used to determine if patients admitted to the targeted services had an ED visit or urgent inpatient admission to the study hospital within 30 days.

Statistical Analysis

A logistic regression for outcomes was performed. This yielded an adjusted odds ratio with a 95% confidence interval (CI) between the intervention and control groups. Statistical significance was determined with a 2-sided α level of 0.05. In the analysis, we used Statistical Analysis Software version 9.2.

In our multivariate logistic regression model, we adjusted for confounding factors that might influence the patients’ risk of readmission or the type of Med Rec they received upon discharge. By using administrative databases, patient level demographics, and the Charlson comorbidity index, the most responsible diagnosis and disease burden were collected. Medication-related factors collected included the number of medications on discharge and the presence of predefined high-alert medications. The number of medications on the medication discharge list was determined by using the electronic database. The final adjustment model included age, gender, the number of medications on discharge, and the LACE index score (supplementary Appendix 1). The LACE index score has been validated in Ontario, Canada, populations to quantify the risk of death or unplanned readmission within 30 days of discharge.²⁴

Propensity Score Adjustment

Propensity scoring (probability of treatment assignment conditional on observed baseline characteristics) was planned a priori to account for possible factors that would impact whether a patient received the intervention or control care levels. The propensity score for receiving Med Rec was computed from a logistic model using Med Rec as the outcome. A structured iterative approach was used to refine this model to achieve covariate balance within the matched pairs. Covariate balance was measured by the standardized difference, in which an absolute standardized difference >10% represents meaningful imbalance.²⁵ From the original cohort, we attempted to match patients who had the intervention to patients from the control by means of a matching algorithm using the logit of the propensity score for receiving the intervention.²⁶

Subgroup Analysis

We also examined the impact of the intervention on high-risk patient populations such as those ≥65 years of age, with a LACE index score ≥10, on high-alert medications, and on ≥10 medications. A univariate analysis was conducted to identify patient-related risk predictors that may be independently correlated with a higher risk of hospital visits.

Baseline Characteristics

A total of 8678 patients representing 9931 unique visits met the inclusion criteria for analysis. There were 2541 unique visits (approximately 26% of visits) in the intervention group that received Gold level care and 7390 unique visits in the control group. The patients in the control group were largely patients who received the original standard of care at the institution, Silver level care (67% of the control group). Patients who received Bronze level care or less comprised 33% of the control group.

Patients in the intervention group were significantly older (average of 68 years old versus 64 years old) and on more medications. They also notably had a longer duration of stay in hospital, an increased percentage of visits with a LACE index score ≥10, and were more likely to be discharged home on a high-alert medication and with supports (Table 2).

Main Analysis

The main unadjusted analysis of GIM patients (n = 9931 visits) did not detect a difference in 30-day ED visits and readmissions between the intervention group (540 out of 2541; 21.2%) and control (1423 out of 7390; 19.3%; Table 3). By using a multivariate logistic regression model to account for age, sex, LACE index, and number of medications on discharge, the adjusted odds ratio was 1.06 (95% CI, 0.95-1.19; P = 0.33). After propensity score adjustment, the relative risk of readmission was 0.88 (16.7% vs 18.9%; 95% CI, 0.59-1.32; P = 0.54).

Secondary Analyses

In each predefined high-risk patient subgroup (age ≥65, LACE index score ≥10, number of discharge medications ≥10, and the presence of high-alert medications), analyses of our primary endpoint did not detect significant adjusted odds ratios (Table 4). In our univariate analysis, increasing number of medications, LACE index score, and male gender were independently correlated with a higher risk of hospital visits (supplementary Appendix 2).

Med Rec is widely recommended as a patient safety strategy to prevent clinically significant medication discrepancies at transitions in care.^4-9 However, Med Rec varies widely in terms of what it entails and who delivers it, with the preponderance of evidence suggesting an impact on clinically significant medication discrepancies only when interprofessional care delivered includes a central role for pharmacists.²⁷ Furthermore, Med Rec appears to impact short term readmissions only when embedded in a broader, multifaceted, bundled intervention in which pharmacists or other team members educate patients about their medications and deliver postdischarge follow-up phone calls.^10-13

As very few hospitals have the resources to sustainably deliver intensive care bundles that are represented in RCTs (characterized by Platinum and Diamond levels of care in Table 1), in our observational study, we sought to explore whether a resource-attainable, enhanced Med Rec care bundle (Gold level) had an impact on hospital utilization compared to partial Med Rec care bundles (Bronze and Silver levels). In our findings, we did not detect a significant difference on ED visits and readmissions within 30 days between enhanced and partial care bundles. In a secondary analysis of the influence of the intervention on prespecified high-risk patient subgroups, we also did not detect a difference.

As far as we are aware, our long-term, observational study is the largest to date to explore a real-life, enhanced Med Rec intervention and examine its impact on meaningful patient outcomes. We extrapolated that our intervention group received several critical attributes of a successful bundle as discussed by Mueller in a systematic review.² Our intervention included the following: (1) a systematic BPMH process on admission; (2) integrated admission-to-discharge reconciliation processes; (3) discharge delineation of medication changes since admission; (4) pharmacist involvement in reconciliation from admission to discharge; (5) an electronic platform; and (6) formal discharge reconciliation with interprofessional collaboration. Additional components in the bundle described by Mueller included the following: patient education at discharge, postdischarge communication with the patient, and communication with outpatient providers and medication management.

In our results, we did not find a difference in outcomes between the intervention and control groups. Therefore, it is possible that the enhanced bundle’s focus on interprofessional involvement in discharge reconciliation (Gold care level) has no impact on hospital utilization compared to partial care bundles (Silver and Bronze levels). Kwan et al.³ describe similar findings in their systematic review, in which they evaluated the effects of hospital-based Med Rec on unintentional discrepancies with nontrivial risks for harm to patients on 30-day postdischarge hospital visits. Kwan et al.³ concluded that larger well-designed studies are required to further evaluate this outcome, but authors of current published studies suggest that Med Rec alone probably does not reduce postdischarge hospital utilization within 30 days. Med Rec may have a more significant impact on utilization when bundled with other interventions that improve discharge coordination.³

There may be several reasons why we were unable to detect a significant difference between the intervention and control groups. One limitation is that our nonrandomized, retrospective design may have led to unmeasured confounders that impacted allocation into the intervention group versus the control group. It was notable that patients in the intervention group had an increased age, longer duration of hospital stay, more medications, and high-alert medications on discharge compared to the control group and that may have biased our results towards the null hypothesis. Although the propensity score analysis attempted to adjust for this, it also did not detect a significant difference between groups.

In addition, the existing standard of care during the study period allowed for patients in the control group to receive varying levels of Med Rec. Ideally, we would have compared the intervention to a placebo group that did not receive any Med Rec-related care elements. However, as this was a real-life observational study, the majority of patients received some Med Rec services as a part of the standard of care. As a result, 67% of patients in the control group received Silver level Med Rec with a BPMH, admission reconciliation, and prescriber-only discharge reconciliation. This may have made it more difficult to show an incremental benefit on readmissions between the intervention and control.

Also, our primary outcome of all-cause ED or hospital readmissions within 30 days may not have been sensitive enough to detect the effect of Med Rec interventions alone. Only a small proportion of readmissions within 30 days of discharge are preventable and many patient and community level factors responsible for readmissions cannot be controlled by the hospital’s actions.²⁸ Comprehensive pharmacy interventions have demonstrated decreased hospitalizations and emergency visits at 12 months; however, the largest impact was seen on the more specific outcome of medication-related hospitalizations (80% reduction).²⁹ Lastly, another limitation was that we were unable to capture hospital visits to other centres. However, in our region, almost 75% of readmissions are to the same site as the initial hospitalization.³⁰

Overall, our findings in this study and novel characterization of Med Rec services are relevant to many hospital sites that are striving to implement integrated Med Rec with limited healthcare resources. Although interprofessional Med Rec likely reduces clinically significant medication discrepancies, enhanced interprofessional Med Rec on discharge (Gold Med Rec) alone may not be enough to impact hospital utilization compared to partial Med Rec services (Silver and Bronze Med Rec). Further research into practical, targeted Med Rec bundles on more specific outcomes (such as preventable postdischarge adverse events, “avoidable” hospital readmissions, and medication-related readmissions) may detect a significant benefit.

A long-term observational evaluation of interprofessional Med Rec did not detect a difference in 30-day postdischarge patient hospital visits between patients who received enhanced versus partial Med Rec patient care bundles. Researchers of future prospective studies could focus on evaluating high-risk populations or specific elements of Med Rec services on avoidable medication-related hospital admissions and postdischarge adverse drug events.

Acknowledgments

The authors thank Nita Dhir, MBA.

Presented as a poster and oral presentation at the 2012 American College of Clinical Pharmacy Annual Meeting, Hollywood, Florida, October 21-24, 2012, and as an encore poster presentation at the Canadian Society of Hospital Pharmacists Professional Practice Conference, Toronto, Canada, Feb 3, 2013.

Disclosure

The authors declare no conflicts of interest related to the manuscript submitted. All monies used for the research came from the University Health Network Department of Pharmacy Budget, including the pharmacy residency program.

Healthcare systems are targeting effective strategies to improve patient safety and reduce hospital readmissions. Hospital readmissions can be detrimental to patients’ health, a source of avoidable healthcare costs, and are frequently a reflection of the quality of patient care during transitions of care. Medication reconciliation (Med Rec) was identified as 1 of 12 interventions that may reduce 30-day readmissions; however, rigorously designed studies are scarce.^1,2 Published systematic reviews and meta-analyses have produced mixed conclusions regarding the impact of Med Rec on unplanned 30-day readmissions.^2-4

In several studies, researchers have established the positive impact of Med Rec on reducing patient medication discrepancies and potential adverse drug events.^4-8 Pharmacy-led Med Rec interventions have been shown to easily identify more clinically relevant and higher impact medication discrepancies when compared to usual care.⁸ In a systematic review, Mueller et al.² suggest that there are several interrelated elements that determine if a Med Rec intervention will influence hospital readmissions. These elements form a multicomponent “bundle” of interventions, including a systematic medication history process, admission reconciliation, patient education on discharge, discharge reconciliation, and communication to outpatient providers.⁹ Several prospective randomized controlled studies have demonstrated lower readmission rates and fewer visits to the emergency department (ED) after implementing a comprehensive, interprofessional, bundled intervention (including Med Rec) from admission to discharge.^10-13 A 2016 systematic review and meta-analysis specifically evaluated pharmacy-led Med Rec programs (the majority of which included interventions involving multicomponent bundles) and demonstrated a significant reduction in posthospital healthcare utilization.¹⁴

Although comprehensive, interprofessional, bundled interventions have been shown to reduce readmission rates and ED visits in randomized controlled trials (RCTs), limited resources often prevent hospitals from consistently implementing all aspects of these multicomponent interventions. In practice, clinicians may provide varying components of the bundle, such as the combination of admission medication history by the pharmacist and discharge Med Rec completed by the physician alone. The unique impact of combined pharmacist and prescriber Med Rec interventions from admission to discharge on readmissions remains inconclusive. Further, it is unclear which high-risk patient groups will benefit the most from these interventions. We set out to evaluate the impact of an enhanced, interprofessional Med Rec process from admission to discharge (characterized within the context of a novel taxonomy continuum that specifies clinician involvement and intensity of services) on readmissions to hospital and ED visits within 30 days of discharge.

We conducted a retrospective, observational, analytical cohort study using QuadraMed’s Computerized Patient Record and the EMITT (Electronic Medication Information Transfer Tool)¹⁵ to collect data from 2007 to 2011.

Setting

The study was conducted at a 417-bed tertiary care teaching hospital in Toronto, Ontario, Canada.

Med Rec Process and Description of Exposure (Intervention)

The targeted clinical areas had sustained interprofessional models of patient care in place from admission to discharge. They also were actively using an in-house EMITT to facilitate the documentation and tracking of Med Rec efforts throughout patient admission, transfer, and discharge.¹⁵ On admission, the pharmacist conducted a best possible medication history (BPMH). A BPMH provides the cornerstone for Med Rec. It differs from a routine medication history in that it involves (1) a systematic process for interviewing the patient (or family) and (2) a review of at least one other reliable source of information (eg, a provincial medication database, an inspection of medication vials, or contact with the community pharmacy) to obtain and verify patient medications (prescribed and nonprescribed). The pharmacist recorded the BPMH in the electronic patient record. The application supported admission and discharge Med Rec. On discharge, there were 2 options: (1) the prescriber alone would review and complete the discharge Med Rec and generate electronic prescriptions (Table 1, Silver level care) or (2) the pharmacist would collaborate with the prescriber to complete the discharge reconciliation and the prescriber would electronically generate prescriptions (Table 1, Gold level care). All clinical areas had a combined pharmacist and prescriber Med Rec model in place at admission, but the proportion of patients receiving discharge reconciliation completed by pharmacist and prescriber versus the prescriber-alone varied based on the individual clinician’s practices.

Patient Selection

All consecutive hospitalized patients admitted and discharged by the general internal medicine [GIM] service from March 2007 to December 2011 were included. The GIM service was chosen for the main analysis because they had been performing the intervention for the longest period of time and had the largest population of patients. Patients were identified via their hospital-specific medical record identification number and specific hospital-visit number. Patients were excluded if any of the following occurred: (1) the length of stay of their index admission was less than 24 hours; (2) they died during the visit; (3) they were transferred to a separate acute care inpatient facility; or (4) they left hospital against medical advice. Patient visits were excluded as index cases from the analysis if they were returning within 90 days of a previous discharge.

Outcomes

The primary study outcome was the occurrence of an inpatient readmission or ED visit within 30 days of discharge. In our secondary analyses, we examined the impact of the intervention on high-risk patient populations, such as those ≥65 years of age, with a length of stay, acuity of admission, Charlson comorbidity index, and emergency department visits in past 6 months (LACE) index score ≥10 (see supplementary Appendix 1 for LACE score description), on high-alert medications (1 or more of warfarin, insulin, digoxin, and opioids), and on ≥10 medications.

Data Collection

Identification of Exposure of Interest

We used the electronic database to capture all patients who received pharmacist and prescriber supported admission-to-discharge reconciliation. We explicitly defined increasing intensity of Med Rec care in categories of Bronze, Silver, and Gold care levels (Table 1). The exposed (intervention) group received an enhanced Med Rec bundle (patients receiving Gold level care). The control group was made of patients receiving a partial Med Rec Bundle (patients receiving Silver or Bronze level of care or below).

Determination of Hospital Visits

A search of administrative databases was used to determine if patients admitted to the targeted services had an ED visit or urgent inpatient admission to the study hospital within 30 days.

Statistical Analysis

A logistic regression for outcomes was performed. This yielded an adjusted odds ratio with a 95% confidence interval (CI) between the intervention and control groups. Statistical significance was determined with a 2-sided α level of 0.05. In the analysis, we used Statistical Analysis Software version 9.2.

In our multivariate logistic regression model, we adjusted for confounding factors that might influence the patients’ risk of readmission or the type of Med Rec they received upon discharge. By using administrative databases, patient level demographics, and the Charlson comorbidity index, the most responsible diagnosis and disease burden were collected. Medication-related factors collected included the number of medications on discharge and the presence of predefined high-alert medications. The number of medications on the medication discharge list was determined by using the electronic database. The final adjustment model included age, gender, the number of medications on discharge, and the LACE index score (supplementary Appendix 1). The LACE index score has been validated in Ontario, Canada, populations to quantify the risk of death or unplanned readmission within 30 days of discharge.²⁴

Propensity Score Adjustment

Propensity scoring (probability of treatment assignment conditional on observed baseline characteristics) was planned a priori to account for possible factors that would impact whether a patient received the intervention or control care levels. The propensity score for receiving Med Rec was computed from a logistic model using Med Rec as the outcome. A structured iterative approach was used to refine this model to achieve covariate balance within the matched pairs. Covariate balance was measured by the standardized difference, in which an absolute standardized difference >10% represents meaningful imbalance.²⁵ From the original cohort, we attempted to match patients who had the intervention to patients from the control by means of a matching algorithm using the logit of the propensity score for receiving the intervention.²⁶

Subgroup Analysis

We also examined the impact of the intervention on high-risk patient populations such as those ≥65 years of age, with a LACE index score ≥10, on high-alert medications, and on ≥10 medications. A univariate analysis was conducted to identify patient-related risk predictors that may be independently correlated with a higher risk of hospital visits.

Baseline Characteristics

A total of 8678 patients representing 9931 unique visits met the inclusion criteria for analysis. There were 2541 unique visits (approximately 26% of visits) in the intervention group that received Gold level care and 7390 unique visits in the control group. The patients in the control group were largely patients who received the original standard of care at the institution, Silver level care (67% of the control group). Patients who received Bronze level care or less comprised 33% of the control group.

Patients in the intervention group were significantly older (average of 68 years old versus 64 years old) and on more medications. They also notably had a longer duration of stay in hospital, an increased percentage of visits with a LACE index score ≥10, and were more likely to be discharged home on a high-alert medication and with supports (Table 2).

Main Analysis

The main unadjusted analysis of GIM patients (n = 9931 visits) did not detect a difference in 30-day ED visits and readmissions between the intervention group (540 out of 2541; 21.2%) and control (1423 out of 7390; 19.3%; Table 3). By using a multivariate logistic regression model to account for age, sex, LACE index, and number of medications on discharge, the adjusted odds ratio was 1.06 (95% CI, 0.95-1.19; P = 0.33). After propensity score adjustment, the relative risk of readmission was 0.88 (16.7% vs 18.9%; 95% CI, 0.59-1.32; P = 0.54).

Secondary Analyses

In each predefined high-risk patient subgroup (age ≥65, LACE index score ≥10, number of discharge medications ≥10, and the presence of high-alert medications), analyses of our primary endpoint did not detect significant adjusted odds ratios (Table 4). In our univariate analysis, increasing number of medications, LACE index score, and male gender were independently correlated with a higher risk of hospital visits (supplementary Appendix 2).

Med Rec is widely recommended as a patient safety strategy to prevent clinically significant medication discrepancies at transitions in care.^4-9 However, Med Rec varies widely in terms of what it entails and who delivers it, with the preponderance of evidence suggesting an impact on clinically significant medication discrepancies only when interprofessional care delivered includes a central role for pharmacists.²⁷ Furthermore, Med Rec appears to impact short term readmissions only when embedded in a broader, multifaceted, bundled intervention in which pharmacists or other team members educate patients about their medications and deliver postdischarge follow-up phone calls.^10-13

As very few hospitals have the resources to sustainably deliver intensive care bundles that are represented in RCTs (characterized by Platinum and Diamond levels of care in Table 1), in our observational study, we sought to explore whether a resource-attainable, enhanced Med Rec care bundle (Gold level) had an impact on hospital utilization compared to partial Med Rec care bundles (Bronze and Silver levels). In our findings, we did not detect a significant difference on ED visits and readmissions within 30 days between enhanced and partial care bundles. In a secondary analysis of the influence of the intervention on prespecified high-risk patient subgroups, we also did not detect a difference.

As far as we are aware, our long-term, observational study is the largest to date to explore a real-life, enhanced Med Rec intervention and examine its impact on meaningful patient outcomes. We extrapolated that our intervention group received several critical attributes of a successful bundle as discussed by Mueller in a systematic review.² Our intervention included the following: (1) a systematic BPMH process on admission; (2) integrated admission-to-discharge reconciliation processes; (3) discharge delineation of medication changes since admission; (4) pharmacist involvement in reconciliation from admission to discharge; (5) an electronic platform; and (6) formal discharge reconciliation with interprofessional collaboration. Additional components in the bundle described by Mueller included the following: patient education at discharge, postdischarge communication with the patient, and communication with outpatient providers and medication management.

In our results, we did not find a difference in outcomes between the intervention and control groups. Therefore, it is possible that the enhanced bundle’s focus on interprofessional involvement in discharge reconciliation (Gold care level) has no impact on hospital utilization compared to partial care bundles (Silver and Bronze levels). Kwan et al.³ describe similar findings in their systematic review, in which they evaluated the effects of hospital-based Med Rec on unintentional discrepancies with nontrivial risks for harm to patients on 30-day postdischarge hospital visits. Kwan et al.³ concluded that larger well-designed studies are required to further evaluate this outcome, but authors of current published studies suggest that Med Rec alone probably does not reduce postdischarge hospital utilization within 30 days. Med Rec may have a more significant impact on utilization when bundled with other interventions that improve discharge coordination.³

There may be several reasons why we were unable to detect a significant difference between the intervention and control groups. One limitation is that our nonrandomized, retrospective design may have led to unmeasured confounders that impacted allocation into the intervention group versus the control group. It was notable that patients in the intervention group had an increased age, longer duration of hospital stay, more medications, and high-alert medications on discharge compared to the control group and that may have biased our results towards the null hypothesis. Although the propensity score analysis attempted to adjust for this, it also did not detect a significant difference between groups.

In addition, the existing standard of care during the study period allowed for patients in the control group to receive varying levels of Med Rec. Ideally, we would have compared the intervention to a placebo group that did not receive any Med Rec-related care elements. However, as this was a real-life observational study, the majority of patients received some Med Rec services as a part of the standard of care. As a result, 67% of patients in the control group received Silver level Med Rec with a BPMH, admission reconciliation, and prescriber-only discharge reconciliation. This may have made it more difficult to show an incremental benefit on readmissions between the intervention and control.

Also, our primary outcome of all-cause ED or hospital readmissions within 30 days may not have been sensitive enough to detect the effect of Med Rec interventions alone. Only a small proportion of readmissions within 30 days of discharge are preventable and many patient and community level factors responsible for readmissions cannot be controlled by the hospital’s actions.²⁸ Comprehensive pharmacy interventions have demonstrated decreased hospitalizations and emergency visits at 12 months; however, the largest impact was seen on the more specific outcome of medication-related hospitalizations (80% reduction).²⁹ Lastly, another limitation was that we were unable to capture hospital visits to other centres. However, in our region, almost 75% of readmissions are to the same site as the initial hospitalization.³⁰

Overall, our findings in this study and novel characterization of Med Rec services are relevant to many hospital sites that are striving to implement integrated Med Rec with limited healthcare resources. Although interprofessional Med Rec likely reduces clinically significant medication discrepancies, enhanced interprofessional Med Rec on discharge (Gold Med Rec) alone may not be enough to impact hospital utilization compared to partial Med Rec services (Silver and Bronze Med Rec). Further research into practical, targeted Med Rec bundles on more specific outcomes (such as preventable postdischarge adverse events, “avoidable” hospital readmissions, and medication-related readmissions) may detect a significant benefit.

A long-term observational evaluation of interprofessional Med Rec did not detect a difference in 30-day postdischarge patient hospital visits between patients who received enhanced versus partial Med Rec patient care bundles. Researchers of future prospective studies could focus on evaluating high-risk populations or specific elements of Med Rec services on avoidable medication-related hospital admissions and postdischarge adverse drug events.

Acknowledgments

The authors thank Nita Dhir, MBA.

Presented as a poster and oral presentation at the 2012 American College of Clinical Pharmacy Annual Meeting, Hollywood, Florida, October 21-24, 2012, and as an encore poster presentation at the Canadian Society of Hospital Pharmacists Professional Practice Conference, Toronto, Canada, Feb 3, 2013.

Disclosure

The authors declare no conflicts of interest related to the manuscript submitted. All monies used for the research came from the University Health Network Department of Pharmacy Budget, including the pharmacy residency program.

Healthcare systems are targeting effective strategies to improve patient safety and reduce hospital readmissions. Hospital readmissions can be detrimental to patients’ health, a source of avoidable healthcare costs, and are frequently a reflection of the quality of patient care during transitions of care. Medication reconciliation (Med Rec) was identified as 1 of 12 interventions that may reduce 30-day readmissions; however, rigorously designed studies are scarce.^1,2 Published systematic reviews and meta-analyses have produced mixed conclusions regarding the impact of Med Rec on unplanned 30-day readmissions.^2-4

In several studies, researchers have established the positive impact of Med Rec on reducing patient medication discrepancies and potential adverse drug events.^4-8 Pharmacy-led Med Rec interventions have been shown to easily identify more clinically relevant and higher impact medication discrepancies when compared to usual care.⁸ In a systematic review, Mueller et al.² suggest that there are several interrelated elements that determine if a Med Rec intervention will influence hospital readmissions. These elements form a multicomponent “bundle” of interventions, including a systematic medication history process, admission reconciliation, patient education on discharge, discharge reconciliation, and communication to outpatient providers.⁹ Several prospective randomized controlled studies have demonstrated lower readmission rates and fewer visits to the emergency department (ED) after implementing a comprehensive, interprofessional, bundled intervention (including Med Rec) from admission to discharge.^10-13 A 2016 systematic review and meta-analysis specifically evaluated pharmacy-led Med Rec programs (the majority of which included interventions involving multicomponent bundles) and demonstrated a significant reduction in posthospital healthcare utilization.¹⁴

Although comprehensive, interprofessional, bundled interventions have been shown to reduce readmission rates and ED visits in randomized controlled trials (RCTs), limited resources often prevent hospitals from consistently implementing all aspects of these multicomponent interventions. In practice, clinicians may provide varying components of the bundle, such as the combination of admission medication history by the pharmacist and discharge Med Rec completed by the physician alone. The unique impact of combined pharmacist and prescriber Med Rec interventions from admission to discharge on readmissions remains inconclusive. Further, it is unclear which high-risk patient groups will benefit the most from these interventions. We set out to evaluate the impact of an enhanced, interprofessional Med Rec process from admission to discharge (characterized within the context of a novel taxonomy continuum that specifies clinician involvement and intensity of services) on readmissions to hospital and ED visits within 30 days of discharge.

We conducted a retrospective, observational, analytical cohort study using QuadraMed’s Computerized Patient Record and the EMITT (Electronic Medication Information Transfer Tool)¹⁵ to collect data from 2007 to 2011.

Setting

The study was conducted at a 417-bed tertiary care teaching hospital in Toronto, Ontario, Canada.

Med Rec Process and Description of Exposure (Intervention)

The targeted clinical areas had sustained interprofessional models of patient care in place from admission to discharge. They also were actively using an in-house EMITT to facilitate the documentation and tracking of Med Rec efforts throughout patient admission, transfer, and discharge.¹⁵ On admission, the pharmacist conducted a best possible medication history (BPMH). A BPMH provides the cornerstone for Med Rec. It differs from a routine medication history in that it involves (1) a systematic process for interviewing the patient (or family) and (2) a review of at least one other reliable source of information (eg, a provincial medication database, an inspection of medication vials, or contact with the community pharmacy) to obtain and verify patient medications (prescribed and nonprescribed). The pharmacist recorded the BPMH in the electronic patient record. The application supported admission and discharge Med Rec. On discharge, there were 2 options: (1) the prescriber alone would review and complete the discharge Med Rec and generate electronic prescriptions (Table 1, Silver level care) or (2) the pharmacist would collaborate with the prescriber to complete the discharge reconciliation and the prescriber would electronically generate prescriptions (Table 1, Gold level care). All clinical areas had a combined pharmacist and prescriber Med Rec model in place at admission, but the proportion of patients receiving discharge reconciliation completed by pharmacist and prescriber versus the prescriber-alone varied based on the individual clinician’s practices.

Patient Selection

All consecutive hospitalized patients admitted and discharged by the general internal medicine [GIM] service from March 2007 to December 2011 were included. The GIM service was chosen for the main analysis because they had been performing the intervention for the longest period of time and had the largest population of patients. Patients were identified via their hospital-specific medical record identification number and specific hospital-visit number. Patients were excluded if any of the following occurred: (1) the length of stay of their index admission was less than 24 hours; (2) they died during the visit; (3) they were transferred to a separate acute care inpatient facility; or (4) they left hospital against medical advice. Patient visits were excluded as index cases from the analysis if they were returning within 90 days of a previous discharge.

Outcomes

The primary study outcome was the occurrence of an inpatient readmission or ED visit within 30 days of discharge. In our secondary analyses, we examined the impact of the intervention on high-risk patient populations, such as those ≥65 years of age, with a length of stay, acuity of admission, Charlson comorbidity index, and emergency department visits in past 6 months (LACE) index score ≥10 (see supplementary Appendix 1 for LACE score description), on high-alert medications (1 or more of warfarin, insulin, digoxin, and opioids), and on ≥10 medications.

Data Collection

Identification of Exposure of Interest

We used the electronic database to capture all patients who received pharmacist and prescriber supported admission-to-discharge reconciliation. We explicitly defined increasing intensity of Med Rec care in categories of Bronze, Silver, and Gold care levels (Table 1). The exposed (intervention) group received an enhanced Med Rec bundle (patients receiving Gold level care). The control group was made of patients receiving a partial Med Rec Bundle (patients receiving Silver or Bronze level of care or below).

Determination of Hospital Visits

A search of administrative databases was used to determine if patients admitted to the targeted services had an ED visit or urgent inpatient admission to the study hospital within 30 days.

Statistical Analysis

A logistic regression for outcomes was performed. This yielded an adjusted odds ratio with a 95% confidence interval (CI) between the intervention and control groups. Statistical significance was determined with a 2-sided α level of 0.05. In the analysis, we used Statistical Analysis Software version 9.2.

In our multivariate logistic regression model, we adjusted for confounding factors that might influence the patients’ risk of readmission or the type of Med Rec they received upon discharge. By using administrative databases, patient level demographics, and the Charlson comorbidity index, the most responsible diagnosis and disease burden were collected. Medication-related factors collected included the number of medications on discharge and the presence of predefined high-alert medications. The number of medications on the medication discharge list was determined by using the electronic database. The final adjustment model included age, gender, the number of medications on discharge, and the LACE index score (supplementary Appendix 1). The LACE index score has been validated in Ontario, Canada, populations to quantify the risk of death or unplanned readmission within 30 days of discharge.²⁴

Propensity Score Adjustment

Propensity scoring (probability of treatment assignment conditional on observed baseline characteristics) was planned a priori to account for possible factors that would impact whether a patient received the intervention or control care levels. The propensity score for receiving Med Rec was computed from a logistic model using Med Rec as the outcome. A structured iterative approach was used to refine this model to achieve covariate balance within the matched pairs. Covariate balance was measured by the standardized difference, in which an absolute standardized difference >10% represents meaningful imbalance.²⁵ From the original cohort, we attempted to match patients who had the intervention to patients from the control by means of a matching algorithm using the logit of the propensity score for receiving the intervention.²⁶

Subgroup Analysis

We also examined the impact of the intervention on high-risk patient populations such as those ≥65 years of age, with a LACE index score ≥10, on high-alert medications, and on ≥10 medications. A univariate analysis was conducted to identify patient-related risk predictors that may be independently correlated with a higher risk of hospital visits.

Baseline Characteristics

A total of 8678 patients representing 9931 unique visits met the inclusion criteria for analysis. There were 2541 unique visits (approximately 26% of visits) in the intervention group that received Gold level care and 7390 unique visits in the control group. The patients in the control group were largely patients who received the original standard of care at the institution, Silver level care (67% of the control group). Patients who received Bronze level care or less comprised 33% of the control group.

Patients in the intervention group were significantly older (average of 68 years old versus 64 years old) and on more medications. They also notably had a longer duration of stay in hospital, an increased percentage of visits with a LACE index score ≥10, and were more likely to be discharged home on a high-alert medication and with supports (Table 2).

Main Analysis

The main unadjusted analysis of GIM patients (n = 9931 visits) did not detect a difference in 30-day ED visits and readmissions between the intervention group (540 out of 2541; 21.2%) and control (1423 out of 7390; 19.3%; Table 3). By using a multivariate logistic regression model to account for age, sex, LACE index, and number of medications on discharge, the adjusted odds ratio was 1.06 (95% CI, 0.95-1.19; P = 0.33). After propensity score adjustment, the relative risk of readmission was 0.88 (16.7% vs 18.9%; 95% CI, 0.59-1.32; P = 0.54).

Secondary Analyses

In each predefined high-risk patient subgroup (age ≥65, LACE index score ≥10, number of discharge medications ≥10, and the presence of high-alert medications), analyses of our primary endpoint did not detect significant adjusted odds ratios (Table 4). In our univariate analysis, increasing number of medications, LACE index score, and male gender were independently correlated with a higher risk of hospital visits (supplementary Appendix 2).

Med Rec is widely recommended as a patient safety strategy to prevent clinically significant medication discrepancies at transitions in care.^4-9 However, Med Rec varies widely in terms of what it entails and who delivers it, with the preponderance of evidence suggesting an impact on clinically significant medication discrepancies only when interprofessional care delivered includes a central role for pharmacists.²⁷ Furthermore, Med Rec appears to impact short term readmissions only when embedded in a broader, multifaceted, bundled intervention in which pharmacists or other team members educate patients about their medications and deliver postdischarge follow-up phone calls.^10-13

As very few hospitals have the resources to sustainably deliver intensive care bundles that are represented in RCTs (characterized by Platinum and Diamond levels of care in Table 1), in our observational study, we sought to explore whether a resource-attainable, enhanced Med Rec care bundle (Gold level) had an impact on hospital utilization compared to partial Med Rec care bundles (Bronze and Silver levels). In our findings, we did not detect a significant difference on ED visits and readmissions within 30 days between enhanced and partial care bundles. In a secondary analysis of the influence of the intervention on prespecified high-risk patient subgroups, we also did not detect a difference.

As far as we are aware, our long-term, observational study is the largest to date to explore a real-life, enhanced Med Rec intervention and examine its impact on meaningful patient outcomes. We extrapolated that our intervention group received several critical attributes of a successful bundle as discussed by Mueller in a systematic review.² Our intervention included the following: (1) a systematic BPMH process on admission; (2) integrated admission-to-discharge reconciliation processes; (3) discharge delineation of medication changes since admission; (4) pharmacist involvement in reconciliation from admission to discharge; (5) an electronic platform; and (6) formal discharge reconciliation with interprofessional collaboration. Additional components in the bundle described by Mueller included the following: patient education at discharge, postdischarge communication with the patient, and communication with outpatient providers and medication management.

In our results, we did not find a difference in outcomes between the intervention and control groups. Therefore, it is possible that the enhanced bundle’s focus on interprofessional involvement in discharge reconciliation (Gold care level) has no impact on hospital utilization compared to partial care bundles (Silver and Bronze levels). Kwan et al.³ describe similar findings in their systematic review, in which they evaluated the effects of hospital-based Med Rec on unintentional discrepancies with nontrivial risks for harm to patients on 30-day postdischarge hospital visits. Kwan et al.³ concluded that larger well-designed studies are required to further evaluate this outcome, but authors of current published studies suggest that Med Rec alone probably does not reduce postdischarge hospital utilization within 30 days. Med Rec may have a more significant impact on utilization when bundled with other interventions that improve discharge coordination.³

There may be several reasons why we were unable to detect a significant difference between the intervention and control groups. One limitation is that our nonrandomized, retrospective design may have led to unmeasured confounders that impacted allocation into the intervention group versus the control group. It was notable that patients in the intervention group had an increased age, longer duration of hospital stay, more medications, and high-alert medications on discharge compared to the control group and that may have biased our results towards the null hypothesis. Although the propensity score analysis attempted to adjust for this, it also did not detect a significant difference between groups.

In addition, the existing standard of care during the study period allowed for patients in the control group to receive varying levels of Med Rec. Ideally, we would have compared the intervention to a placebo group that did not receive any Med Rec-related care elements. However, as this was a real-life observational study, the majority of patients received some Med Rec services as a part of the standard of care. As a result, 67% of patients in the control group received Silver level Med Rec with a BPMH, admission reconciliation, and prescriber-only discharge reconciliation. This may have made it more difficult to show an incremental benefit on readmissions between the intervention and control.

Also, our primary outcome of all-cause ED or hospital readmissions within 30 days may not have been sensitive enough to detect the effect of Med Rec interventions alone. Only a small proportion of readmissions within 30 days of discharge are preventable and many patient and community level factors responsible for readmissions cannot be controlled by the hospital’s actions.²⁸ Comprehensive pharmacy interventions have demonstrated decreased hospitalizations and emergency visits at 12 months; however, the largest impact was seen on the more specific outcome of medication-related hospitalizations (80% reduction).²⁹ Lastly, another limitation was that we were unable to capture hospital visits to other centres. However, in our region, almost 75% of readmissions are to the same site as the initial hospitalization.³⁰

Overall, our findings in this study and novel characterization of Med Rec services are relevant to many hospital sites that are striving to implement integrated Med Rec with limited healthcare resources. Although interprofessional Med Rec likely reduces clinically significant medication discrepancies, enhanced interprofessional Med Rec on discharge (Gold Med Rec) alone may not be enough to impact hospital utilization compared to partial Med Rec services (Silver and Bronze Med Rec). Further research into practical, targeted Med Rec bundles on more specific outcomes (such as preventable postdischarge adverse events, “avoidable” hospital readmissions, and medication-related readmissions) may detect a significant benefit.

A long-term observational evaluation of interprofessional Med Rec did not detect a difference in 30-day postdischarge patient hospital visits between patients who received enhanced versus partial Med Rec patient care bundles. Researchers of future prospective studies could focus on evaluating high-risk populations or specific elements of Med Rec services on avoidable medication-related hospital admissions and postdischarge adverse drug events.

Acknowledgments

The authors thank Nita Dhir, MBA.

Presented as a poster and oral presentation at the 2012 American College of Clinical Pharmacy Annual Meeting, Hollywood, Florida, October 21-24, 2012, and as an encore poster presentation at the Canadian Society of Hospital Pharmacists Professional Practice Conference, Toronto, Canada, Feb 3, 2013.

Disclosure

The authors declare no conflicts of interest related to the manuscript submitted. All monies used for the research came from the University Health Network Department of Pharmacy Budget, including the pharmacy residency program.

The lack of mentorship in hospital medicine has been previously documented,^1-3 but there is scant literature about solutions to the problem.⁴ In other disciplines, data suggest that the guidance of a mentor has a positive influence on academic productivity and professional satisfaction. Mentored faculty at all levels in their careers are more successful at producing peer-reviewed publications, procuring grant support, and maintaining confidence in their career trajectory.^5,6 In one study, mentored faculty physicians reported receiving career advice, improving communication skills, and growing their professional networks.⁷ Another study found that the primary benefits of physician mentoring were improved professional and personal well-being.⁸ Whether early-career hospitalists would have similarly favorable responses to a structured mentorship program is unknown. We report our experience in implementing a pilot mentorship program to support junior hospitalists at a large academic medical center.

The mentorship program was implemented from October 2015 to June 2016 in the Hospital Medicine Unit (HMU) of the Massachusetts General Hospital (MGH), a teaching affiliate of Harvard Medical School.  

Program Goals, Design, and Development

In collaboration with the MGH Center for Faculty Development (CFD), we offered 3 training sessions over a period of 9 months, for both mentors and mentees, on how to maximize mentorship success. Funding was provided by the MGH Division of General Internal Medicine and CFD. There were no external funding sources. This study was exempt by the Partners Institutional Review Board.

Participants

Mentees had to be hired at >0.5 full-time equivalent and have 3 years or fewer of hospitalist experience. Mentors were physicians with at least 7 years of hospital medicine experience. All HMU faculty who met the criteria were invited to participate on a voluntary basis.

Mentor–Mentee Matching

Mentors were paired with 1 or 2 mentees. Participant information such as history of mentorship and areas of interest for mentorship was collected. Two authors matched mentors and mentees to maximize similarities in these areas. Four mentors were paired with 2 mentees each, and 12 mentors were paired with 1 mentee each.

Mentorship Training Sessions

The program provided 3 mentorship-training lunch sessions for both mentees and mentors during the 9-month program. To enrich attendance, mentees were provided coverage for their clinical duties. The initial training session provided an opportunity to meet, articulate expectations and challenges, and develop action plans with individualized goals for the mentoring relationship. The second training session occurred at the midpoint. Pairs considered their mentorship status, evaluated their progress, and discussed strategies for optimizing their experience. At the final training session, participants reflected on their mentoring relationships, identified their extended network of mentoring support, and set expectations regarding whether the mentoring relationship would continue.

Mentorship Meetings

In addition to the training sessions, mentee–mentor pairs were expected to meet a minimum of 2 times during the formal mentorship program. CFD experts performed participant outreach via e-mail to assess progress. Mentees were given dining facility gift cards to support meetings with their mentors.

Program Evaluation

Confidential, anonymous semiquantitative surveys were used to assess the efficacy of this prospective, nonrandomized intervention study. An online survey platform was utilized to assess the frequency of mentorship meetings, satisfaction and challenges with mentorship, perception of support, degree of career satisfaction, and perceived need for and value of mentoring. Data were collected from both mentors and mentees prior to the first training session and after completion of the program. To preserve anonymity and encourage responses, surveys did not contain identifying information. As such, individual respondent data were not directly matched pre- and postintervention.

Statistical Analysis

Individual satisfaction scores (ranked 1 to 5, with 5 being very satisfied) were assigned to each response within each of the 18 domains. A composite satisfaction score was then calculated for each respondent both pre- and postintervention. An unpaired Student’s t test was first used to assess change in overall satisfaction scores pre- and postintervention. As there was a statistically significant change in this aggregate score, Wilcoxon rank sum testing was used to compare ordinal scores pre- and postintervention within each of the 18 domains. The proportion of respondents ranking their satisfaction in each domain as satisfied or very satisfied was also compared pre- and postmentorship. This approach of modified “top-box” reporting is similar to prior major national survey-based experiences.⁹

Program Participation and Response Rate

Of the 25 eligible mentees, 16 (64%) participated in the mentorship program. Of the 20 eligible mentors, 12 (60%) participated. One participating mentee and 1 mentor left the institution during the intervention period. Fourteen mentees (response rate: 88%) and 9 mentors (response rate: 75%) completed the preintervention survey. Ten mentees (response rate: 63%) and 8 mentors (response rate: 67%) completed the postintervention survey.

Mentor Characteristics

Ninety-two percent of mentors were clinician educators. The mentors had 21 peer-reviewed publications during the year of the study, 25% of the mentors had external research funding, 75% had internal funding for projects or administrative roles, and 75% were above the rank of instructor. Most mentors were married with children.

Mentorship Meetings and the Mentorship Network

All participants attended at least 2 of the 3 trainings. For the mentees who completed the postintervention survey, 9 (90%) met with their mentors 3 or more additional times, and 8 (80%) were connected by their mentor to at least 1 additional faculty mentor.

Perceptions and Overall Satisfaction with Mentorship

Prior to starting the mentoring relationship, 86% of mentees and 78% of mentors anticipated that differing career goals would be a challenge to a successful mentor–mentee relationship. At the end of the program, only 30% of mentees and 38% of mentors felt that such differences were a challenge. Ninety percent of mentees and 88% of mentors were satisfied or very satisfied with their mentorship match. Forty-three percent of mentees felt supported by the HMU prior to the mentorship program, while 90% felt supported after the program. All the mentees agreed that future HMU faculty should participate in a similar program.

Impact of Mentorship on Critical Domains

At baseline, the following domains were most commonly rated as very important by mentees: career planning, professional connectedness, producing scholarly work, finding an area of expertise, balancing work and family life, and job satisfaction (Figure 1). There was a significant improvement in composite satisfaction scores after completion of the mentorship program (54.5 ± 6.2 vs 65 ± 14.9, P = 0.02). The influence of the mentorship program on all domains is shown in Figure 2. After completion of the mentorship program, there was a significant improvement in mentee satisfaction in the following domains: career planning, professional connectedness, self-reflection, research skills, and mentoring skills.

Our pilot structured mentorship program for junior hospitalists was feasible and led to improved satisfaction in select key career domains. Other mentoring or faculty coaching programs have been studied in several fields of medicine^10-12; however, to our knowledge, there have not been published data studying a structured mentorship program for junior faculty in hospital medicine. Our intervention prioritized not only optimizing mentorship matches but also formalizing training sessions led by content experts.

After experiencing a structured mentoring relationship, most mentees felt a greater sense of support, were satisfied with their mentoring experiences, were connected to additional faculty, and had significant improvement in satisfaction in key career domains. Satisfaction with other self-identified “very important” domains, including scholarly activity, finding an area of expertise, job satisfaction, and work and family-life balance, did not significantly improve by the end of the program.

Perceived challenges to mentoring did not persist to the same degree with the implementation of a structured program. This highlights the importance of building mentorship skill sets (such as mentoring across differences and goal setting) through expert-led training sessions and perhaps also the importance of matching based on career goals.

This study has several limitations, including a small sample size, modest response rate, and short study period. Additionally, the assessment relied on self-reporting. This study was performed at a large academic institution, and mentors were almost all clinician educators with some research experience, which limits generalizability. Surveys were entirely anonymized and did not contain identifying information, so individual respondent data could not be matched pre- and postintervention. Given that this was an observational study without a control group, mentorship can only be said to be associated with, and not necessarily causally linked to, the observed improvements. Other cointerventions occurring during the same time frame that may have impacted satisfaction include annual career conferences, changing leadership, and other faculty development seminars. Finally, given the study design and the reliance on survey-based data, the net improvement in satisfaction scores may be influenced by the Hawthorne effect.

Effective and sustainable career development requires mentorship. In our pilot study, implementing a personalized and structured mentorship program for junior hospitalists focusing on building mentor–mentee relationships was feasible and was met with satisfaction. Indeed, the proportion of junior hospitalists who felt supported more than doubled, which could potentially improve academic productivity, recruitment, and retention. Larger prospective studies with a longer follow-up are needed to assess the impact of a structured mentorship program on hospitalist careers.

Acknowledgments

The authors would like to thank each of the participants in the HMU Mentorship Program and the MGH CFD and Division of General Internal Medicine for supporting this effort.

Disclosure 

Funding was provided by the MGH DGIM and CFD. Dr. Regina O’Neill reports the following relevant financial relationship: Massachusetts General Hospital Center for Faculty Development (consultant). All other authors report no other financial or other conflicts of interest to disclose.

The lack of mentorship in hospital medicine has been previously documented,^1-3 but there is scant literature about solutions to the problem.⁴ In other disciplines, data suggest that the guidance of a mentor has a positive influence on academic productivity and professional satisfaction. Mentored faculty at all levels in their careers are more successful at producing peer-reviewed publications, procuring grant support, and maintaining confidence in their career trajectory.^5,6 In one study, mentored faculty physicians reported receiving career advice, improving communication skills, and growing their professional networks.⁷ Another study found that the primary benefits of physician mentoring were improved professional and personal well-being.⁸ Whether early-career hospitalists would have similarly favorable responses to a structured mentorship program is unknown. We report our experience in implementing a pilot mentorship program to support junior hospitalists at a large academic medical center.

The mentorship program was implemented from October 2015 to June 2016 in the Hospital Medicine Unit (HMU) of the Massachusetts General Hospital (MGH), a teaching affiliate of Harvard Medical School.  

Program Goals, Design, and Development

In collaboration with the MGH Center for Faculty Development (CFD), we offered 3 training sessions over a period of 9 months, for both mentors and mentees, on how to maximize mentorship success. Funding was provided by the MGH Division of General Internal Medicine and CFD. There were no external funding sources. This study was exempt by the Partners Institutional Review Board.

Participants

Mentees had to be hired at >0.5 full-time equivalent and have 3 years or fewer of hospitalist experience. Mentors were physicians with at least 7 years of hospital medicine experience. All HMU faculty who met the criteria were invited to participate on a voluntary basis.

Mentor–Mentee Matching

Mentors were paired with 1 or 2 mentees. Participant information such as history of mentorship and areas of interest for mentorship was collected. Two authors matched mentors and mentees to maximize similarities in these areas. Four mentors were paired with 2 mentees each, and 12 mentors were paired with 1 mentee each.

Mentorship Training Sessions

The program provided 3 mentorship-training lunch sessions for both mentees and mentors during the 9-month program. To enrich attendance, mentees were provided coverage for their clinical duties. The initial training session provided an opportunity to meet, articulate expectations and challenges, and develop action plans with individualized goals for the mentoring relationship. The second training session occurred at the midpoint. Pairs considered their mentorship status, evaluated their progress, and discussed strategies for optimizing their experience. At the final training session, participants reflected on their mentoring relationships, identified their extended network of mentoring support, and set expectations regarding whether the mentoring relationship would continue.

Mentorship Meetings

In addition to the training sessions, mentee–mentor pairs were expected to meet a minimum of 2 times during the formal mentorship program. CFD experts performed participant outreach via e-mail to assess progress. Mentees were given dining facility gift cards to support meetings with their mentors.

Program Evaluation

Confidential, anonymous semiquantitative surveys were used to assess the efficacy of this prospective, nonrandomized intervention study. An online survey platform was utilized to assess the frequency of mentorship meetings, satisfaction and challenges with mentorship, perception of support, degree of career satisfaction, and perceived need for and value of mentoring. Data were collected from both mentors and mentees prior to the first training session and after completion of the program. To preserve anonymity and encourage responses, surveys did not contain identifying information. As such, individual respondent data were not directly matched pre- and postintervention.

Statistical Analysis

Individual satisfaction scores (ranked 1 to 5, with 5 being very satisfied) were assigned to each response within each of the 18 domains. A composite satisfaction score was then calculated for each respondent both pre- and postintervention. An unpaired Student’s t test was first used to assess change in overall satisfaction scores pre- and postintervention. As there was a statistically significant change in this aggregate score, Wilcoxon rank sum testing was used to compare ordinal scores pre- and postintervention within each of the 18 domains. The proportion of respondents ranking their satisfaction in each domain as satisfied or very satisfied was also compared pre- and postmentorship. This approach of modified “top-box” reporting is similar to prior major national survey-based experiences.⁹

Program Participation and Response Rate

Of the 25 eligible mentees, 16 (64%) participated in the mentorship program. Of the 20 eligible mentors, 12 (60%) participated. One participating mentee and 1 mentor left the institution during the intervention period. Fourteen mentees (response rate: 88%) and 9 mentors (response rate: 75%) completed the preintervention survey. Ten mentees (response rate: 63%) and 8 mentors (response rate: 67%) completed the postintervention survey.

Mentor Characteristics

Ninety-two percent of mentors were clinician educators. The mentors had 21 peer-reviewed publications during the year of the study, 25% of the mentors had external research funding, 75% had internal funding for projects or administrative roles, and 75% were above the rank of instructor. Most mentors were married with children.

Mentorship Meetings and the Mentorship Network

All participants attended at least 2 of the 3 trainings. For the mentees who completed the postintervention survey, 9 (90%) met with their mentors 3 or more additional times, and 8 (80%) were connected by their mentor to at least 1 additional faculty mentor.

Perceptions and Overall Satisfaction with Mentorship

Prior to starting the mentoring relationship, 86% of mentees and 78% of mentors anticipated that differing career goals would be a challenge to a successful mentor–mentee relationship. At the end of the program, only 30% of mentees and 38% of mentors felt that such differences were a challenge. Ninety percent of mentees and 88% of mentors were satisfied or very satisfied with their mentorship match. Forty-three percent of mentees felt supported by the HMU prior to the mentorship program, while 90% felt supported after the program. All the mentees agreed that future HMU faculty should participate in a similar program.

Impact of Mentorship on Critical Domains

At baseline, the following domains were most commonly rated as very important by mentees: career planning, professional connectedness, producing scholarly work, finding an area of expertise, balancing work and family life, and job satisfaction (Figure 1). There was a significant improvement in composite satisfaction scores after completion of the mentorship program (54.5 ± 6.2 vs 65 ± 14.9, P = 0.02). The influence of the mentorship program on all domains is shown in Figure 2. After completion of the mentorship program, there was a significant improvement in mentee satisfaction in the following domains: career planning, professional connectedness, self-reflection, research skills, and mentoring skills.

Our pilot structured mentorship program for junior hospitalists was feasible and led to improved satisfaction in select key career domains. Other mentoring or faculty coaching programs have been studied in several fields of medicine^10-12; however, to our knowledge, there have not been published data studying a structured mentorship program for junior faculty in hospital medicine. Our intervention prioritized not only optimizing mentorship matches but also formalizing training sessions led by content experts.

After experiencing a structured mentoring relationship, most mentees felt a greater sense of support, were satisfied with their mentoring experiences, were connected to additional faculty, and had significant improvement in satisfaction in key career domains. Satisfaction with other self-identified “very important” domains, including scholarly activity, finding an area of expertise, job satisfaction, and work and family-life balance, did not significantly improve by the end of the program.

Perceived challenges to mentoring did not persist to the same degree with the implementation of a structured program. This highlights the importance of building mentorship skill sets (such as mentoring across differences and goal setting) through expert-led training sessions and perhaps also the importance of matching based on career goals.

This study has several limitations, including a small sample size, modest response rate, and short study period. Additionally, the assessment relied on self-reporting. This study was performed at a large academic institution, and mentors were almost all clinician educators with some research experience, which limits generalizability. Surveys were entirely anonymized and did not contain identifying information, so individual respondent data could not be matched pre- and postintervention. Given that this was an observational study without a control group, mentorship can only be said to be associated with, and not necessarily causally linked to, the observed improvements. Other cointerventions occurring during the same time frame that may have impacted satisfaction include annual career conferences, changing leadership, and other faculty development seminars. Finally, given the study design and the reliance on survey-based data, the net improvement in satisfaction scores may be influenced by the Hawthorne effect.

Effective and sustainable career development requires mentorship. In our pilot study, implementing a personalized and structured mentorship program for junior hospitalists focusing on building mentor–mentee relationships was feasible and was met with satisfaction. Indeed, the proportion of junior hospitalists who felt supported more than doubled, which could potentially improve academic productivity, recruitment, and retention. Larger prospective studies with a longer follow-up are needed to assess the impact of a structured mentorship program on hospitalist careers.

Acknowledgments

The authors would like to thank each of the participants in the HMU Mentorship Program and the MGH CFD and Division of General Internal Medicine for supporting this effort.

Disclosure 

Funding was provided by the MGH DGIM and CFD. Dr. Regina O’Neill reports the following relevant financial relationship: Massachusetts General Hospital Center for Faculty Development (consultant). All other authors report no other financial or other conflicts of interest to disclose.

The lack of mentorship in hospital medicine has been previously documented,^1-3 but there is scant literature about solutions to the problem.⁴ In other disciplines, data suggest that the guidance of a mentor has a positive influence on academic productivity and professional satisfaction. Mentored faculty at all levels in their careers are more successful at producing peer-reviewed publications, procuring grant support, and maintaining confidence in their career trajectory.^5,6 In one study, mentored faculty physicians reported receiving career advice, improving communication skills, and growing their professional networks.⁷ Another study found that the primary benefits of physician mentoring were improved professional and personal well-being.⁸ Whether early-career hospitalists would have similarly favorable responses to a structured mentorship program is unknown. We report our experience in implementing a pilot mentorship program to support junior hospitalists at a large academic medical center.

The mentorship program was implemented from October 2015 to June 2016 in the Hospital Medicine Unit (HMU) of the Massachusetts General Hospital (MGH), a teaching affiliate of Harvard Medical School.  

Program Goals, Design, and Development

In collaboration with the MGH Center for Faculty Development (CFD), we offered 3 training sessions over a period of 9 months, for both mentors and mentees, on how to maximize mentorship success. Funding was provided by the MGH Division of General Internal Medicine and CFD. There were no external funding sources. This study was exempt by the Partners Institutional Review Board.

Participants

Mentees had to be hired at >0.5 full-time equivalent and have 3 years or fewer of hospitalist experience. Mentors were physicians with at least 7 years of hospital medicine experience. All HMU faculty who met the criteria were invited to participate on a voluntary basis.

Mentor–Mentee Matching

Mentors were paired with 1 or 2 mentees. Participant information such as history of mentorship and areas of interest for mentorship was collected. Two authors matched mentors and mentees to maximize similarities in these areas. Four mentors were paired with 2 mentees each, and 12 mentors were paired with 1 mentee each.

Mentorship Training Sessions

The program provided 3 mentorship-training lunch sessions for both mentees and mentors during the 9-month program. To enrich attendance, mentees were provided coverage for their clinical duties. The initial training session provided an opportunity to meet, articulate expectations and challenges, and develop action plans with individualized goals for the mentoring relationship. The second training session occurred at the midpoint. Pairs considered their mentorship status, evaluated their progress, and discussed strategies for optimizing their experience. At the final training session, participants reflected on their mentoring relationships, identified their extended network of mentoring support, and set expectations regarding whether the mentoring relationship would continue.

Mentorship Meetings

In addition to the training sessions, mentee–mentor pairs were expected to meet a minimum of 2 times during the formal mentorship program. CFD experts performed participant outreach via e-mail to assess progress. Mentees were given dining facility gift cards to support meetings with their mentors.

Program Evaluation

Confidential, anonymous semiquantitative surveys were used to assess the efficacy of this prospective, nonrandomized intervention study. An online survey platform was utilized to assess the frequency of mentorship meetings, satisfaction and challenges with mentorship, perception of support, degree of career satisfaction, and perceived need for and value of mentoring. Data were collected from both mentors and mentees prior to the first training session and after completion of the program. To preserve anonymity and encourage responses, surveys did not contain identifying information. As such, individual respondent data were not directly matched pre- and postintervention.

Statistical Analysis

Individual satisfaction scores (ranked 1 to 5, with 5 being very satisfied) were assigned to each response within each of the 18 domains. A composite satisfaction score was then calculated for each respondent both pre- and postintervention. An unpaired Student’s t test was first used to assess change in overall satisfaction scores pre- and postintervention. As there was a statistically significant change in this aggregate score, Wilcoxon rank sum testing was used to compare ordinal scores pre- and postintervention within each of the 18 domains. The proportion of respondents ranking their satisfaction in each domain as satisfied or very satisfied was also compared pre- and postmentorship. This approach of modified “top-box” reporting is similar to prior major national survey-based experiences.⁹

Program Participation and Response Rate

Of the 25 eligible mentees, 16 (64%) participated in the mentorship program. Of the 20 eligible mentors, 12 (60%) participated. One participating mentee and 1 mentor left the institution during the intervention period. Fourteen mentees (response rate: 88%) and 9 mentors (response rate: 75%) completed the preintervention survey. Ten mentees (response rate: 63%) and 8 mentors (response rate: 67%) completed the postintervention survey.

Mentor Characteristics

Ninety-two percent of mentors were clinician educators. The mentors had 21 peer-reviewed publications during the year of the study, 25% of the mentors had external research funding, 75% had internal funding for projects or administrative roles, and 75% were above the rank of instructor. Most mentors were married with children.

Mentorship Meetings and the Mentorship Network

All participants attended at least 2 of the 3 trainings. For the mentees who completed the postintervention survey, 9 (90%) met with their mentors 3 or more additional times, and 8 (80%) were connected by their mentor to at least 1 additional faculty mentor.

Perceptions and Overall Satisfaction with Mentorship

Prior to starting the mentoring relationship, 86% of mentees and 78% of mentors anticipated that differing career goals would be a challenge to a successful mentor–mentee relationship. At the end of the program, only 30% of mentees and 38% of mentors felt that such differences were a challenge. Ninety percent of mentees and 88% of mentors were satisfied or very satisfied with their mentorship match. Forty-three percent of mentees felt supported by the HMU prior to the mentorship program, while 90% felt supported after the program. All the mentees agreed that future HMU faculty should participate in a similar program.

Impact of Mentorship on Critical Domains

At baseline, the following domains were most commonly rated as very important by mentees: career planning, professional connectedness, producing scholarly work, finding an area of expertise, balancing work and family life, and job satisfaction (Figure 1). There was a significant improvement in composite satisfaction scores after completion of the mentorship program (54.5 ± 6.2 vs 65 ± 14.9, P = 0.02). The influence of the mentorship program on all domains is shown in Figure 2. After completion of the mentorship program, there was a significant improvement in mentee satisfaction in the following domains: career planning, professional connectedness, self-reflection, research skills, and mentoring skills.

Our pilot structured mentorship program for junior hospitalists was feasible and led to improved satisfaction in select key career domains. Other mentoring or faculty coaching programs have been studied in several fields of medicine^10-12; however, to our knowledge, there have not been published data studying a structured mentorship program for junior faculty in hospital medicine. Our intervention prioritized not only optimizing mentorship matches but also formalizing training sessions led by content experts.

After experiencing a structured mentoring relationship, most mentees felt a greater sense of support, were satisfied with their mentoring experiences, were connected to additional faculty, and had significant improvement in satisfaction in key career domains. Satisfaction with other self-identified “very important” domains, including scholarly activity, finding an area of expertise, job satisfaction, and work and family-life balance, did not significantly improve by the end of the program.

Perceived challenges to mentoring did not persist to the same degree with the implementation of a structured program. This highlights the importance of building mentorship skill sets (such as mentoring across differences and goal setting) through expert-led training sessions and perhaps also the importance of matching based on career goals.

This study has several limitations, including a small sample size, modest response rate, and short study period. Additionally, the assessment relied on self-reporting. This study was performed at a large academic institution, and mentors were almost all clinician educators with some research experience, which limits generalizability. Surveys were entirely anonymized and did not contain identifying information, so individual respondent data could not be matched pre- and postintervention. Given that this was an observational study without a control group, mentorship can only be said to be associated with, and not necessarily causally linked to, the observed improvements. Other cointerventions occurring during the same time frame that may have impacted satisfaction include annual career conferences, changing leadership, and other faculty development seminars. Finally, given the study design and the reliance on survey-based data, the net improvement in satisfaction scores may be influenced by the Hawthorne effect.

Effective and sustainable career development requires mentorship. In our pilot study, implementing a personalized and structured mentorship program for junior hospitalists focusing on building mentor–mentee relationships was feasible and was met with satisfaction. Indeed, the proportion of junior hospitalists who felt supported more than doubled, which could potentially improve academic productivity, recruitment, and retention. Larger prospective studies with a longer follow-up are needed to assess the impact of a structured mentorship program on hospitalist careers.

Acknowledgments

The authors would like to thank each of the participants in the HMU Mentorship Program and the MGH CFD and Division of General Internal Medicine for supporting this effort.

Disclosure 

Funding was provided by the MGH DGIM and CFD. Dr. Regina O’Neill reports the following relevant financial relationship: Massachusetts General Hospital Center for Faculty Development (consultant). All other authors report no other financial or other conflicts of interest to disclose.

Public reporting of readmission rates on the Nursing Home Compare website is mandated to begin on October 1, 2017, with skilled nursing facilities (SNFs) set to receive a Medicare bonus or penalty beginning a year later.¹ The Centers for Medicare & Medicaid Services (CMS) began public reporting of hospitals’ 30-day readmission rates for selected conditions in 2009, and the Patient Protection and Affordable Care Act of 2010 mandated financial penalties for excess readmissions through the Hospital Readmission Reduction Program.² In response, most hospitals have focused on patients who return home following discharge. Innovative interventions have proven successful, such as the Transitional Care model developed by Naylor and Coleman’s Care Transitions Intervention.^3-5 Approximately 20% of Medicare beneficiaries are discharged from hospitals to SNFs, and these patients have higher readmission rates than those discharged home. CMS reported that in 2010, 23.3% of those with an SNF stay were readmitted within 30 days, compared with 18.8% for those with other discharge dispositions.⁶

Some work has been undertaken in this arena. In 2012, the Center for Medicare and Medicaid Innovation (CMMI) and the Medicare-Medicaid Coordination Office jointly launched the Initiative to Reduce Avoidable Hospitalizations among Nursing Facility Residents.⁷ This partnership established 7 Enhanced Care and Coordination Provider organizations and was designed to improve care by reducing hospitalizations among long-stay, dual-eligible nursing facility residents at 143 nursing homes in 7 states.⁸ At the time of the most recent project report, there were mixed results regarding program effects on hospitalizations and spending, with 2 states showing strongly positive patterns, 3 states with reductions that were consistent though not statistically strong, and mixed results in the remaining states. Quality measures did not show any pattern suggesting a program effect.⁹ Interventions to Reduce Acute Care Transfers (INTERACT) II was a 6-month, collaborative, quality-improvement project implemented in 2009 at 30 nursing homes in 3 states.¹⁰ The project evaluation found a statistically significant, 17% decrease in self-reported hospital admissions among the 25 SNFs that completed the intervention, compared with the same 6 months in the prior year. The Cleveland Clinic recently reported favorable results implementing its Connected Care model, which relied on staff physicians and advanced practice professionals to visit patients 4 to 5 times per week and be on call 24/7 at 7 intervention SNFs.¹¹ Through this intervention, it successfully reduced its 30-day hospital readmission rate from SNFs from 28.1% to 21.7% (P < 0.001), and the authors posed the question as to whether its model and results were reproducible in other healthcare systems.

Herein, we report on the results of a collaborative initiative named the Enhanced Care Program (ECP), which offers the services of clinical providers and administrative staff to assist with the care of patients at 8 partner SNFs. The 3 components of ECP (described below) were specifically designed to address commonly recognized gaps and opportunities in routine SNF care. In contrast to the Cleveland Clinic’s Connected Care model (which involved hospital-employed physicians serving as the SNF attendings and excluded patients followed by their own physicians), ECP was designed to integrate into a pluralistic, community model whereby independent physicians continued to follow their own patients at the SNFs. The Connected Care analysis compared participating versus nonparticipating SNFs; both the Connected Care model and the INTERACT II evaluation relied on pre–post comparisons; the CMMI evaluation used a difference-in-differences model to compare the outcomes of the program SNFs with those of a matched comparison group of nonparticipating SNFs. The evaluation of ECP differs from these other initiatives, using a concurrent comparison group of patients discharged to the same SNFs but who were not enrolled in ECP.

Setting

Cedars-Sinai Medical Center (CSMC) is an 850-bed, acute care facility located in an urban area of Los Angeles. Eight SNFs, ranging in size from 49 to 150 beds and located between 0.6 and 2.2 miles from CSMC, were invited to partner with the ECP. The physician community encompasses more than 2000 physicians on the medical staff, including private practitioners, nonteaching hospitalists, full-time faculty hospitalists, and faculty specialists.

Study Design and Patients

This was an observational, retrospective cohort analysis of 30-day same-hospital readmissions among 3951 patients discharged from CSMC to 8 SNFs between January 1, 2014, and June 30, 2015. A total of 2394 patients were enrolled in the ECP, and 1557 patients were not enrolled.

ECP Enrollment Protocol

Every patient discharged from CSMC to 1 of the 8 partner SNFs was eligible to participate in the program. To respect the autonomy of the SNF attending physicians and to facilitate a collaborative relationship, the decision to enroll a patient in the ECP rested with the SNF attending physician. The ECP team maintained a database that tracked whether each SNF attending physician (1) opted to automatically enroll all his or her patients in the ECP, (2) opted to enroll patients on a case-by-case basis (in which case an ECP nurse practitioner [NP] contacted the attending physician for each eligible patient), or (3) opted out of the ECP completely. When a new SNF attending physician was encountered, the ECP medical director called the physician to explain the ECP and offer enrollment of his or her patient(s). Ultimately, patients (or their decision-makers) retained the right to opt in or out of the ECP at any time, regardless of the decision of the attending physicians.

Program Description

Patients enrolled in the ECP experienced the standard care provided by the SNF staff and attending physicians plus a clinical care program delivered by 9 full-time NPs, 1 full-time pharmacist, 1 pharmacy technician, 1 full-time nurse educator, a program administrator, and a medical director.

The program included the following 3 major components:

1. Direct patient care and 24/7 NP availability: Program enrollment began with an on-site, bedside evaluation by an ECP NP at the SNF within 24 hours of arrival and continued with weekly NP rounding (or more frequently, if clinically indicated) on the patient. Each encounter included a review of the medical record; a dialogue with the patient’s SNF attending physician to formulate treatment plans and place orders; discussions with nurses, family members, and other caregivers; and documentation in the medical record. The ECP team was on-site at the SNFs 7 days a week and on call 24/7 to address questions and concerns. Patients remained enrolled in the ECP from SNF admission to discharge even if their stay extended beyond 30 days.

2. Medication reconciliation: The ECP pharmacy team completed a review of a patient’s SNF medication administration record (MAR) within 72 hours of SNF admission. This process involved the pharmacy technician gathering medication lists from the SNFs and CSMC and providing this information to the pharmacist for a medication reconciliation and clinical evaluation. Discrepancies and pharmacist recommendations were communicated to the ECP NPs, and all identified issues were resolved.

3. Educational in-services: Building upon the INTERACT II model, the ECP team identified high-yield, clinically relevant topics, which the ECP nurse educator turned into monthly educational sessions for the SNF nursing staff at each of the participating SNFs.¹⁰

Primary Outcome Measure

An inpatient readmission to CSMC within 30 days of the hospital discharge date was counted as a readmission, whether the patient returned directly from an SNF or was readmitted from home after an SNF discharge.

Data

ECP patients were identified using a log maintained by the ECP program manager. Non-ECP patients discharged to the same SNFs during the study period were identified from CSMC’s electronic registry of SNF discharges. Covariates known to be associated with increased risk of 30-day readmission were obtained from CSMC’s electronic data warehouse, including demographic information, length of stay (LOS) of index hospitalization, and payer.¹² Eleven clinical service lines represented patients’ clinical conditions based on Medicare-Severity Diagnosis-Related groupings. The discharge severity of illness score was calculated using 3M All Patients Refined Diagnosis Related Group software, version 33.¹³

Analysis

Characteristics of the ECP and non-ECP patients were compared using the χ² test. A multivariable logistic regression model with fixed effects for SNF was created to determine the program’s impact on 30-day hospital readmission, adjusting for patient characteristics. The Pearson χ² goodness-of-fit test and the link test for model specification were used to evaluate model specification. The sensitivity of the results to differences in patient characteristics was assessed in 2 ways. First, the ECP and non-ECP populations were stratified based on race and/or ethnicity and payer, and the multivariable regression model was run within the strata associated with the highest readmission rates. Second, a propensity analysis using inverse probability of treatment weighting (IPTW) was performed to control for group differences. Results of all comparisons were considered statistically significant when P < 0.05. Stata version 13 was used to perform the main analyses.¹⁴ The propensity analysis was conducted using R version 3.2.3. The CSMC Institutional Review Board (IRB) determined that this study qualified as a quality-improvement activity and did not require IRB approval or exemption.

The average unadjusted 30-day readmission rate for ECP patients over the 18-month study period was 17.2%, compared to 23.0% for patients not enrolled in ECP (P < 0.001) (Figure 1). After adjusting for patient characteristics, ECP patients had 29% lower odds (95% confidence interval [CI], 0.60-0.85) of being readmitted to the medical center within 30 days than non-ECP patients at the same SNFs. The characteristics of the ECP and comparison patient cohorts are shown in Table 1. There were significant differences in sociodemographic characteristics: The ECP group had a higher proportion of non-Hispanic white patients, while the comparison group had a higher proportion of patients who were African American or Hispanic. ECP patients were more likely to prefer speaking English, while Russian, Farsi, and Spanish were preferred more frequently in the comparison group. There were also differences in payer mix, with the ECP group including proportionately more Medicare fee-for-service (52.9% vs 35.0%, P < 0.001), while the comparison group had a correspondingly larger proportion of dual-eligible (Medicare and Medicaid) patients (55.0% vs 35.1%, P < 0.001).

Sensitivity Analyses

The results were robust when tested within strata of the study population, including analyses limited to dual-eligible patients, African American patients, patients admitted to all except the highest volume facility, and patients admitted to any service line other than orthopedic surgery. Similar results were obtained when the study population was restricted to patients living within the medical center’s primary service area and to patients living in zip codes in which the proportion of adults living in households with income below 100% of the poverty level was 15% or greater (see Supplementary Material for results).

The effect of the program on readmission was also consistent when the full logistic regression model was run with IPTW using the propensity score. The evaluation of standardized cluster differences between the ECP and non-ECP groups before and after IPTW showed that the differences were reduced to <10% for being African American; speaking Russian or Farsi; having dual-eligible insurance coverage; having orthopedic surgery; being discharged from the clinical service lines of gastroenterology, pulmonary, other surgery, and other services; and having an index hospital LOS of 4 to 5 days or 10 or more days (results are provided in the Supplementary Material).

Hospitals continue to experience significant pressure to manage LOS, and SNFs and hospitals are being held accountable for readmission rates. The setting of this study is representative of many large, urban hospitals in the United States whose communities include a heterogeneous mix of hospitalists, primary care physicians who follow their patients in SNFs, and independent SNFs.¹⁵ The current regulations have not kept up with the increasing acuity and complexity of SNF patients. Specifically, Medicare guidelines allow the SNF attending physician up to 72 hours to complete a history and physical (or 7 days if he or she was the hospital attending physician for the index hospitalization) and only require monthly follow-up visits. It is the opinion of the ECP designers that these relatively lax requirements present unnecessary risk for vulnerable patients. While the INTERACT II model was focused largely on educational initiatives (with an advanced practice nurse available in a consultative role, as needed), the central tenet of ECP was similar to the Connected Care model in that the focus was on adding an extra layer of direct clinical support. Protocols that provided timely initial assessments by an NP (within 24 hours), weekly NP rounding (at a minimum), and 24/7 on-call availability all contributed to helping patients stay on track. Although the ECP had patients visited less frequently than the Connected Care model, and the Cleveland Clinic started with a higher baseline 30-day readmission rate from SNFs, similar overall reductions in 30-day readmissions were observed. The key point from both initiatives is that an increase in clinical touchpoints and ease of access to clinicians generates myriad opportunities to identify and address small issues before they become clinical emergencies requiring hospital transfers and readmissions.

Correcting medication discrepancies between hospital discharge summaries and SNF admission orders through a systematic medication reconciliation using a clinical pharmacist has previously been shown to improve outcomes.^16-18 The ECP pharmacy technician and ECP clinical pharmacist discovered and corrected errors on a daily basis that ranged from incidental to potentially life-threatening. If the SNF staff does not provide the patient’s MAR within 48 hours of arrival, the pharmacy technician contacts the facility to obtain the information. As a result, all patients enrolled in the ECP during the study period received this intervention (unless they were rehospitalized or left the SNF before the process was completed), and 54% of ECP patients required some form of intervention after medication reconciliation was completed (data not shown).

This type of program requires hospital leadership and SNF administrators to be fully committed to developing strong working relationships, and in fact, there is evidence that SNF baseline readmission rates have a greater influence on patients’ risk of rehospitalization than the discharging hospital itself.^19-21 Monthly educational in-services are delivered at the partner SNFs to enhance SNF nursing staff knowledge and clinical acumen. High-impact topics identified by the ECP team include the following: fall prevention, hand hygiene, venous thromboembolism, cardiovascular health, how to report change in condition, and advanced care planning, among others. While no formal pre–post assessments of the SNF nurses’ knowledge were conducted, a log of in-services was kept, subjective feedback was collected for performance improvement purposes, and continuing educational units were provided to the SNF nurses who attended.

This study has limitations. As a single-hospital study, generalizability may be limited. While adherence to the program components was closely monitored daily, service gaps may have occurred that were not captured. The program design makes it difficult to quantify the relative impact of the 3 program components on the outcome. Furthermore, the study was observational, so the differences in readmission rates may have been due to unmeasured variables. The decision to enroll patients in the ECP was made by each patient’s SNF attending physician, and those who chose to (or not to) participate in the program may manifest other, unmeasured practice patterns that made readmissions more or less likely. Participating physicians also had the option to enroll their patients on a case-by-case basis, introducing further potential bias in patient selection; however, <5% of physicians exercised this option. Patients may have also been readmitted to hospitals other than CSMC, producing an observed readmission rate for 1 or both groups that underrepresents the true outcome. On this point, while we did not systematically track these other-hospital readmissions for both groups, there is no reason to believe that this occurred preferentially for ECP or non-ECP patients.

Multiple sensitivity analyses were performed to address the observed differences between ECP and non-ECP patients. These included stratified examinations of variables differing between populations, examination of clustering effects between SNFs, and an analysis adjusted for the propensity to be included in the ECP. The calculated effect of the intervention on readmission remained robust, although we acknowledge that differences in the populations may persist and have influenced the outcomes even after controlling for multiple variables.^22-25

In conclusion, the results of this intervention are compelling and add to the growing body of literature suggesting that a comprehensive, multipronged effort to enhance clinical oversight and coordination of care for SNF patients can improve outcomes. Given CMS’s plans to report SNF readmission rates in 2017 followed by the application of financial incentives in 2018, a favorable climate currently exists for greater coordination between hospitals and SNFs.²⁶ We are currently undertaking an economic evaluation of the program.

Acknowledgments

The authors would like to thank the following people for their contributions: Mae Saunders, Rita Shane, Dr. Jon Kea, Miranda Li, the ECP NPs, the ECP pharmacy team, CSMC’s performance improvement team, and Alan Matus.

Disclosure

 No conflicts of interest or disclosures.

Public reporting of readmission rates on the Nursing Home Compare website is mandated to begin on October 1, 2017, with skilled nursing facilities (SNFs) set to receive a Medicare bonus or penalty beginning a year later.¹ The Centers for Medicare & Medicaid Services (CMS) began public reporting of hospitals’ 30-day readmission rates for selected conditions in 2009, and the Patient Protection and Affordable Care Act of 2010 mandated financial penalties for excess readmissions through the Hospital Readmission Reduction Program.² In response, most hospitals have focused on patients who return home following discharge. Innovative interventions have proven successful, such as the Transitional Care model developed by Naylor and Coleman’s Care Transitions Intervention.^3-5 Approximately 20% of Medicare beneficiaries are discharged from hospitals to SNFs, and these patients have higher readmission rates than those discharged home. CMS reported that in 2010, 23.3% of those with an SNF stay were readmitted within 30 days, compared with 18.8% for those with other discharge dispositions.⁶

Some work has been undertaken in this arena. In 2012, the Center for Medicare and Medicaid Innovation (CMMI) and the Medicare-Medicaid Coordination Office jointly launched the Initiative to Reduce Avoidable Hospitalizations among Nursing Facility Residents.⁷ This partnership established 7 Enhanced Care and Coordination Provider organizations and was designed to improve care by reducing hospitalizations among long-stay, dual-eligible nursing facility residents at 143 nursing homes in 7 states.⁸ At the time of the most recent project report, there were mixed results regarding program effects on hospitalizations and spending, with 2 states showing strongly positive patterns, 3 states with reductions that were consistent though not statistically strong, and mixed results in the remaining states. Quality measures did not show any pattern suggesting a program effect.⁹ Interventions to Reduce Acute Care Transfers (INTERACT) II was a 6-month, collaborative, quality-improvement project implemented in 2009 at 30 nursing homes in 3 states.¹⁰ The project evaluation found a statistically significant, 17% decrease in self-reported hospital admissions among the 25 SNFs that completed the intervention, compared with the same 6 months in the prior year. The Cleveland Clinic recently reported favorable results implementing its Connected Care model, which relied on staff physicians and advanced practice professionals to visit patients 4 to 5 times per week and be on call 24/7 at 7 intervention SNFs.¹¹ Through this intervention, it successfully reduced its 30-day hospital readmission rate from SNFs from 28.1% to 21.7% (P < 0.001), and the authors posed the question as to whether its model and results were reproducible in other healthcare systems.

Herein, we report on the results of a collaborative initiative named the Enhanced Care Program (ECP), which offers the services of clinical providers and administrative staff to assist with the care of patients at 8 partner SNFs. The 3 components of ECP (described below) were specifically designed to address commonly recognized gaps and opportunities in routine SNF care. In contrast to the Cleveland Clinic’s Connected Care model (which involved hospital-employed physicians serving as the SNF attendings and excluded patients followed by their own physicians), ECP was designed to integrate into a pluralistic, community model whereby independent physicians continued to follow their own patients at the SNFs. The Connected Care analysis compared participating versus nonparticipating SNFs; both the Connected Care model and the INTERACT II evaluation relied on pre–post comparisons; the CMMI evaluation used a difference-in-differences model to compare the outcomes of the program SNFs with those of a matched comparison group of nonparticipating SNFs. The evaluation of ECP differs from these other initiatives, using a concurrent comparison group of patients discharged to the same SNFs but who were not enrolled in ECP.

Setting

Cedars-Sinai Medical Center (CSMC) is an 850-bed, acute care facility located in an urban area of Los Angeles. Eight SNFs, ranging in size from 49 to 150 beds and located between 0.6 and 2.2 miles from CSMC, were invited to partner with the ECP. The physician community encompasses more than 2000 physicians on the medical staff, including private practitioners, nonteaching hospitalists, full-time faculty hospitalists, and faculty specialists.

Study Design and Patients

This was an observational, retrospective cohort analysis of 30-day same-hospital readmissions among 3951 patients discharged from CSMC to 8 SNFs between January 1, 2014, and June 30, 2015. A total of 2394 patients were enrolled in the ECP, and 1557 patients were not enrolled.

ECP Enrollment Protocol

Every patient discharged from CSMC to 1 of the 8 partner SNFs was eligible to participate in the program. To respect the autonomy of the SNF attending physicians and to facilitate a collaborative relationship, the decision to enroll a patient in the ECP rested with the SNF attending physician. The ECP team maintained a database that tracked whether each SNF attending physician (1) opted to automatically enroll all his or her patients in the ECP, (2) opted to enroll patients on a case-by-case basis (in which case an ECP nurse practitioner [NP] contacted the attending physician for each eligible patient), or (3) opted out of the ECP completely. When a new SNF attending physician was encountered, the ECP medical director called the physician to explain the ECP and offer enrollment of his or her patient(s). Ultimately, patients (or their decision-makers) retained the right to opt in or out of the ECP at any time, regardless of the decision of the attending physicians.

Program Description

Patients enrolled in the ECP experienced the standard care provided by the SNF staff and attending physicians plus a clinical care program delivered by 9 full-time NPs, 1 full-time pharmacist, 1 pharmacy technician, 1 full-time nurse educator, a program administrator, and a medical director.

The program included the following 3 major components:

1. Direct patient care and 24/7 NP availability: Program enrollment began with an on-site, bedside evaluation by an ECP NP at the SNF within 24 hours of arrival and continued with weekly NP rounding (or more frequently, if clinically indicated) on the patient. Each encounter included a review of the medical record; a dialogue with the patient’s SNF attending physician to formulate treatment plans and place orders; discussions with nurses, family members, and other caregivers; and documentation in the medical record. The ECP team was on-site at the SNFs 7 days a week and on call 24/7 to address questions and concerns. Patients remained enrolled in the ECP from SNF admission to discharge even if their stay extended beyond 30 days.

2. Medication reconciliation: The ECP pharmacy team completed a review of a patient’s SNF medication administration record (MAR) within 72 hours of SNF admission. This process involved the pharmacy technician gathering medication lists from the SNFs and CSMC and providing this information to the pharmacist for a medication reconciliation and clinical evaluation. Discrepancies and pharmacist recommendations were communicated to the ECP NPs, and all identified issues were resolved.

3. Educational in-services: Building upon the INTERACT II model, the ECP team identified high-yield, clinically relevant topics, which the ECP nurse educator turned into monthly educational sessions for the SNF nursing staff at each of the participating SNFs.¹⁰

Primary Outcome Measure

An inpatient readmission to CSMC within 30 days of the hospital discharge date was counted as a readmission, whether the patient returned directly from an SNF or was readmitted from home after an SNF discharge.

Data

ECP patients were identified using a log maintained by the ECP program manager. Non-ECP patients discharged to the same SNFs during the study period were identified from CSMC’s electronic registry of SNF discharges. Covariates known to be associated with increased risk of 30-day readmission were obtained from CSMC’s electronic data warehouse, including demographic information, length of stay (LOS) of index hospitalization, and payer.¹² Eleven clinical service lines represented patients’ clinical conditions based on Medicare-Severity Diagnosis-Related groupings. The discharge severity of illness score was calculated using 3M All Patients Refined Diagnosis Related Group software, version 33.¹³

Analysis

Characteristics of the ECP and non-ECP patients were compared using the χ² test. A multivariable logistic regression model with fixed effects for SNF was created to determine the program’s impact on 30-day hospital readmission, adjusting for patient characteristics. The Pearson χ² goodness-of-fit test and the link test for model specification were used to evaluate model specification. The sensitivity of the results to differences in patient characteristics was assessed in 2 ways. First, the ECP and non-ECP populations were stratified based on race and/or ethnicity and payer, and the multivariable regression model was run within the strata associated with the highest readmission rates. Second, a propensity analysis using inverse probability of treatment weighting (IPTW) was performed to control for group differences. Results of all comparisons were considered statistically significant when P < 0.05. Stata version 13 was used to perform the main analyses.¹⁴ The propensity analysis was conducted using R version 3.2.3. The CSMC Institutional Review Board (IRB) determined that this study qualified as a quality-improvement activity and did not require IRB approval or exemption.

The average unadjusted 30-day readmission rate for ECP patients over the 18-month study period was 17.2%, compared to 23.0% for patients not enrolled in ECP (P < 0.001) (Figure 1). After adjusting for patient characteristics, ECP patients had 29% lower odds (95% confidence interval [CI], 0.60-0.85) of being readmitted to the medical center within 30 days than non-ECP patients at the same SNFs. The characteristics of the ECP and comparison patient cohorts are shown in Table 1. There were significant differences in sociodemographic characteristics: The ECP group had a higher proportion of non-Hispanic white patients, while the comparison group had a higher proportion of patients who were African American or Hispanic. ECP patients were more likely to prefer speaking English, while Russian, Farsi, and Spanish were preferred more frequently in the comparison group. There were also differences in payer mix, with the ECP group including proportionately more Medicare fee-for-service (52.9% vs 35.0%, P < 0.001), while the comparison group had a correspondingly larger proportion of dual-eligible (Medicare and Medicaid) patients (55.0% vs 35.1%, P < 0.001).

Sensitivity Analyses

The results were robust when tested within strata of the study population, including analyses limited to dual-eligible patients, African American patients, patients admitted to all except the highest volume facility, and patients admitted to any service line other than orthopedic surgery. Similar results were obtained when the study population was restricted to patients living within the medical center’s primary service area and to patients living in zip codes in which the proportion of adults living in households with income below 100% of the poverty level was 15% or greater (see Supplementary Material for results).

The effect of the program on readmission was also consistent when the full logistic regression model was run with IPTW using the propensity score. The evaluation of standardized cluster differences between the ECP and non-ECP groups before and after IPTW showed that the differences were reduced to <10% for being African American; speaking Russian or Farsi; having dual-eligible insurance coverage; having orthopedic surgery; being discharged from the clinical service lines of gastroenterology, pulmonary, other surgery, and other services; and having an index hospital LOS of 4 to 5 days or 10 or more days (results are provided in the Supplementary Material).

Hospitals continue to experience significant pressure to manage LOS, and SNFs and hospitals are being held accountable for readmission rates. The setting of this study is representative of many large, urban hospitals in the United States whose communities include a heterogeneous mix of hospitalists, primary care physicians who follow their patients in SNFs, and independent SNFs.¹⁵ The current regulations have not kept up with the increasing acuity and complexity of SNF patients. Specifically, Medicare guidelines allow the SNF attending physician up to 72 hours to complete a history and physical (or 7 days if he or she was the hospital attending physician for the index hospitalization) and only require monthly follow-up visits. It is the opinion of the ECP designers that these relatively lax requirements present unnecessary risk for vulnerable patients. While the INTERACT II model was focused largely on educational initiatives (with an advanced practice nurse available in a consultative role, as needed), the central tenet of ECP was similar to the Connected Care model in that the focus was on adding an extra layer of direct clinical support. Protocols that provided timely initial assessments by an NP (within 24 hours), weekly NP rounding (at a minimum), and 24/7 on-call availability all contributed to helping patients stay on track. Although the ECP had patients visited less frequently than the Connected Care model, and the Cleveland Clinic started with a higher baseline 30-day readmission rate from SNFs, similar overall reductions in 30-day readmissions were observed. The key point from both initiatives is that an increase in clinical touchpoints and ease of access to clinicians generates myriad opportunities to identify and address small issues before they become clinical emergencies requiring hospital transfers and readmissions.

Correcting medication discrepancies between hospital discharge summaries and SNF admission orders through a systematic medication reconciliation using a clinical pharmacist has previously been shown to improve outcomes.^16-18 The ECP pharmacy technician and ECP clinical pharmacist discovered and corrected errors on a daily basis that ranged from incidental to potentially life-threatening. If the SNF staff does not provide the patient’s MAR within 48 hours of arrival, the pharmacy technician contacts the facility to obtain the information. As a result, all patients enrolled in the ECP during the study period received this intervention (unless they were rehospitalized or left the SNF before the process was completed), and 54% of ECP patients required some form of intervention after medication reconciliation was completed (data not shown).

This type of program requires hospital leadership and SNF administrators to be fully committed to developing strong working relationships, and in fact, there is evidence that SNF baseline readmission rates have a greater influence on patients’ risk of rehospitalization than the discharging hospital itself.^19-21 Monthly educational in-services are delivered at the partner SNFs to enhance SNF nursing staff knowledge and clinical acumen. High-impact topics identified by the ECP team include the following: fall prevention, hand hygiene, venous thromboembolism, cardiovascular health, how to report change in condition, and advanced care planning, among others. While no formal pre–post assessments of the SNF nurses’ knowledge were conducted, a log of in-services was kept, subjective feedback was collected for performance improvement purposes, and continuing educational units were provided to the SNF nurses who attended.

This study has limitations. As a single-hospital study, generalizability may be limited. While adherence to the program components was closely monitored daily, service gaps may have occurred that were not captured. The program design makes it difficult to quantify the relative impact of the 3 program components on the outcome. Furthermore, the study was observational, so the differences in readmission rates may have been due to unmeasured variables. The decision to enroll patients in the ECP was made by each patient’s SNF attending physician, and those who chose to (or not to) participate in the program may manifest other, unmeasured practice patterns that made readmissions more or less likely. Participating physicians also had the option to enroll their patients on a case-by-case basis, introducing further potential bias in patient selection; however, <5% of physicians exercised this option. Patients may have also been readmitted to hospitals other than CSMC, producing an observed readmission rate for 1 or both groups that underrepresents the true outcome. On this point, while we did not systematically track these other-hospital readmissions for both groups, there is no reason to believe that this occurred preferentially for ECP or non-ECP patients.

Multiple sensitivity analyses were performed to address the observed differences between ECP and non-ECP patients. These included stratified examinations of variables differing between populations, examination of clustering effects between SNFs, and an analysis adjusted for the propensity to be included in the ECP. The calculated effect of the intervention on readmission remained robust, although we acknowledge that differences in the populations may persist and have influenced the outcomes even after controlling for multiple variables.^22-25

In conclusion, the results of this intervention are compelling and add to the growing body of literature suggesting that a comprehensive, multipronged effort to enhance clinical oversight and coordination of care for SNF patients can improve outcomes. Given CMS’s plans to report SNF readmission rates in 2017 followed by the application of financial incentives in 2018, a favorable climate currently exists for greater coordination between hospitals and SNFs.²⁶ We are currently undertaking an economic evaluation of the program.

Acknowledgments

The authors would like to thank the following people for their contributions: Mae Saunders, Rita Shane, Dr. Jon Kea, Miranda Li, the ECP NPs, the ECP pharmacy team, CSMC’s performance improvement team, and Alan Matus.

Disclosure

 No conflicts of interest or disclosures.

Public reporting of readmission rates on the Nursing Home Compare website is mandated to begin on October 1, 2017, with skilled nursing facilities (SNFs) set to receive a Medicare bonus or penalty beginning a year later.¹ The Centers for Medicare & Medicaid Services (CMS) began public reporting of hospitals’ 30-day readmission rates for selected conditions in 2009, and the Patient Protection and Affordable Care Act of 2010 mandated financial penalties for excess readmissions through the Hospital Readmission Reduction Program.² In response, most hospitals have focused on patients who return home following discharge. Innovative interventions have proven successful, such as the Transitional Care model developed by Naylor and Coleman’s Care Transitions Intervention.^3-5 Approximately 20% of Medicare beneficiaries are discharged from hospitals to SNFs, and these patients have higher readmission rates than those discharged home. CMS reported that in 2010, 23.3% of those with an SNF stay were readmitted within 30 days, compared with 18.8% for those with other discharge dispositions.⁶

Some work has been undertaken in this arena. In 2012, the Center for Medicare and Medicaid Innovation (CMMI) and the Medicare-Medicaid Coordination Office jointly launched the Initiative to Reduce Avoidable Hospitalizations among Nursing Facility Residents.⁷ This partnership established 7 Enhanced Care and Coordination Provider organizations and was designed to improve care by reducing hospitalizations among long-stay, dual-eligible nursing facility residents at 143 nursing homes in 7 states.⁸ At the time of the most recent project report, there were mixed results regarding program effects on hospitalizations and spending, with 2 states showing strongly positive patterns, 3 states with reductions that were consistent though not statistically strong, and mixed results in the remaining states. Quality measures did not show any pattern suggesting a program effect.⁹ Interventions to Reduce Acute Care Transfers (INTERACT) II was a 6-month, collaborative, quality-improvement project implemented in 2009 at 30 nursing homes in 3 states.¹⁰ The project evaluation found a statistically significant, 17% decrease in self-reported hospital admissions among the 25 SNFs that completed the intervention, compared with the same 6 months in the prior year. The Cleveland Clinic recently reported favorable results implementing its Connected Care model, which relied on staff physicians and advanced practice professionals to visit patients 4 to 5 times per week and be on call 24/7 at 7 intervention SNFs.¹¹ Through this intervention, it successfully reduced its 30-day hospital readmission rate from SNFs from 28.1% to 21.7% (P < 0.001), and the authors posed the question as to whether its model and results were reproducible in other healthcare systems.

Herein, we report on the results of a collaborative initiative named the Enhanced Care Program (ECP), which offers the services of clinical providers and administrative staff to assist with the care of patients at 8 partner SNFs. The 3 components of ECP (described below) were specifically designed to address commonly recognized gaps and opportunities in routine SNF care. In contrast to the Cleveland Clinic’s Connected Care model (which involved hospital-employed physicians serving as the SNF attendings and excluded patients followed by their own physicians), ECP was designed to integrate into a pluralistic, community model whereby independent physicians continued to follow their own patients at the SNFs. The Connected Care analysis compared participating versus nonparticipating SNFs; both the Connected Care model and the INTERACT II evaluation relied on pre–post comparisons; the CMMI evaluation used a difference-in-differences model to compare the outcomes of the program SNFs with those of a matched comparison group of nonparticipating SNFs. The evaluation of ECP differs from these other initiatives, using a concurrent comparison group of patients discharged to the same SNFs but who were not enrolled in ECP.

Setting

Cedars-Sinai Medical Center (CSMC) is an 850-bed, acute care facility located in an urban area of Los Angeles. Eight SNFs, ranging in size from 49 to 150 beds and located between 0.6 and 2.2 miles from CSMC, were invited to partner with the ECP. The physician community encompasses more than 2000 physicians on the medical staff, including private practitioners, nonteaching hospitalists, full-time faculty hospitalists, and faculty specialists.

Study Design and Patients

This was an observational, retrospective cohort analysis of 30-day same-hospital readmissions among 3951 patients discharged from CSMC to 8 SNFs between January 1, 2014, and June 30, 2015. A total of 2394 patients were enrolled in the ECP, and 1557 patients were not enrolled.

ECP Enrollment Protocol

Every patient discharged from CSMC to 1 of the 8 partner SNFs was eligible to participate in the program. To respect the autonomy of the SNF attending physicians and to facilitate a collaborative relationship, the decision to enroll a patient in the ECP rested with the SNF attending physician. The ECP team maintained a database that tracked whether each SNF attending physician (1) opted to automatically enroll all his or her patients in the ECP, (2) opted to enroll patients on a case-by-case basis (in which case an ECP nurse practitioner [NP] contacted the attending physician for each eligible patient), or (3) opted out of the ECP completely. When a new SNF attending physician was encountered, the ECP medical director called the physician to explain the ECP and offer enrollment of his or her patient(s). Ultimately, patients (or their decision-makers) retained the right to opt in or out of the ECP at any time, regardless of the decision of the attending physicians.

Program Description

Patients enrolled in the ECP experienced the standard care provided by the SNF staff and attending physicians plus a clinical care program delivered by 9 full-time NPs, 1 full-time pharmacist, 1 pharmacy technician, 1 full-time nurse educator, a program administrator, and a medical director.

The program included the following 3 major components:

1. Direct patient care and 24/7 NP availability: Program enrollment began with an on-site, bedside evaluation by an ECP NP at the SNF within 24 hours of arrival and continued with weekly NP rounding (or more frequently, if clinically indicated) on the patient. Each encounter included a review of the medical record; a dialogue with the patient’s SNF attending physician to formulate treatment plans and place orders; discussions with nurses, family members, and other caregivers; and documentation in the medical record. The ECP team was on-site at the SNFs 7 days a week and on call 24/7 to address questions and concerns. Patients remained enrolled in the ECP from SNF admission to discharge even if their stay extended beyond 30 days.

2. Medication reconciliation: The ECP pharmacy team completed a review of a patient’s SNF medication administration record (MAR) within 72 hours of SNF admission. This process involved the pharmacy technician gathering medication lists from the SNFs and CSMC and providing this information to the pharmacist for a medication reconciliation and clinical evaluation. Discrepancies and pharmacist recommendations were communicated to the ECP NPs, and all identified issues were resolved.

3. Educational in-services: Building upon the INTERACT II model, the ECP team identified high-yield, clinically relevant topics, which the ECP nurse educator turned into monthly educational sessions for the SNF nursing staff at each of the participating SNFs.¹⁰

Primary Outcome Measure

An inpatient readmission to CSMC within 30 days of the hospital discharge date was counted as a readmission, whether the patient returned directly from an SNF or was readmitted from home after an SNF discharge.

Data

ECP patients were identified using a log maintained by the ECP program manager. Non-ECP patients discharged to the same SNFs during the study period were identified from CSMC’s electronic registry of SNF discharges. Covariates known to be associated with increased risk of 30-day readmission were obtained from CSMC’s electronic data warehouse, including demographic information, length of stay (LOS) of index hospitalization, and payer.¹² Eleven clinical service lines represented patients’ clinical conditions based on Medicare-Severity Diagnosis-Related groupings. The discharge severity of illness score was calculated using 3M All Patients Refined Diagnosis Related Group software, version 33.¹³

Analysis

Characteristics of the ECP and non-ECP patients were compared using the χ² test. A multivariable logistic regression model with fixed effects for SNF was created to determine the program’s impact on 30-day hospital readmission, adjusting for patient characteristics. The Pearson χ² goodness-of-fit test and the link test for model specification were used to evaluate model specification. The sensitivity of the results to differences in patient characteristics was assessed in 2 ways. First, the ECP and non-ECP populations were stratified based on race and/or ethnicity and payer, and the multivariable regression model was run within the strata associated with the highest readmission rates. Second, a propensity analysis using inverse probability of treatment weighting (IPTW) was performed to control for group differences. Results of all comparisons were considered statistically significant when P < 0.05. Stata version 13 was used to perform the main analyses.¹⁴ The propensity analysis was conducted using R version 3.2.3. The CSMC Institutional Review Board (IRB) determined that this study qualified as a quality-improvement activity and did not require IRB approval or exemption.

The average unadjusted 30-day readmission rate for ECP patients over the 18-month study period was 17.2%, compared to 23.0% for patients not enrolled in ECP (P < 0.001) (Figure 1). After adjusting for patient characteristics, ECP patients had 29% lower odds (95% confidence interval [CI], 0.60-0.85) of being readmitted to the medical center within 30 days than non-ECP patients at the same SNFs. The characteristics of the ECP and comparison patient cohorts are shown in Table 1. There were significant differences in sociodemographic characteristics: The ECP group had a higher proportion of non-Hispanic white patients, while the comparison group had a higher proportion of patients who were African American or Hispanic. ECP patients were more likely to prefer speaking English, while Russian, Farsi, and Spanish were preferred more frequently in the comparison group. There were also differences in payer mix, with the ECP group including proportionately more Medicare fee-for-service (52.9% vs 35.0%, P < 0.001), while the comparison group had a correspondingly larger proportion of dual-eligible (Medicare and Medicaid) patients (55.0% vs 35.1%, P < 0.001).

Sensitivity Analyses

The results were robust when tested within strata of the study population, including analyses limited to dual-eligible patients, African American patients, patients admitted to all except the highest volume facility, and patients admitted to any service line other than orthopedic surgery. Similar results were obtained when the study population was restricted to patients living within the medical center’s primary service area and to patients living in zip codes in which the proportion of adults living in households with income below 100% of the poverty level was 15% or greater (see Supplementary Material for results).

The effect of the program on readmission was also consistent when the full logistic regression model was run with IPTW using the propensity score. The evaluation of standardized cluster differences between the ECP and non-ECP groups before and after IPTW showed that the differences were reduced to <10% for being African American; speaking Russian or Farsi; having dual-eligible insurance coverage; having orthopedic surgery; being discharged from the clinical service lines of gastroenterology, pulmonary, other surgery, and other services; and having an index hospital LOS of 4 to 5 days or 10 or more days (results are provided in the Supplementary Material).

Hospitals continue to experience significant pressure to manage LOS, and SNFs and hospitals are being held accountable for readmission rates. The setting of this study is representative of many large, urban hospitals in the United States whose communities include a heterogeneous mix of hospitalists, primary care physicians who follow their patients in SNFs, and independent SNFs.¹⁵ The current regulations have not kept up with the increasing acuity and complexity of SNF patients. Specifically, Medicare guidelines allow the SNF attending physician up to 72 hours to complete a history and physical (or 7 days if he or she was the hospital attending physician for the index hospitalization) and only require monthly follow-up visits. It is the opinion of the ECP designers that these relatively lax requirements present unnecessary risk for vulnerable patients. While the INTERACT II model was focused largely on educational initiatives (with an advanced practice nurse available in a consultative role, as needed), the central tenet of ECP was similar to the Connected Care model in that the focus was on adding an extra layer of direct clinical support. Protocols that provided timely initial assessments by an NP (within 24 hours), weekly NP rounding (at a minimum), and 24/7 on-call availability all contributed to helping patients stay on track. Although the ECP had patients visited less frequently than the Connected Care model, and the Cleveland Clinic started with a higher baseline 30-day readmission rate from SNFs, similar overall reductions in 30-day readmissions were observed. The key point from both initiatives is that an increase in clinical touchpoints and ease of access to clinicians generates myriad opportunities to identify and address small issues before they become clinical emergencies requiring hospital transfers and readmissions.

Correcting medication discrepancies between hospital discharge summaries and SNF admission orders through a systematic medication reconciliation using a clinical pharmacist has previously been shown to improve outcomes.^16-18 The ECP pharmacy technician and ECP clinical pharmacist discovered and corrected errors on a daily basis that ranged from incidental to potentially life-threatening. If the SNF staff does not provide the patient’s MAR within 48 hours of arrival, the pharmacy technician contacts the facility to obtain the information. As a result, all patients enrolled in the ECP during the study period received this intervention (unless they were rehospitalized or left the SNF before the process was completed), and 54% of ECP patients required some form of intervention after medication reconciliation was completed (data not shown).

This type of program requires hospital leadership and SNF administrators to be fully committed to developing strong working relationships, and in fact, there is evidence that SNF baseline readmission rates have a greater influence on patients’ risk of rehospitalization than the discharging hospital itself.^19-21 Monthly educational in-services are delivered at the partner SNFs to enhance SNF nursing staff knowledge and clinical acumen. High-impact topics identified by the ECP team include the following: fall prevention, hand hygiene, venous thromboembolism, cardiovascular health, how to report change in condition, and advanced care planning, among others. While no formal pre–post assessments of the SNF nurses’ knowledge were conducted, a log of in-services was kept, subjective feedback was collected for performance improvement purposes, and continuing educational units were provided to the SNF nurses who attended.

This study has limitations. As a single-hospital study, generalizability may be limited. While adherence to the program components was closely monitored daily, service gaps may have occurred that were not captured. The program design makes it difficult to quantify the relative impact of the 3 program components on the outcome. Furthermore, the study was observational, so the differences in readmission rates may have been due to unmeasured variables. The decision to enroll patients in the ECP was made by each patient’s SNF attending physician, and those who chose to (or not to) participate in the program may manifest other, unmeasured practice patterns that made readmissions more or less likely. Participating physicians also had the option to enroll their patients on a case-by-case basis, introducing further potential bias in patient selection; however, <5% of physicians exercised this option. Patients may have also been readmitted to hospitals other than CSMC, producing an observed readmission rate for 1 or both groups that underrepresents the true outcome. On this point, while we did not systematically track these other-hospital readmissions for both groups, there is no reason to believe that this occurred preferentially for ECP or non-ECP patients.

Multiple sensitivity analyses were performed to address the observed differences between ECP and non-ECP patients. These included stratified examinations of variables differing between populations, examination of clustering effects between SNFs, and an analysis adjusted for the propensity to be included in the ECP. The calculated effect of the intervention on readmission remained robust, although we acknowledge that differences in the populations may persist and have influenced the outcomes even after controlling for multiple variables.^22-25

In conclusion, the results of this intervention are compelling and add to the growing body of literature suggesting that a comprehensive, multipronged effort to enhance clinical oversight and coordination of care for SNF patients can improve outcomes. Given CMS’s plans to report SNF readmission rates in 2017 followed by the application of financial incentives in 2018, a favorable climate currently exists for greater coordination between hospitals and SNFs.²⁶ We are currently undertaking an economic evaluation of the program.

Acknowledgments

The authors would like to thank the following people for their contributions: Mae Saunders, Rita Shane, Dr. Jon Kea, Miranda Li, the ECP NPs, the ECP pharmacy team, CSMC’s performance improvement team, and Alan Matus.

Disclosure

 No conflicts of interest or disclosures.

This article reviews recommendations and evidence concerning current anticoagulant management for venous thromboembolism and perioperative care, with an emphasis on individualizing treatment for real-world patients.

TREATING ACUTE VENOUS THROMBOEMBOLISM

Case 1: Deep vein thrombosis in an otherwise healthy man

A 40-year-old man presents with 7 days of progressive right leg swelling. He has no antecedent risk factors for deep vein thrombosis or other medical problems. Venous ultrasonography reveals an iliofemoral deep vein thrombosis. How should he be managed?

• Outpatient treatment with low-molecular-weight heparin for 4 to 6 days plus warfarin
• Outpatient treatment with a direct oral anticoagulant, ie, apixaban, dabigatran (which requires 4 to 6 days of initial treatment with low-molecular-weight heparin), or rivaroxaban
• Catheter-directed thrombolysis followed by low-molecular-weight heparin, then warfarin or a direct oral anticoagulant
• Inpatient intravenous heparin for 7 to 10 days, then warfarin or a direct oral anticoagulant

All of these are acceptable for managing acute venous thromboembolism, but the clinician’s role is to identify which treatment is most appropriate for an individual patient.

Deep vein thrombosis is not a single condition

Multiple guidelines exist to help decide on a management strategy. Those of the American College of Chest Physicians (ACCP)¹ are used most often.

That said, guidelines are established for “average” patients, so it is important to look beyond guidelines and individualize management. Venous thromboembolism is not a single entity; it has a myriad of clinical presentations that could call for different treatments. Most patients have submassive deep vein thrombosis or pulmonary embolism, which is not limb-threatening nor associated with hemodynamic instability. It can also differ in terms of etiology and can be unprovoked (or idiopathic), cancer-related, catheter-associated, or provoked by surgery or immobility.

Deep vein thrombosis has a wide spectrum of presentations. It can involve the veins of the calf only, or it can involve the femoral and iliac veins and other locations including the splanchnic veins, the cerebral sinuses, and upper extremities. Pulmonary embolism can be massive (defined as being associated with hemodynamic instability or impending respiratory failure) or submassive. Similarly, patients differ in terms of baseline medical conditions, mobility, and lifestyle. Anticoagulant management decisions should take all these factors into account.

Consider clot location

Our patient with iliofemoral deep vein thrombosis is best managed differently than a more typical patient with less extensive thrombosis that would involve the popliteal or femoral vein segments, or both. A clot that involves the iliac vein is more likely to lead to postthrombotic chronic pain and swelling as the lack of venous outflow bypass channels to circumvent the clot location creates higher venous pressure within the affected leg. Therefore, for our patient, catheter-directed thrombolysis is an option that should be considered.

Catheter-directed thrombolysis trials

According to the “open-vein hypothesis,” quickly eliminating the thrombus and restoring unobstructed venous flow may mitigate the risk not only of recurrent thrombosis, but also of postthrombotic syndrome, which is often not given much consideration acutely but can cause significant, life-altering chronic disability.

The “valve-integrity hypothesis” is also important; it considers whether lytic therapy may help prevent damage to such valves in an attempt to mitigate the amount of venous hypertension.

Thus, catheter-directed thrombolysis offers theoretical benefits, and recent trials have assessed it against standard anticoagulation treatments.

The CaVenT trial (Catheter-Directed Venous Thrombolysis),² conducted in Norway, randomized 209 patients with midfemoral to iliac deep vein thrombosis to conventional treatment (anticoagulation alone) or anticoagulation plus catheter-directed thrombolysis. At 2 years, postthrombotic syndrome had occurred in 41% of the catheter-directed thrombolysis group compared with 56% of the conventional treatment group (P = .047). At 5 years, the difference widened to 43% vs 71% (P < .01, number needed to treat = 4).³ Despite the superiority of lytic therapy, the incidence of postthrombotic syndrome remained high in patients who received this treatment. 

The ATTRACT trial (Acute Venous Thrombosis: Thrombus Removal With Adjunctive Catheter-Directed Thrombolysis),⁴ a US multicenter, open-label, assessor-blind study, randomized 698 patients with femoral or more-proximal deep vein thrombosis to either standard care (anticoagulant therapy and graduated elastic compression stockings) or standard care plus catheter-directed thrombolysis. In preliminary results presented at the Society of Interventional Radiology meeting in March 2017, although no difference was found in the primary outcome (postthrombotic syndrome at 24 months), catheter-directed thrombolysis for iliofemoral deep vein thrombosis led to a 25% reduction in moderate to severe postthrombotic syndrome.

Although it is too early to draw conclusions before publication of the ATTRACT study, the preliminary results highlight the need to individualize treatment and to be selective about using catheter-directed thrombolysis. The trials provide reassurance that catheter-directed lysis is a reasonable and safe intervention when performed by physicians experienced in the procedure. The risk of major bleeding appears to be low (about 2%) and that for intracranial hemorrhage even lower (< 0.5%).

Catheter-directed thrombolysis is appropriate in some cases

The 2016 ACCP guidelines¹ recommend anticoagulant therapy alone over catheter-directed thrombolysis for patients with acute proximal deep vein thrombosis of the leg. However, it is a grade 2C (weak) recommendation.

They provide no specific recommendation as to the clinical indications for catheter-directed thrombolysis, but identify patients who would be most likely to benefit, ie, those who have: 

• Iliofemoral deep vein thrombosis
• Symptoms for less than 14 days
• Good functional status
• Life expectancy of more than 1 year
• Low risk of bleeding.

Our patient satisfies these criteria, suggesting that catheter-directed thrombolysis is a reasonable option for him. 

Timing is important. Catheter-directed lysis is more likely to be beneficial if used before fibrin deposits form and stiffen the venous valves, causing irreversible damage that leads to postthrombotic syndrome. 

The availability of direct oral anticoagulants has generated interest in defining their therapeutic role in patients with venous thromboembolism.

In a meta-analysis⁵ of major trials comparing direct oral anticoagulants and vitamin K antagonists such as warfarin, no significant difference was found for the risk of recurrent venous thromboembolism or venous thromboembolism-related deaths. However, fewer patients experienced major bleeding with direct oral anticoagulants (relative risk 0.61, P = .002). Although significant, the absolute risk reduction was small; the incidence of major bleeding was 1.1% with direct oral anticoagulants vs 1.8% with vitamin K antagonists.

The main advantage of direct oral anticoagulants is greater convenience for the patient.

WHICH PATIENTS ON WARFARIN NEED BRIDGING PREOPERATIVELY?

Many patients still take warfarin, particularly those with atrial fibrillation, a mechanical heart valve, or venous thromboembolism. In many countries, warfarin remains the dominant anticoagulant for stroke prevention. Whether these patients need heparin during the period of perioperative warfarin interruption is a frequently encountered scenario that, until recently, was controversial. Recent studies have helped to inform the need for heparin bridging in many of these patients.

Case 2: An elderly woman on warfarin facing cancer surgery

A 75-year-old woman weighing 65 kg is scheduled for elective colon resection for incidentally found colon cancer. She is taking warfarin for atrial fibrillation. She also has hypertension and diabetes and had a transient ischemic attack 10 years ago.

One doctor told her she needs to be assessed for heparin bridging, but another told her she does not need bridging.

The default management should be not to bridge patients who have atrial fibrillation, but to consider bridging in selected patients, such as those with recent stroke or transient ischemic attack or a prior thromboembolic event during warfarin interruption. However, decisions about bridging should not be made on the basis of the CHADS₂ score alone. For the patient described here, I would recommend not bridging.

Complex factors contribute to stroke risk

Stroke risk for patients with atrial fibrillation can be quickly estimated with the CHADS₂ score, based on: 

• Congestive heart failure (1 point)
• Hypertension (1 point)
• Age at least 75 (1 point)
• Diabetes (1 point)
• Stroke or transient ischemic attack (2 points).

Our patient has a score of 5, corresponding to an annual adjusted stroke risk of 12.5%. Whether her transient ischemic attack of 10 years ago is comparable in significance to a recent stroke is debatable and highlights a weakness of clinical prediction rules. Moreover, such prediction scores were developed to estimate the long-term risk of stroke if anticoagulants are not given, and they have not been assessed in a perioperative setting where there is short-term interruption of anticoagulants. Also, the perioperative milieu is associated with additional factors not captured in these clinical prediction rules that may affect the risk of stroke.

Thus, the risk of perioperative stroke likely involves the interplay of multiple factors, including the type of surgery the patient is undergoing. Some factors may be mitigated:

• Rebound hypercoagulability after stopping an oral anticoagulant can be prevented by intraoperative blood pressure and volume control
• Elevated biochemical factors (eg, D-dimer, B-type natriuretic peptide, troponin) may be lowered with perioperative aspirin therapy
• Lipid and genetic factors may be mitigated with perioperative statin use.

Can heparin bridging also mitigate the risk?

Bridging in patients with atrial fibrillation

Most patients who are taking warfarin are doing so because of atrial fibrillation, so most evidence about perioperative bridging was developed in such patients.

The BRIDGE trial (Bridging Anticoagulation in Patients Who Require Temporary Interruption of Warfarin Therapy for an Elective Invasive Procedure or Surgery)⁶ was the first randomized controlled trial to compare a bridging and no-bridging strategy for patients with atrial fibrillation who required warfarin interruption for elective surgery. Nearly 2,000 patients were given either low-molecular-weight heparin or placebo starting 3 days before until 24 hours before a procedure, and then for 5 to 10 days afterwards. For all patients, warfarin was stopped 5 days before the procedure and was resumed within 24 hours afterwards.

A no-bridging strategy was noninferior to bridging: the risk of perioperative arterial thromboembolism was 0.4% without bridging vs 0.3% with bridging (P = .01 for noninferiority). In addition, a no-bridging strategy conferred a lower risk of major bleeding than bridging: 1.3% vs 3.2% (relative risk 0.41, P = .005 for superiority).

Although the difference in absolute bleeding risk was small, bleeding rates were lower than those seen outside of clinical trials, as the bridging protocol used in BRIDGE was designed to minimize the risk of bleeding. Also, although only 5% of patients had a CHADS₂ score of 5 or 6, such patients are infrequent in clinical practice, and BRIDGE did include a considerable proportion (17%) of patients with a prior stroke or transient ischemic attack who would be considered at high risk.

Other evidence about heparin bridging is derived from observational studies, more than 10 of which have been conducted. In general, they have found that not bridging is associated with low rates of arterial thromboembolism (< 0.5%) and that bridging is associated with high rates of major bleeding (4%–7%).^7–12

Bridging in patients with a mechanical heart valve

Warfarin is the only anticoagulant option for patients who have a mechanical heart valve. No randomized controlled trials have evaluated the benefits of perioperative bridging vs no bridging in this setting.

Observational (cohort) studies suggest that the risk of perioperative arterial thromboembolism is similar with or without bridging anticoagulation, although most patients studied were bridged and those not bridged were considered at low risk (eg, with a bileaflet aortic valve and no additional risk factors).¹³ However, without stronger evidence from randomized controlled trials, bridging should be the default management for patients with a mechanical heart valve. In our practice, we bridge most patients who have a mechanical heart valve unless they are considered to be at low risk, such as those who have a bileaflet aortic valve.

Even less evidence is available for periprocedural management of patients who have a history of venous thromboembolism. No randomized controlled trials exist evaluating bridging vs no bridging. In 1 cohort study in which more than 90% of patients had had thromboembolism more than 3 months before the procedure, the rate of recurrent venous thromboembolism without bridging was less than 0.5%.¹⁴

It is reasonable to bridge patients who need anticoagulant interruption within 3 months of diagnosis of a deep vein thrombosis or pulmonary embolism, and to consider using a temporary inferior vena cava filter for patients who have had a clot who need treatment interruption during the initial 3 to 4 weeks after diagnosis.

Practice guidelines: Perioperative anticoagulation

Guidance for preoperative and postoperative bridging for patients taking warfarin is summarized in Table 2.

CARDIAC PROCEDURES

For patients facing a procedure to implant an implantable cardioverter-defibrillator (ICD) or pacemaker, a procedure-specific concern is the avoidance of pocket hematoma.

Patients on warfarin: Do not bridge

The BRUISE CONTROL-1 trial (Bridge or Continue Coumadin for Device Surgery Randomized Controlled Trial)¹⁹ randomized patients undergoing pacemaker or ICD implantation to either continued anticoagulation therapy and not bridging (ie, continued warfarin so long as the international normalized ratio was < 3) vs conventional bridging treatment (ie, stopping warfarin and bridging with low-molecular-weight heparin). A clinically significant device-pocket hematoma occurred in 3.5% of the continued-warfarin group vs 16.0% in the heparin-bridging group (P < .001). Thromboembolic complications were rare, and rates did not differ between the 2 groups.

Results of the BRUISE CONTROL-1 trial serve as a caution to at least not be too aggressive with bridging. The study design involved resuming heparin 24 hours after surgery, which is perhaps more aggressive than standard practice. In our practice, we wait at least 24 hours to reinstate heparin after minor surgery, and 48 to 72 hours after surgery with higher bleeding risk.

These results are perhaps not surprising if one considers how carefully surgeons try to control bleeding during surgery for patients taking anticoagulants. For patients who are not on an anticoagulant, small bleeding may be less of a concern during a procedure. When high doses of heparin are introduced soon after surgery, small concerns during surgery may become big problems afterward.

Based on these results, it is reasonable to undertake device implantation without interruption of a vitamin K antagonist such as warfarin.

Patients on direct oral anticoagulants: The jury is still out

The similar BRUISE CONTROL-2 trial is currently under way, comparing interruption vs continuation of dabigatran for patients undergoing cardiac device surgery.

In Europe, surgeons are less concerned than those in the United States about operating while a patient is on anticoagulant therapy. But the safety of this practice is not backed by strong evidence.

Direct oral anticoagulants: Consider pharmacokinetics

Direct oral anticoagulants are potent and fast-acting, with a peak effect 1 to 3 hours after intake. This rapid anticoagulant action is similar to that of bridging with low-molecular-weight heparin, and caution is needed when administering direct oral anticoagulants, especially after major surgery or surgery with a high bleeding risk.

Frost et al²⁰ compared the pharmacokinetics of apixaban (with twice-daily dosing) and rivaroxaban (once-daily dosing) and found that peak anticoagulant activity is faster and higher with rivaroxaban. This is important, because many patients will take their anticoagulant first thing in the morning. Consequently, if patients require any kind of procedure (including dental), they should skip the morning dose of the direct oral anticoagulant to avoid having the procedure done during the peak anticoagulant effect, and they should either not take that day’s dose or defer the dose until the evening after the procedure. 

MANAGING SURGERY FOR PATIENTS ON A DIRECT ORAL ANTICOAGULANT

Case 3: An elderly woman on apixaban facing surgery

Let us imagine that our previous patient takes apixaban instead of warfarin. She is 75 years old, has atrial fibrillation, and is about to undergo elective colon resection for cancer. One doctor advises her to simply stop apixaban for 2 days, while another says she should go off apixaban for 5 days and will need bridging. Which plan is best?

In the perioperative setting, our goal is to interrupt patients’ anticoagulant therapy for the shortest time that results in no residual anticoagulant effect at the time of the procedure. 

They further recommend that if the risk of venous thromboembolism is high, low-molecular-weight heparin bridging should be done while stopping the direct oral anticoagulant, with the heparin discontinued 24 hours before the procedure. This recommendation seems counterintuitive, as it is advising replacing a short-acting anticoagulant with low-molecular-weight heparin, another short-acting anticoagulant.

The guidelines committee was unable to provide strength and grading of their recommendations, as too few well-designed studies are available to support them. The doctor in case 3 who advised stopping apixaban for 5 days and bridging is following the guidelines, but without much evidence to support this strategy.

There are no randomized, controlled trials of bridging vs no bridging in patients taking direct oral anticoagulants. Substudies exist of patients taking these drugs for atrial fibrillation who had treatment interrupted for procedures, but the studies did not randomize bridging vs no bridging, nor were bridging regimens standardized. Three of the four atrial fibrillation trials had a blinded design (warfarin vs direct oral anticoagulants), making perioperative management difficult, as physicians did not know the pharmacokinetics of the drugs their patients were taking.^22–24

We used the database from the Randomized Evaluation of Long-Term Anticoagulation Therapy (RE-LY) trial²² to evaluate bridging in patients taking either warfarin or dabigatran. With an open-label study design (the blinding was only for the 110 mg and 150 mg dabigatran doses), clinicians were aware of whether patients were receiving warfarin or dabigatran, thereby facilitating perioperative management. Among dabigatran-treated patients, those who were bridged had significantly more major bleeding than those not bridged (6.5% vs 1.8%, P < .001), with no difference between the groups for stroke or systemic embolism. Although it is not a randomized controlled trial, it does provide evidence that bridging may not be advisable for patients taking a direct oral anticoagulant.

The 2017 American College of Cardiology guidelines²⁵ conclude that parenteral bridging is not indicated for direct oral anticoagulants. Although this is not based on strong evidence, the guidance appears reasonable according to the evidence at hand.

The 2017 American Heart Association Guidelines¹⁶ recommend a somewhat complex approach based on periprocedural bleeding risk and thromboembolic risk.

How long to interrupt direct oral anticoagulants?

Evidence for this approach comes from a prospective cohort study²⁷ of 541 patients being treated with dabigatran who were having an elective surgery or invasive procedure. Patients received standard perioperative management, with the timing of the last dabigatran dose before the procedure (24 hours, 48 hours, or 96 hours) based on the bleeding risk of surgery and the patient’s creatinine clearance. Dabigatran was resumed 24 to 72 hours after the procedure. No heparin bridging was done. Patients were followed for up to 30 days postoperatively. The results were favorable with few complications: one transient ischemic attack (0.2%), 10 major bleeding episodes (1.8%), and 28 minor bleeding episodes (5.2%).

A subgroup of 181 patients in this study²⁸ had a plasma sample drawn just before surgery, allowing the investigators to assess the level of coagulation factors after dabigatran interruption. Results were as follows:

• 93% had a normal prothrombin time 
• 80% had a normal activated partial thromboplastin time
• 33% had a normal thrombin time
• 81% had a normal dilute thrombin time.

The dilute thrombin time is considered the most reliable test of the anticoagulant effect of dabigatran but is not widely available. The activated partial thromboplastin time can provide a more widely used coagulation test to assess (in a less precise manner) whether there is an anticoagulant effect of dabigatran present, and more sensitive activated partial thromboplastin time assays can be used to better detect any residual dabigatran effect.

Dabigatran levels were also measured. Although 66% of patients had low drug levels just before surgery, the others still had substantial dabigatran on board. The fact that bleeding event rates were so low in this study despite the presence of dabigatran in many patients raises the question of whether having some drug on board is a good predictor of bleeding risk.

An interruption protocol with a longer interruption interval—12 to 14 hours longer than in the previous study (3 days for high-bleed risk procedures, 2 days for low-bleed risk procedures)—brought the activated partial thromboplastin time and dilute thrombin time to normal levels for 100% of patients with the protocol for high-bleeding-risk surgery. This study was based on small numbers and its interruption strategy needs further investigation.²⁹

Case 3 continued

The PAUSE study (NCT02228798), a multicenter, prospective cohort study, is designed to establish a safe, standardized protocol for the perioperative management of patients with atrial fibrillation taking dabigatran, rivaroxaban, or apixaban and will include 3,300 patients.

PATIENTS WITH A CORONARY STENT WHO NEED SURGERY

Case 4: A woman with a stent facing surgery

A 70-year-old woman needs breast cancer resection. She has coronary artery disease and had a drug-eluting stent placed 5 months ago after elective cardiac catheterization. She also has hypertension, obesity, and type 2 diabetes. Her medications include an angiotensin II receptor blocker, hydrochlorothiazide, insulin, and an oral hypoglycemic. She is also taking aspirin 81 mg daily and ticagrelor (a P2Y₁₂ receptor antagonist) 90 mg twice daily.

Her cardiologist is concerned that stopping antiplatelet therapy could trigger acute stent thrombosis, which has a 50% or higher mortality rate.

Should she stop taking aspirin before surgery? What about the ticagrelor?

Evidence concerning aspirin during surgery comes from Perioperative Ischemic Evaluation 2 (POISE-2), a double-blind, randomized controlled trial.³⁰ Patients who had known cardiovascular disease or risk factors for cardiovascular disease and were about to undergo noncardiac surgery were stratified according to whether they had been taking aspirin before the study (patients taking aspirin within 72 hours of the surgery were excluded from randomization). Participants in each group were randomized to take either aspirin or placebo just before surgery. The primary outcome was the combined rate of death or nonfatal myocardial infarction 30 days after randomization.

The study found no differences in the primary end point between the two groups. However, major bleeding occurred significantly more often in the aspirin group (4.6% vs 3.8%, hazard ratio 1.2, 95% confidence interval 1.0–1.5).

Moreover, only 4% of the patients in this trial had a cardiac stent. The trial excluded patients who had had a bare-metal stent placed within 6 weeks or a drug-eluting stent placed within 1 year, so it does not help us answer whether aspirin should be stopped for our current patient.

Is surgery safe for patients with stents?

The safety of undergoing surgery with a stent was investigated in a large US Veterans Administration retrospective cohort study.³¹ More than 20,000 patients with stents who underwent noncardiac surgery within 2 years of stent placement were compared with a control group of more than 41,000 patients with stents who did not undergo surgery. Patients were matched by stent type and cardiac risk factors at the time of stent placement.

The risk of an adverse cardiac event in both the surgical and nonsurgical cohorts was highest in the initial 6 weeks after stent placement and plateaued 6 months after stent placement, when the risk difference between the surgical and nonsurgical groups leveled off to 1%.

The risk of a major adverse cardiac event postoperatively was much more dependent on the timing of stent placement in complex and inpatient surgeries. For outpatient surgeries, the risk of a major cardiac event was very low and the timing of stent placement did not matter.

A Danish observational study³² compared more than 4,000 patients with drug-eluting stents having surgery to more than 20,000 matched controls without coronary heart disease having similar surgery. The risk of myocardial infarction or cardiac death was much higher for patients undergoing surgery within 1 month after drug-eluting stent placement compared with controls without heart disease and patients with stent placement longer than 1 month before surgery.

Our practice is to continue aspirin for surgery in patients with coronary stents regardless of the timing of placement. Although there is a small increased risk of bleeding, this must be balanced against thrombotic risk. We typically stop clopidogrel 5 to 7 days before surgery and ticagrelor 3 to 5 days before surgery. We may decide to give platelets before very-high-risk surgery (eg, intracranial, spinal) if there is a decision to continue both antiplatelet drugs—for example, in a patient who recently received a drug-eluting stent (ie, within 3 months). It is essential to involve the cardiologist and surgeon in these decisions.

BOTTOM LINE

This article reviews recommendations and evidence concerning current anticoagulant management for venous thromboembolism and perioperative care, with an emphasis on individualizing treatment for real-world patients.

TREATING ACUTE VENOUS THROMBOEMBOLISM

Case 1: Deep vein thrombosis in an otherwise healthy man

A 40-year-old man presents with 7 days of progressive right leg swelling. He has no antecedent risk factors for deep vein thrombosis or other medical problems. Venous ultrasonography reveals an iliofemoral deep vein thrombosis. How should he be managed?

• Outpatient treatment with low-molecular-weight heparin for 4 to 6 days plus warfarin
• Outpatient treatment with a direct oral anticoagulant, ie, apixaban, dabigatran (which requires 4 to 6 days of initial treatment with low-molecular-weight heparin), or rivaroxaban
• Catheter-directed thrombolysis followed by low-molecular-weight heparin, then warfarin or a direct oral anticoagulant
• Inpatient intravenous heparin for 7 to 10 days, then warfarin or a direct oral anticoagulant

All of these are acceptable for managing acute venous thromboembolism, but the clinician’s role is to identify which treatment is most appropriate for an individual patient.

Deep vein thrombosis is not a single condition

Multiple guidelines exist to help decide on a management strategy. Those of the American College of Chest Physicians (ACCP)¹ are used most often.

That said, guidelines are established for “average” patients, so it is important to look beyond guidelines and individualize management. Venous thromboembolism is not a single entity; it has a myriad of clinical presentations that could call for different treatments. Most patients have submassive deep vein thrombosis or pulmonary embolism, which is not limb-threatening nor associated with hemodynamic instability. It can also differ in terms of etiology and can be unprovoked (or idiopathic), cancer-related, catheter-associated, or provoked by surgery or immobility.

Deep vein thrombosis has a wide spectrum of presentations. It can involve the veins of the calf only, or it can involve the femoral and iliac veins and other locations including the splanchnic veins, the cerebral sinuses, and upper extremities. Pulmonary embolism can be massive (defined as being associated with hemodynamic instability or impending respiratory failure) or submassive. Similarly, patients differ in terms of baseline medical conditions, mobility, and lifestyle. Anticoagulant management decisions should take all these factors into account.

Consider clot location

Our patient with iliofemoral deep vein thrombosis is best managed differently than a more typical patient with less extensive thrombosis that would involve the popliteal or femoral vein segments, or both. A clot that involves the iliac vein is more likely to lead to postthrombotic chronic pain and swelling as the lack of venous outflow bypass channels to circumvent the clot location creates higher venous pressure within the affected leg. Therefore, for our patient, catheter-directed thrombolysis is an option that should be considered.

Catheter-directed thrombolysis trials

According to the “open-vein hypothesis,” quickly eliminating the thrombus and restoring unobstructed venous flow may mitigate the risk not only of recurrent thrombosis, but also of postthrombotic syndrome, which is often not given much consideration acutely but can cause significant, life-altering chronic disability.

The “valve-integrity hypothesis” is also important; it considers whether lytic therapy may help prevent damage to such valves in an attempt to mitigate the amount of venous hypertension.

Thus, catheter-directed thrombolysis offers theoretical benefits, and recent trials have assessed it against standard anticoagulation treatments.

The CaVenT trial (Catheter-Directed Venous Thrombolysis),² conducted in Norway, randomized 209 patients with midfemoral to iliac deep vein thrombosis to conventional treatment (anticoagulation alone) or anticoagulation plus catheter-directed thrombolysis. At 2 years, postthrombotic syndrome had occurred in 41% of the catheter-directed thrombolysis group compared with 56% of the conventional treatment group (P = .047). At 5 years, the difference widened to 43% vs 71% (P < .01, number needed to treat = 4).³ Despite the superiority of lytic therapy, the incidence of postthrombotic syndrome remained high in patients who received this treatment. 

The ATTRACT trial (Acute Venous Thrombosis: Thrombus Removal With Adjunctive Catheter-Directed Thrombolysis),⁴ a US multicenter, open-label, assessor-blind study, randomized 698 patients with femoral or more-proximal deep vein thrombosis to either standard care (anticoagulant therapy and graduated elastic compression stockings) or standard care plus catheter-directed thrombolysis. In preliminary results presented at the Society of Interventional Radiology meeting in March 2017, although no difference was found in the primary outcome (postthrombotic syndrome at 24 months), catheter-directed thrombolysis for iliofemoral deep vein thrombosis led to a 25% reduction in moderate to severe postthrombotic syndrome.

Although it is too early to draw conclusions before publication of the ATTRACT study, the preliminary results highlight the need to individualize treatment and to be selective about using catheter-directed thrombolysis. The trials provide reassurance that catheter-directed lysis is a reasonable and safe intervention when performed by physicians experienced in the procedure. The risk of major bleeding appears to be low (about 2%) and that for intracranial hemorrhage even lower (< 0.5%).

Catheter-directed thrombolysis is appropriate in some cases

The 2016 ACCP guidelines¹ recommend anticoagulant therapy alone over catheter-directed thrombolysis for patients with acute proximal deep vein thrombosis of the leg. However, it is a grade 2C (weak) recommendation.

They provide no specific recommendation as to the clinical indications for catheter-directed thrombolysis, but identify patients who would be most likely to benefit, ie, those who have: 

• Iliofemoral deep vein thrombosis
• Symptoms for less than 14 days
• Good functional status
• Life expectancy of more than 1 year
• Low risk of bleeding.

Our patient satisfies these criteria, suggesting that catheter-directed thrombolysis is a reasonable option for him. 

Timing is important. Catheter-directed lysis is more likely to be beneficial if used before fibrin deposits form and stiffen the venous valves, causing irreversible damage that leads to postthrombotic syndrome. 

The availability of direct oral anticoagulants has generated interest in defining their therapeutic role in patients with venous thromboembolism.

In a meta-analysis⁵ of major trials comparing direct oral anticoagulants and vitamin K antagonists such as warfarin, no significant difference was found for the risk of recurrent venous thromboembolism or venous thromboembolism-related deaths. However, fewer patients experienced major bleeding with direct oral anticoagulants (relative risk 0.61, P = .002). Although significant, the absolute risk reduction was small; the incidence of major bleeding was 1.1% with direct oral anticoagulants vs 1.8% with vitamin K antagonists.

The main advantage of direct oral anticoagulants is greater convenience for the patient.

WHICH PATIENTS ON WARFARIN NEED BRIDGING PREOPERATIVELY?

Many patients still take warfarin, particularly those with atrial fibrillation, a mechanical heart valve, or venous thromboembolism. In many countries, warfarin remains the dominant anticoagulant for stroke prevention. Whether these patients need heparin during the period of perioperative warfarin interruption is a frequently encountered scenario that, until recently, was controversial. Recent studies have helped to inform the need for heparin bridging in many of these patients.

Case 2: An elderly woman on warfarin facing cancer surgery

A 75-year-old woman weighing 65 kg is scheduled for elective colon resection for incidentally found colon cancer. She is taking warfarin for atrial fibrillation. She also has hypertension and diabetes and had a transient ischemic attack 10 years ago.

One doctor told her she needs to be assessed for heparin bridging, but another told her she does not need bridging.

The default management should be not to bridge patients who have atrial fibrillation, but to consider bridging in selected patients, such as those with recent stroke or transient ischemic attack or a prior thromboembolic event during warfarin interruption. However, decisions about bridging should not be made on the basis of the CHADS₂ score alone. For the patient described here, I would recommend not bridging.

Complex factors contribute to stroke risk

Stroke risk for patients with atrial fibrillation can be quickly estimated with the CHADS₂ score, based on: 

• Congestive heart failure (1 point)
• Hypertension (1 point)
• Age at least 75 (1 point)
• Diabetes (1 point)
• Stroke or transient ischemic attack (2 points).

Our patient has a score of 5, corresponding to an annual adjusted stroke risk of 12.5%. Whether her transient ischemic attack of 10 years ago is comparable in significance to a recent stroke is debatable and highlights a weakness of clinical prediction rules. Moreover, such prediction scores were developed to estimate the long-term risk of stroke if anticoagulants are not given, and they have not been assessed in a perioperative setting where there is short-term interruption of anticoagulants. Also, the perioperative milieu is associated with additional factors not captured in these clinical prediction rules that may affect the risk of stroke.

Thus, the risk of perioperative stroke likely involves the interplay of multiple factors, including the type of surgery the patient is undergoing. Some factors may be mitigated:

• Rebound hypercoagulability after stopping an oral anticoagulant can be prevented by intraoperative blood pressure and volume control
• Elevated biochemical factors (eg, D-dimer, B-type natriuretic peptide, troponin) may be lowered with perioperative aspirin therapy
• Lipid and genetic factors may be mitigated with perioperative statin use.

Can heparin bridging also mitigate the risk?

Bridging in patients with atrial fibrillation

Most patients who are taking warfarin are doing so because of atrial fibrillation, so most evidence about perioperative bridging was developed in such patients.

The BRIDGE trial (Bridging Anticoagulation in Patients Who Require Temporary Interruption of Warfarin Therapy for an Elective Invasive Procedure or Surgery)⁶ was the first randomized controlled trial to compare a bridging and no-bridging strategy for patients with atrial fibrillation who required warfarin interruption for elective surgery. Nearly 2,000 patients were given either low-molecular-weight heparin or placebo starting 3 days before until 24 hours before a procedure, and then for 5 to 10 days afterwards. For all patients, warfarin was stopped 5 days before the procedure and was resumed within 24 hours afterwards.

A no-bridging strategy was noninferior to bridging: the risk of perioperative arterial thromboembolism was 0.4% without bridging vs 0.3% with bridging (P = .01 for noninferiority). In addition, a no-bridging strategy conferred a lower risk of major bleeding than bridging: 1.3% vs 3.2% (relative risk 0.41, P = .005 for superiority).

Although the difference in absolute bleeding risk was small, bleeding rates were lower than those seen outside of clinical trials, as the bridging protocol used in BRIDGE was designed to minimize the risk of bleeding. Also, although only 5% of patients had a CHADS₂ score of 5 or 6, such patients are infrequent in clinical practice, and BRIDGE did include a considerable proportion (17%) of patients with a prior stroke or transient ischemic attack who would be considered at high risk.

Other evidence about heparin bridging is derived from observational studies, more than 10 of which have been conducted. In general, they have found that not bridging is associated with low rates of arterial thromboembolism (< 0.5%) and that bridging is associated with high rates of major bleeding (4%–7%).^7–12

Bridging in patients with a mechanical heart valve

Warfarin is the only anticoagulant option for patients who have a mechanical heart valve. No randomized controlled trials have evaluated the benefits of perioperative bridging vs no bridging in this setting.

Observational (cohort) studies suggest that the risk of perioperative arterial thromboembolism is similar with or without bridging anticoagulation, although most patients studied were bridged and those not bridged were considered at low risk (eg, with a bileaflet aortic valve and no additional risk factors).¹³ However, without stronger evidence from randomized controlled trials, bridging should be the default management for patients with a mechanical heart valve. In our practice, we bridge most patients who have a mechanical heart valve unless they are considered to be at low risk, such as those who have a bileaflet aortic valve.

Even less evidence is available for periprocedural management of patients who have a history of venous thromboembolism. No randomized controlled trials exist evaluating bridging vs no bridging. In 1 cohort study in which more than 90% of patients had had thromboembolism more than 3 months before the procedure, the rate of recurrent venous thromboembolism without bridging was less than 0.5%.¹⁴

It is reasonable to bridge patients who need anticoagulant interruption within 3 months of diagnosis of a deep vein thrombosis or pulmonary embolism, and to consider using a temporary inferior vena cava filter for patients who have had a clot who need treatment interruption during the initial 3 to 4 weeks after diagnosis.

Practice guidelines: Perioperative anticoagulation

Guidance for preoperative and postoperative bridging for patients taking warfarin is summarized in Table 2.

CARDIAC PROCEDURES

For patients facing a procedure to implant an implantable cardioverter-defibrillator (ICD) or pacemaker, a procedure-specific concern is the avoidance of pocket hematoma.

Patients on warfarin: Do not bridge

The BRUISE CONTROL-1 trial (Bridge or Continue Coumadin for Device Surgery Randomized Controlled Trial)¹⁹ randomized patients undergoing pacemaker or ICD implantation to either continued anticoagulation therapy and not bridging (ie, continued warfarin so long as the international normalized ratio was < 3) vs conventional bridging treatment (ie, stopping warfarin and bridging with low-molecular-weight heparin). A clinically significant device-pocket hematoma occurred in 3.5% of the continued-warfarin group vs 16.0% in the heparin-bridging group (P < .001). Thromboembolic complications were rare, and rates did not differ between the 2 groups.

Results of the BRUISE CONTROL-1 trial serve as a caution to at least not be too aggressive with bridging. The study design involved resuming heparin 24 hours after surgery, which is perhaps more aggressive than standard practice. In our practice, we wait at least 24 hours to reinstate heparin after minor surgery, and 48 to 72 hours after surgery with higher bleeding risk.

These results are perhaps not surprising if one considers how carefully surgeons try to control bleeding during surgery for patients taking anticoagulants. For patients who are not on an anticoagulant, small bleeding may be less of a concern during a procedure. When high doses of heparin are introduced soon after surgery, small concerns during surgery may become big problems afterward.

Based on these results, it is reasonable to undertake device implantation without interruption of a vitamin K antagonist such as warfarin.

Patients on direct oral anticoagulants: The jury is still out

The similar BRUISE CONTROL-2 trial is currently under way, comparing interruption vs continuation of dabigatran for patients undergoing cardiac device surgery.

In Europe, surgeons are less concerned than those in the United States about operating while a patient is on anticoagulant therapy. But the safety of this practice is not backed by strong evidence.

Direct oral anticoagulants: Consider pharmacokinetics

Direct oral anticoagulants are potent and fast-acting, with a peak effect 1 to 3 hours after intake. This rapid anticoagulant action is similar to that of bridging with low-molecular-weight heparin, and caution is needed when administering direct oral anticoagulants, especially after major surgery or surgery with a high bleeding risk.

Frost et al²⁰ compared the pharmacokinetics of apixaban (with twice-daily dosing) and rivaroxaban (once-daily dosing) and found that peak anticoagulant activity is faster and higher with rivaroxaban. This is important, because many patients will take their anticoagulant first thing in the morning. Consequently, if patients require any kind of procedure (including dental), they should skip the morning dose of the direct oral anticoagulant to avoid having the procedure done during the peak anticoagulant effect, and they should either not take that day’s dose or defer the dose until the evening after the procedure. 

MANAGING SURGERY FOR PATIENTS ON A DIRECT ORAL ANTICOAGULANT

Case 3: An elderly woman on apixaban facing surgery

Let us imagine that our previous patient takes apixaban instead of warfarin. She is 75 years old, has atrial fibrillation, and is about to undergo elective colon resection for cancer. One doctor advises her to simply stop apixaban for 2 days, while another says she should go off apixaban for 5 days and will need bridging. Which plan is best?

In the perioperative setting, our goal is to interrupt patients’ anticoagulant therapy for the shortest time that results in no residual anticoagulant effect at the time of the procedure. 

They further recommend that if the risk of venous thromboembolism is high, low-molecular-weight heparin bridging should be done while stopping the direct oral anticoagulant, with the heparin discontinued 24 hours before the procedure. This recommendation seems counterintuitive, as it is advising replacing a short-acting anticoagulant with low-molecular-weight heparin, another short-acting anticoagulant.

The guidelines committee was unable to provide strength and grading of their recommendations, as too few well-designed studies are available to support them. The doctor in case 3 who advised stopping apixaban for 5 days and bridging is following the guidelines, but without much evidence to support this strategy.

There are no randomized, controlled trials of bridging vs no bridging in patients taking direct oral anticoagulants. Substudies exist of patients taking these drugs for atrial fibrillation who had treatment interrupted for procedures, but the studies did not randomize bridging vs no bridging, nor were bridging regimens standardized. Three of the four atrial fibrillation trials had a blinded design (warfarin vs direct oral anticoagulants), making perioperative management difficult, as physicians did not know the pharmacokinetics of the drugs their patients were taking.^22–24

We used the database from the Randomized Evaluation of Long-Term Anticoagulation Therapy (RE-LY) trial²² to evaluate bridging in patients taking either warfarin or dabigatran. With an open-label study design (the blinding was only for the 110 mg and 150 mg dabigatran doses), clinicians were aware of whether patients were receiving warfarin or dabigatran, thereby facilitating perioperative management. Among dabigatran-treated patients, those who were bridged had significantly more major bleeding than those not bridged (6.5% vs 1.8%, P < .001), with no difference between the groups for stroke or systemic embolism. Although it is not a randomized controlled trial, it does provide evidence that bridging may not be advisable for patients taking a direct oral anticoagulant.

The 2017 American College of Cardiology guidelines²⁵ conclude that parenteral bridging is not indicated for direct oral anticoagulants. Although this is not based on strong evidence, the guidance appears reasonable according to the evidence at hand.

The 2017 American Heart Association Guidelines¹⁶ recommend a somewhat complex approach based on periprocedural bleeding risk and thromboembolic risk.

How long to interrupt direct oral anticoagulants?

Evidence for this approach comes from a prospective cohort study²⁷ of 541 patients being treated with dabigatran who were having an elective surgery or invasive procedure. Patients received standard perioperative management, with the timing of the last dabigatran dose before the procedure (24 hours, 48 hours, or 96 hours) based on the bleeding risk of surgery and the patient’s creatinine clearance. Dabigatran was resumed 24 to 72 hours after the procedure. No heparin bridging was done. Patients were followed for up to 30 days postoperatively. The results were favorable with few complications: one transient ischemic attack (0.2%), 10 major bleeding episodes (1.8%), and 28 minor bleeding episodes (5.2%).

A subgroup of 181 patients in this study²⁸ had a plasma sample drawn just before surgery, allowing the investigators to assess the level of coagulation factors after dabigatran interruption. Results were as follows:

• 93% had a normal prothrombin time 
• 80% had a normal activated partial thromboplastin time
• 33% had a normal thrombin time
• 81% had a normal dilute thrombin time.

The dilute thrombin time is considered the most reliable test of the anticoagulant effect of dabigatran but is not widely available. The activated partial thromboplastin time can provide a more widely used coagulation test to assess (in a less precise manner) whether there is an anticoagulant effect of dabigatran present, and more sensitive activated partial thromboplastin time assays can be used to better detect any residual dabigatran effect.

Dabigatran levels were also measured. Although 66% of patients had low drug levels just before surgery, the others still had substantial dabigatran on board. The fact that bleeding event rates were so low in this study despite the presence of dabigatran in many patients raises the question of whether having some drug on board is a good predictor of bleeding risk.

An interruption protocol with a longer interruption interval—12 to 14 hours longer than in the previous study (3 days for high-bleed risk procedures, 2 days for low-bleed risk procedures)—brought the activated partial thromboplastin time and dilute thrombin time to normal levels for 100% of patients with the protocol for high-bleeding-risk surgery. This study was based on small numbers and its interruption strategy needs further investigation.²⁹

Case 3 continued

The PAUSE study (NCT02228798), a multicenter, prospective cohort study, is designed to establish a safe, standardized protocol for the perioperative management of patients with atrial fibrillation taking dabigatran, rivaroxaban, or apixaban and will include 3,300 patients.

PATIENTS WITH A CORONARY STENT WHO NEED SURGERY

Case 4: A woman with a stent facing surgery

A 70-year-old woman needs breast cancer resection. She has coronary artery disease and had a drug-eluting stent placed 5 months ago after elective cardiac catheterization. She also has hypertension, obesity, and type 2 diabetes. Her medications include an angiotensin II receptor blocker, hydrochlorothiazide, insulin, and an oral hypoglycemic. She is also taking aspirin 81 mg daily and ticagrelor (a P2Y₁₂ receptor antagonist) 90 mg twice daily.

Her cardiologist is concerned that stopping antiplatelet therapy could trigger acute stent thrombosis, which has a 50% or higher mortality rate.

Should she stop taking aspirin before surgery? What about the ticagrelor?

Evidence concerning aspirin during surgery comes from Perioperative Ischemic Evaluation 2 (POISE-2), a double-blind, randomized controlled trial.³⁰ Patients who had known cardiovascular disease or risk factors for cardiovascular disease and were about to undergo noncardiac surgery were stratified according to whether they had been taking aspirin before the study (patients taking aspirin within 72 hours of the surgery were excluded from randomization). Participants in each group were randomized to take either aspirin or placebo just before surgery. The primary outcome was the combined rate of death or nonfatal myocardial infarction 30 days after randomization.

The study found no differences in the primary end point between the two groups. However, major bleeding occurred significantly more often in the aspirin group (4.6% vs 3.8%, hazard ratio 1.2, 95% confidence interval 1.0–1.5).

Moreover, only 4% of the patients in this trial had a cardiac stent. The trial excluded patients who had had a bare-metal stent placed within 6 weeks or a drug-eluting stent placed within 1 year, so it does not help us answer whether aspirin should be stopped for our current patient.

Is surgery safe for patients with stents?

The safety of undergoing surgery with a stent was investigated in a large US Veterans Administration retrospective cohort study.³¹ More than 20,000 patients with stents who underwent noncardiac surgery within 2 years of stent placement were compared with a control group of more than 41,000 patients with stents who did not undergo surgery. Patients were matched by stent type and cardiac risk factors at the time of stent placement.

The risk of an adverse cardiac event in both the surgical and nonsurgical cohorts was highest in the initial 6 weeks after stent placement and plateaued 6 months after stent placement, when the risk difference between the surgical and nonsurgical groups leveled off to 1%.

The risk of a major adverse cardiac event postoperatively was much more dependent on the timing of stent placement in complex and inpatient surgeries. For outpatient surgeries, the risk of a major cardiac event was very low and the timing of stent placement did not matter.

A Danish observational study³² compared more than 4,000 patients with drug-eluting stents having surgery to more than 20,000 matched controls without coronary heart disease having similar surgery. The risk of myocardial infarction or cardiac death was much higher for patients undergoing surgery within 1 month after drug-eluting stent placement compared with controls without heart disease and patients with stent placement longer than 1 month before surgery.

Our practice is to continue aspirin for surgery in patients with coronary stents regardless of the timing of placement. Although there is a small increased risk of bleeding, this must be balanced against thrombotic risk. We typically stop clopidogrel 5 to 7 days before surgery and ticagrelor 3 to 5 days before surgery. We may decide to give platelets before very-high-risk surgery (eg, intracranial, spinal) if there is a decision to continue both antiplatelet drugs—for example, in a patient who recently received a drug-eluting stent (ie, within 3 months). It is essential to involve the cardiologist and surgeon in these decisions.

BOTTOM LINE

This article reviews recommendations and evidence concerning current anticoagulant management for venous thromboembolism and perioperative care, with an emphasis on individualizing treatment for real-world patients.

TREATING ACUTE VENOUS THROMBOEMBOLISM

Case 1: Deep vein thrombosis in an otherwise healthy man

A 40-year-old man presents with 7 days of progressive right leg swelling. He has no antecedent risk factors for deep vein thrombosis or other medical problems. Venous ultrasonography reveals an iliofemoral deep vein thrombosis. How should he be managed?

• Outpatient treatment with low-molecular-weight heparin for 4 to 6 days plus warfarin
• Outpatient treatment with a direct oral anticoagulant, ie, apixaban, dabigatran (which requires 4 to 6 days of initial treatment with low-molecular-weight heparin), or rivaroxaban
• Catheter-directed thrombolysis followed by low-molecular-weight heparin, then warfarin or a direct oral anticoagulant
• Inpatient intravenous heparin for 7 to 10 days, then warfarin or a direct oral anticoagulant

All of these are acceptable for managing acute venous thromboembolism, but the clinician’s role is to identify which treatment is most appropriate for an individual patient.

Deep vein thrombosis is not a single condition

Multiple guidelines exist to help decide on a management strategy. Those of the American College of Chest Physicians (ACCP)¹ are used most often.

That said, guidelines are established for “average” patients, so it is important to look beyond guidelines and individualize management. Venous thromboembolism is not a single entity; it has a myriad of clinical presentations that could call for different treatments. Most patients have submassive deep vein thrombosis or pulmonary embolism, which is not limb-threatening nor associated with hemodynamic instability. It can also differ in terms of etiology and can be unprovoked (or idiopathic), cancer-related, catheter-associated, or provoked by surgery or immobility.

Deep vein thrombosis has a wide spectrum of presentations. It can involve the veins of the calf only, or it can involve the femoral and iliac veins and other locations including the splanchnic veins, the cerebral sinuses, and upper extremities. Pulmonary embolism can be massive (defined as being associated with hemodynamic instability or impending respiratory failure) or submassive. Similarly, patients differ in terms of baseline medical conditions, mobility, and lifestyle. Anticoagulant management decisions should take all these factors into account.

Consider clot location

Our patient with iliofemoral deep vein thrombosis is best managed differently than a more typical patient with less extensive thrombosis that would involve the popliteal or femoral vein segments, or both. A clot that involves the iliac vein is more likely to lead to postthrombotic chronic pain and swelling as the lack of venous outflow bypass channels to circumvent the clot location creates higher venous pressure within the affected leg. Therefore, for our patient, catheter-directed thrombolysis is an option that should be considered.

Catheter-directed thrombolysis trials

According to the “open-vein hypothesis,” quickly eliminating the thrombus and restoring unobstructed venous flow may mitigate the risk not only of recurrent thrombosis, but also of postthrombotic syndrome, which is often not given much consideration acutely but can cause significant, life-altering chronic disability.

The “valve-integrity hypothesis” is also important; it considers whether lytic therapy may help prevent damage to such valves in an attempt to mitigate the amount of venous hypertension.

Thus, catheter-directed thrombolysis offers theoretical benefits, and recent trials have assessed it against standard anticoagulation treatments.

The CaVenT trial (Catheter-Directed Venous Thrombolysis),² conducted in Norway, randomized 209 patients with midfemoral to iliac deep vein thrombosis to conventional treatment (anticoagulation alone) or anticoagulation plus catheter-directed thrombolysis. At 2 years, postthrombotic syndrome had occurred in 41% of the catheter-directed thrombolysis group compared with 56% of the conventional treatment group (P = .047). At 5 years, the difference widened to 43% vs 71% (P < .01, number needed to treat = 4).³ Despite the superiority of lytic therapy, the incidence of postthrombotic syndrome remained high in patients who received this treatment. 

The ATTRACT trial (Acute Venous Thrombosis: Thrombus Removal With Adjunctive Catheter-Directed Thrombolysis),⁴ a US multicenter, open-label, assessor-blind study, randomized 698 patients with femoral or more-proximal deep vein thrombosis to either standard care (anticoagulant therapy and graduated elastic compression stockings) or standard care plus catheter-directed thrombolysis. In preliminary results presented at the Society of Interventional Radiology meeting in March 2017, although no difference was found in the primary outcome (postthrombotic syndrome at 24 months), catheter-directed thrombolysis for iliofemoral deep vein thrombosis led to a 25% reduction in moderate to severe postthrombotic syndrome.

Although it is too early to draw conclusions before publication of the ATTRACT study, the preliminary results highlight the need to individualize treatment and to be selective about using catheter-directed thrombolysis. The trials provide reassurance that catheter-directed lysis is a reasonable and safe intervention when performed by physicians experienced in the procedure. The risk of major bleeding appears to be low (about 2%) and that for intracranial hemorrhage even lower (< 0.5%).

Catheter-directed thrombolysis is appropriate in some cases

The 2016 ACCP guidelines¹ recommend anticoagulant therapy alone over catheter-directed thrombolysis for patients with acute proximal deep vein thrombosis of the leg. However, it is a grade 2C (weak) recommendation.

They provide no specific recommendation as to the clinical indications for catheter-directed thrombolysis, but identify patients who would be most likely to benefit, ie, those who have: 

• Iliofemoral deep vein thrombosis
• Symptoms for less than 14 days
• Good functional status
• Life expectancy of more than 1 year
• Low risk of bleeding.

Our patient satisfies these criteria, suggesting that catheter-directed thrombolysis is a reasonable option for him. 

Timing is important. Catheter-directed lysis is more likely to be beneficial if used before fibrin deposits form and stiffen the venous valves, causing irreversible damage that leads to postthrombotic syndrome. 

The availability of direct oral anticoagulants has generated interest in defining their therapeutic role in patients with venous thromboembolism.

In a meta-analysis⁵ of major trials comparing direct oral anticoagulants and vitamin K antagonists such as warfarin, no significant difference was found for the risk of recurrent venous thromboembolism or venous thromboembolism-related deaths. However, fewer patients experienced major bleeding with direct oral anticoagulants (relative risk 0.61, P = .002). Although significant, the absolute risk reduction was small; the incidence of major bleeding was 1.1% with direct oral anticoagulants vs 1.8% with vitamin K antagonists.

The main advantage of direct oral anticoagulants is greater convenience for the patient.

WHICH PATIENTS ON WARFARIN NEED BRIDGING PREOPERATIVELY?

Many patients still take warfarin, particularly those with atrial fibrillation, a mechanical heart valve, or venous thromboembolism. In many countries, warfarin remains the dominant anticoagulant for stroke prevention. Whether these patients need heparin during the period of perioperative warfarin interruption is a frequently encountered scenario that, until recently, was controversial. Recent studies have helped to inform the need for heparin bridging in many of these patients.

Case 2: An elderly woman on warfarin facing cancer surgery

A 75-year-old woman weighing 65 kg is scheduled for elective colon resection for incidentally found colon cancer. She is taking warfarin for atrial fibrillation. She also has hypertension and diabetes and had a transient ischemic attack 10 years ago.

One doctor told her she needs to be assessed for heparin bridging, but another told her she does not need bridging.

The default management should be not to bridge patients who have atrial fibrillation, but to consider bridging in selected patients, such as those with recent stroke or transient ischemic attack or a prior thromboembolic event during warfarin interruption. However, decisions about bridging should not be made on the basis of the CHADS₂ score alone. For the patient described here, I would recommend not bridging.

Complex factors contribute to stroke risk

Stroke risk for patients with atrial fibrillation can be quickly estimated with the CHADS₂ score, based on: 

• Congestive heart failure (1 point)
• Hypertension (1 point)
• Age at least 75 (1 point)
• Diabetes (1 point)
• Stroke or transient ischemic attack (2 points).

Our patient has a score of 5, corresponding to an annual adjusted stroke risk of 12.5%. Whether her transient ischemic attack of 10 years ago is comparable in significance to a recent stroke is debatable and highlights a weakness of clinical prediction rules. Moreover, such prediction scores were developed to estimate the long-term risk of stroke if anticoagulants are not given, and they have not been assessed in a perioperative setting where there is short-term interruption of anticoagulants. Also, the perioperative milieu is associated with additional factors not captured in these clinical prediction rules that may affect the risk of stroke.

Thus, the risk of perioperative stroke likely involves the interplay of multiple factors, including the type of surgery the patient is undergoing. Some factors may be mitigated:

• Rebound hypercoagulability after stopping an oral anticoagulant can be prevented by intraoperative blood pressure and volume control
• Elevated biochemical factors (eg, D-dimer, B-type natriuretic peptide, troponin) may be lowered with perioperative aspirin therapy
• Lipid and genetic factors may be mitigated with perioperative statin use.

Can heparin bridging also mitigate the risk?

Bridging in patients with atrial fibrillation

Most patients who are taking warfarin are doing so because of atrial fibrillation, so most evidence about perioperative bridging was developed in such patients.

The BRIDGE trial (Bridging Anticoagulation in Patients Who Require Temporary Interruption of Warfarin Therapy for an Elective Invasive Procedure or Surgery)⁶ was the first randomized controlled trial to compare a bridging and no-bridging strategy for patients with atrial fibrillation who required warfarin interruption for elective surgery. Nearly 2,000 patients were given either low-molecular-weight heparin or placebo starting 3 days before until 24 hours before a procedure, and then for 5 to 10 days afterwards. For all patients, warfarin was stopped 5 days before the procedure and was resumed within 24 hours afterwards.

A no-bridging strategy was noninferior to bridging: the risk of perioperative arterial thromboembolism was 0.4% without bridging vs 0.3% with bridging (P = .01 for noninferiority). In addition, a no-bridging strategy conferred a lower risk of major bleeding than bridging: 1.3% vs 3.2% (relative risk 0.41, P = .005 for superiority).

Although the difference in absolute bleeding risk was small, bleeding rates were lower than those seen outside of clinical trials, as the bridging protocol used in BRIDGE was designed to minimize the risk of bleeding. Also, although only 5% of patients had a CHADS₂ score of 5 or 6, such patients are infrequent in clinical practice, and BRIDGE did include a considerable proportion (17%) of patients with a prior stroke or transient ischemic attack who would be considered at high risk.

Other evidence about heparin bridging is derived from observational studies, more than 10 of which have been conducted. In general, they have found that not bridging is associated with low rates of arterial thromboembolism (< 0.5%) and that bridging is associated with high rates of major bleeding (4%–7%).^7–12

Bridging in patients with a mechanical heart valve

Warfarin is the only anticoagulant option for patients who have a mechanical heart valve. No randomized controlled trials have evaluated the benefits of perioperative bridging vs no bridging in this setting.

Observational (cohort) studies suggest that the risk of perioperative arterial thromboembolism is similar with or without bridging anticoagulation, although most patients studied were bridged and those not bridged were considered at low risk (eg, with a bileaflet aortic valve and no additional risk factors).¹³ However, without stronger evidence from randomized controlled trials, bridging should be the default management for patients with a mechanical heart valve. In our practice, we bridge most patients who have a mechanical heart valve unless they are considered to be at low risk, such as those who have a bileaflet aortic valve.

Even less evidence is available for periprocedural management of patients who have a history of venous thromboembolism. No randomized controlled trials exist evaluating bridging vs no bridging. In 1 cohort study in which more than 90% of patients had had thromboembolism more than 3 months before the procedure, the rate of recurrent venous thromboembolism without bridging was less than 0.5%.¹⁴

It is reasonable to bridge patients who need anticoagulant interruption within 3 months of diagnosis of a deep vein thrombosis or pulmonary embolism, and to consider using a temporary inferior vena cava filter for patients who have had a clot who need treatment interruption during the initial 3 to 4 weeks after diagnosis.

Practice guidelines: Perioperative anticoagulation

Guidance for preoperative and postoperative bridging for patients taking warfarin is summarized in Table 2.

CARDIAC PROCEDURES

For patients facing a procedure to implant an implantable cardioverter-defibrillator (ICD) or pacemaker, a procedure-specific concern is the avoidance of pocket hematoma.

Patients on warfarin: Do not bridge

The BRUISE CONTROL-1 trial (Bridge or Continue Coumadin for Device Surgery Randomized Controlled Trial)¹⁹ randomized patients undergoing pacemaker or ICD implantation to either continued anticoagulation therapy and not bridging (ie, continued warfarin so long as the international normalized ratio was < 3) vs conventional bridging treatment (ie, stopping warfarin and bridging with low-molecular-weight heparin). A clinically significant device-pocket hematoma occurred in 3.5% of the continued-warfarin group vs 16.0% in the heparin-bridging group (P < .001). Thromboembolic complications were rare, and rates did not differ between the 2 groups.

Results of the BRUISE CONTROL-1 trial serve as a caution to at least not be too aggressive with bridging. The study design involved resuming heparin 24 hours after surgery, which is perhaps more aggressive than standard practice. In our practice, we wait at least 24 hours to reinstate heparin after minor surgery, and 48 to 72 hours after surgery with higher bleeding risk.

These results are perhaps not surprising if one considers how carefully surgeons try to control bleeding during surgery for patients taking anticoagulants. For patients who are not on an anticoagulant, small bleeding may be less of a concern during a procedure. When high doses of heparin are introduced soon after surgery, small concerns during surgery may become big problems afterward.

Based on these results, it is reasonable to undertake device implantation without interruption of a vitamin K antagonist such as warfarin.

Patients on direct oral anticoagulants: The jury is still out

The similar BRUISE CONTROL-2 trial is currently under way, comparing interruption vs continuation of dabigatran for patients undergoing cardiac device surgery.

In Europe, surgeons are less concerned than those in the United States about operating while a patient is on anticoagulant therapy. But the safety of this practice is not backed by strong evidence.

Direct oral anticoagulants: Consider pharmacokinetics

Direct oral anticoagulants are potent and fast-acting, with a peak effect 1 to 3 hours after intake. This rapid anticoagulant action is similar to that of bridging with low-molecular-weight heparin, and caution is needed when administering direct oral anticoagulants, especially after major surgery or surgery with a high bleeding risk.

Frost et al²⁰ compared the pharmacokinetics of apixaban (with twice-daily dosing) and rivaroxaban (once-daily dosing) and found that peak anticoagulant activity is faster and higher with rivaroxaban. This is important, because many patients will take their anticoagulant first thing in the morning. Consequently, if patients require any kind of procedure (including dental), they should skip the morning dose of the direct oral anticoagulant to avoid having the procedure done during the peak anticoagulant effect, and they should either not take that day’s dose or defer the dose until the evening after the procedure. 

MANAGING SURGERY FOR PATIENTS ON A DIRECT ORAL ANTICOAGULANT

Case 3: An elderly woman on apixaban facing surgery

Let us imagine that our previous patient takes apixaban instead of warfarin. She is 75 years old, has atrial fibrillation, and is about to undergo elective colon resection for cancer. One doctor advises her to simply stop apixaban for 2 days, while another says she should go off apixaban for 5 days and will need bridging. Which plan is best?

In the perioperative setting, our goal is to interrupt patients’ anticoagulant therapy for the shortest time that results in no residual anticoagulant effect at the time of the procedure. 

They further recommend that if the risk of venous thromboembolism is high, low-molecular-weight heparin bridging should be done while stopping the direct oral anticoagulant, with the heparin discontinued 24 hours before the procedure. This recommendation seems counterintuitive, as it is advising replacing a short-acting anticoagulant with low-molecular-weight heparin, another short-acting anticoagulant.

The guidelines committee was unable to provide strength and grading of their recommendations, as too few well-designed studies are available to support them. The doctor in case 3 who advised stopping apixaban for 5 days and bridging is following the guidelines, but without much evidence to support this strategy.

There are no randomized, controlled trials of bridging vs no bridging in patients taking direct oral anticoagulants. Substudies exist of patients taking these drugs for atrial fibrillation who had treatment interrupted for procedures, but the studies did not randomize bridging vs no bridging, nor were bridging regimens standardized. Three of the four atrial fibrillation trials had a blinded design (warfarin vs direct oral anticoagulants), making perioperative management difficult, as physicians did not know the pharmacokinetics of the drugs their patients were taking.^22–24

We used the database from the Randomized Evaluation of Long-Term Anticoagulation Therapy (RE-LY) trial²² to evaluate bridging in patients taking either warfarin or dabigatran. With an open-label study design (the blinding was only for the 110 mg and 150 mg dabigatran doses), clinicians were aware of whether patients were receiving warfarin or dabigatran, thereby facilitating perioperative management. Among dabigatran-treated patients, those who were bridged had significantly more major bleeding than those not bridged (6.5% vs 1.8%, P < .001), with no difference between the groups for stroke or systemic embolism. Although it is not a randomized controlled trial, it does provide evidence that bridging may not be advisable for patients taking a direct oral anticoagulant.

The 2017 American College of Cardiology guidelines²⁵ conclude that parenteral bridging is not indicated for direct oral anticoagulants. Although this is not based on strong evidence, the guidance appears reasonable according to the evidence at hand.

The 2017 American Heart Association Guidelines¹⁶ recommend a somewhat complex approach based on periprocedural bleeding risk and thromboembolic risk.

How long to interrupt direct oral anticoagulants?

Evidence for this approach comes from a prospective cohort study²⁷ of 541 patients being treated with dabigatran who were having an elective surgery or invasive procedure. Patients received standard perioperative management, with the timing of the last dabigatran dose before the procedure (24 hours, 48 hours, or 96 hours) based on the bleeding risk of surgery and the patient’s creatinine clearance. Dabigatran was resumed 24 to 72 hours after the procedure. No heparin bridging was done. Patients were followed for up to 30 days postoperatively. The results were favorable with few complications: one transient ischemic attack (0.2%), 10 major bleeding episodes (1.8%), and 28 minor bleeding episodes (5.2%).

A subgroup of 181 patients in this study²⁸ had a plasma sample drawn just before surgery, allowing the investigators to assess the level of coagulation factors after dabigatran interruption. Results were as follows:

• 93% had a normal prothrombin time 
• 80% had a normal activated partial thromboplastin time
• 33% had a normal thrombin time
• 81% had a normal dilute thrombin time.

The dilute thrombin time is considered the most reliable test of the anticoagulant effect of dabigatran but is not widely available. The activated partial thromboplastin time can provide a more widely used coagulation test to assess (in a less precise manner) whether there is an anticoagulant effect of dabigatran present, and more sensitive activated partial thromboplastin time assays can be used to better detect any residual dabigatran effect.

Dabigatran levels were also measured. Although 66% of patients had low drug levels just before surgery, the others still had substantial dabigatran on board. The fact that bleeding event rates were so low in this study despite the presence of dabigatran in many patients raises the question of whether having some drug on board is a good predictor of bleeding risk.

An interruption protocol with a longer interruption interval—12 to 14 hours longer than in the previous study (3 days for high-bleed risk procedures, 2 days for low-bleed risk procedures)—brought the activated partial thromboplastin time and dilute thrombin time to normal levels for 100% of patients with the protocol for high-bleeding-risk surgery. This study was based on small numbers and its interruption strategy needs further investigation.²⁹

Case 3 continued

The PAUSE study (NCT02228798), a multicenter, prospective cohort study, is designed to establish a safe, standardized protocol for the perioperative management of patients with atrial fibrillation taking dabigatran, rivaroxaban, or apixaban and will include 3,300 patients.

PATIENTS WITH A CORONARY STENT WHO NEED SURGERY

Case 4: A woman with a stent facing surgery

A 70-year-old woman needs breast cancer resection. She has coronary artery disease and had a drug-eluting stent placed 5 months ago after elective cardiac catheterization. She also has hypertension, obesity, and type 2 diabetes. Her medications include an angiotensin II receptor blocker, hydrochlorothiazide, insulin, and an oral hypoglycemic. She is also taking aspirin 81 mg daily and ticagrelor (a P2Y₁₂ receptor antagonist) 90 mg twice daily.

Her cardiologist is concerned that stopping antiplatelet therapy could trigger acute stent thrombosis, which has a 50% or higher mortality rate.

Should she stop taking aspirin before surgery? What about the ticagrelor?

Evidence concerning aspirin during surgery comes from Perioperative Ischemic Evaluation 2 (POISE-2), a double-blind, randomized controlled trial.³⁰ Patients who had known cardiovascular disease or risk factors for cardiovascular disease and were about to undergo noncardiac surgery were stratified according to whether they had been taking aspirin before the study (patients taking aspirin within 72 hours of the surgery were excluded from randomization). Participants in each group were randomized to take either aspirin or placebo just before surgery. The primary outcome was the combined rate of death or nonfatal myocardial infarction 30 days after randomization.

The study found no differences in the primary end point between the two groups. However, major bleeding occurred significantly more often in the aspirin group (4.6% vs 3.8%, hazard ratio 1.2, 95% confidence interval 1.0–1.5).

Moreover, only 4% of the patients in this trial had a cardiac stent. The trial excluded patients who had had a bare-metal stent placed within 6 weeks or a drug-eluting stent placed within 1 year, so it does not help us answer whether aspirin should be stopped for our current patient.

Is surgery safe for patients with stents?

The safety of undergoing surgery with a stent was investigated in a large US Veterans Administration retrospective cohort study.³¹ More than 20,000 patients with stents who underwent noncardiac surgery within 2 years of stent placement were compared with a control group of more than 41,000 patients with stents who did not undergo surgery. Patients were matched by stent type and cardiac risk factors at the time of stent placement.

The risk of an adverse cardiac event in both the surgical and nonsurgical cohorts was highest in the initial 6 weeks after stent placement and plateaued 6 months after stent placement, when the risk difference between the surgical and nonsurgical groups leveled off to 1%.

The risk of a major adverse cardiac event postoperatively was much more dependent on the timing of stent placement in complex and inpatient surgeries. For outpatient surgeries, the risk of a major cardiac event was very low and the timing of stent placement did not matter.

A Danish observational study³² compared more than 4,000 patients with drug-eluting stents having surgery to more than 20,000 matched controls without coronary heart disease having similar surgery. The risk of myocardial infarction or cardiac death was much higher for patients undergoing surgery within 1 month after drug-eluting stent placement compared with controls without heart disease and patients with stent placement longer than 1 month before surgery.

Our practice is to continue aspirin for surgery in patients with coronary stents regardless of the timing of placement. Although there is a small increased risk of bleeding, this must be balanced against thrombotic risk. We typically stop clopidogrel 5 to 7 days before surgery and ticagrelor 3 to 5 days before surgery. We may decide to give platelets before very-high-risk surgery (eg, intracranial, spinal) if there is a decision to continue both antiplatelet drugs—for example, in a patient who recently received a drug-eluting stent (ie, within 3 months). It is essential to involve the cardiologist and surgeon in these decisions.

BOTTOM LINE

Performance of 6 bedside procedures (paracentesis, thoracentesis, lumbar puncture, arthrocentesis, central venous catheter [CVC] placement, and arterial line placement) are considered core competencies for hospitalists.¹ Yet, the American Board of Internal Medicine (ABIM) no longer requires demonstration of manual competency for bedside procedures, and graduates may enter the workforce with minimal or no experience performing such procedures.² As such, the burden falls on hospital privileging committees to ensure providers have the necessary training and experience to competently perform invasive procedures before granting institutional privileges to perform them.³ Although recommendations for privileging to perform certain surgical procedures have been proposed,^4,5 there are no widely accepted guidelines for initial or ongoing privileging of common invasive bedside procedures performed by hospitalists, and current privileging practices vary significantly.

In 2015, the Society of Hospital Medicine (SHM) set up a Point-of-Care Ultrasound (POCUS) Task Force to draft evidence-based guidelines on the use of ultrasound to perform bedside procedures. The recommendations for certification of competency in ultrasound-guided procedures may guide institutional privileging. The purpose of this study was to better understand current hospital privileging practices for invasive bedside procedures both with and without ultrasound guidance and how current practices are perceived by experts.

Study Design, Setting, and Participants

After approval by the University of Texas Health Science Center at San Antonio Institutional Review Board, we conducted a survey of hospital privileging processes for bedside procedures from a convenience sample of hospitalist procedure experts on the SHM POCUS Task Force. All 21 hospitalists on the task force were invited to participate, including the authors of this article. These hospitalists represent 21 unique institutions, and all have clinical, educational, and/or research expertise in ultrasound-guided bedside procedures.

Survey Design

A 26-question, electronic survey on privileging for bedside procedures was conducted (Appendix A). Twenty questions addressed procedures in general, such as minimum numbers of procedures required and use of simulation. Six questions focused on the use of ultrasound guidance. To provide context, many questions were framed to assess a privileging process being drafted by the task force. Answers were either multiple choice or free text.

Data Collection and Analysis

All members of the task force were invited to complete the survey by e-mail during November 2016. A reminder e-mail was sent on the day after initial distribution. No compensation was offered, and participation was not required. Survey results were compiled electronically through Research Electronic Data Capture, or “REDCap”^TM (Nashville, Tennessee), and data analysis was performed with Stata version 14 (College Station, Texas). Means of current and recommended minimum thresholds were calculated by excluding responses of “I don’t know,” and responses of “no minimum number threshold” were coded as 0.

The survey response rate was 100% (21 of 21). All experts were hospitalists, but 2 also identified themselves as intensivists. Experts practiced in a variety of hospital settings, including private university hospitals (43%), public university hospitals (19%), Veterans Affairs teaching hospitals (14%), community teaching hospitals (14%), and community nonteaching hospitals (10%). Most hospitals (90%) were teaching hospitals for internal medicine trainees. All experts have personally performed bedside procedures on a regular basis, and most (86%) had leadership roles in teaching procedures to students, residents, fellows, physician assistants, nurse practitioners, and/or physicians. Approximately half (57%) were involved in granting privileges for bedside procedures at their institutions.

Our survey identified 3 distinct differences between hospitalist procedure experts’ recommendations and their own hospitals’ current privileging practices. First, whereas experts recommended ultrasound guidance for thoracentesis, paracentesis, and CVC placement, it is rarely a current requirement. Second, experts recommend requiring minimum numbers of procedures for both initial and ongoing privileging even though such minimums are not currently required at half of their hospitals. Third, recommended minimum numbers were generally higher than those currently in place.

The routine use of ultrasound guidance for thoracentesis, paracentesis, and CVC placement is likely a result of increased adoption based on the literature showing clinical benefits.^6-9 Thus, the expert recommendations for required use of ultrasound guidance for these procedures seems both appropriate and feasible. The procedure minimums identified in our study are similar to prior ABIM guidelines when manual competency was required for board certification in internal medicine and are comparable to recent minimums proposed by the Society of Critical Care Medicine, both of which recommended a minimum of 5 to 10 per procedure.^10,11 Nevertheless, no commonly agreed-upon minimum number of procedures currently exists for certification of competency, and the variability seen in the experts’ responses further supports the idea that no specific number will guarantee competence. Thus, while requiring minimum numbers of procedures was generally considered necessary by our experts, minimums alone were also considered insufficient for initial privileging because most recommended that direct observation and simulation should be part of an initial privileging process.

These findings encourage more rigorous requirements for both initial and ongoing privileging of procedures. Nevertheless, our findings were rarely unanimous. The most frequently cited reason for disagreement on our findings was feasibility and capacity for direct observation, and the absence of ultrasound equipment or simulators, particularly in resource-limited clinical environments.

Our study has several strengths and limitations. One strength is the recruitment of study experts specifically composed of hospitalist procedure experts from diverse geographic and hospital settings. Yet, we acknowledge that our findings may not be generalizable to other specialties. Another strength is we obtained 100% participation from the experts surveyed. Weaknesses of this study include the relatively small number of experts who are likely to be biased in favor of both the use of ultrasound guidance and higher standards for privileging. We also relied on self-reported data about privileging processes rather than direct observation of those practices. Finally, questions were framed in the context of only 1 possible privileging pathway, and experts may respond differently to a different framing.

Our findings may guide the development of more standardized frameworks for initial and ongoing privileging of hospitalists for invasive bedside procedures. In particular, additional privileging requirements may include the routine use of ultrasound guidance for paracentesis, thoracentesis, and CVC insertion; simulation preceding direct observation of manual skills if possible; and higher required minimums of procedures for both initial and ongoing privileging. The goal of a standardized framework for privileging should be directed at improving the quality and safety of bedside procedures but must consider feasibility in diverse clinical settings where hospitalists work.

Acknowledgments

The authors thank the hospitalists on the SHM POCUS Task Force who provided data about their institutions’ privileging processes and requirements. They are also grateful to Loretta M. Grikis, MLS, AHIP, at the White River Junction Veterans Affairs Medical Center for her assistance as a medical librarian.

Disclosure

Brian P. Lucas (U.S. Department of Veterans Affairs, Veterans Health Administration, Office of Research and Development, Dartmouth SYNERGY, and the National Institutes of Health National Center for Advancing Translational Sciences [UL1TR001086]). Nilam Soni (U.S. Department of Veterans Affairs and Quality Enhancement Research Initiative Partnered Evaluation Initiative grant [HX002263-01A1]). The contents of this publication do not represent the views of the U.S. Department of Veterans Affairs or the U.S. Government.

Performance of 6 bedside procedures (paracentesis, thoracentesis, lumbar puncture, arthrocentesis, central venous catheter [CVC] placement, and arterial line placement) are considered core competencies for hospitalists.¹ Yet, the American Board of Internal Medicine (ABIM) no longer requires demonstration of manual competency for bedside procedures, and graduates may enter the workforce with minimal or no experience performing such procedures.² As such, the burden falls on hospital privileging committees to ensure providers have the necessary training and experience to competently perform invasive procedures before granting institutional privileges to perform them.³ Although recommendations for privileging to perform certain surgical procedures have been proposed,^4,5 there are no widely accepted guidelines for initial or ongoing privileging of common invasive bedside procedures performed by hospitalists, and current privileging practices vary significantly.

In 2015, the Society of Hospital Medicine (SHM) set up a Point-of-Care Ultrasound (POCUS) Task Force to draft evidence-based guidelines on the use of ultrasound to perform bedside procedures. The recommendations for certification of competency in ultrasound-guided procedures may guide institutional privileging. The purpose of this study was to better understand current hospital privileging practices for invasive bedside procedures both with and without ultrasound guidance and how current practices are perceived by experts.

Study Design, Setting, and Participants

After approval by the University of Texas Health Science Center at San Antonio Institutional Review Board, we conducted a survey of hospital privileging processes for bedside procedures from a convenience sample of hospitalist procedure experts on the SHM POCUS Task Force. All 21 hospitalists on the task force were invited to participate, including the authors of this article. These hospitalists represent 21 unique institutions, and all have clinical, educational, and/or research expertise in ultrasound-guided bedside procedures.

Survey Design

A 26-question, electronic survey on privileging for bedside procedures was conducted (Appendix A). Twenty questions addressed procedures in general, such as minimum numbers of procedures required and use of simulation. Six questions focused on the use of ultrasound guidance. To provide context, many questions were framed to assess a privileging process being drafted by the task force. Answers were either multiple choice or free text.

Data Collection and Analysis

All members of the task force were invited to complete the survey by e-mail during November 2016. A reminder e-mail was sent on the day after initial distribution. No compensation was offered, and participation was not required. Survey results were compiled electronically through Research Electronic Data Capture, or “REDCap”^TM (Nashville, Tennessee), and data analysis was performed with Stata version 14 (College Station, Texas). Means of current and recommended minimum thresholds were calculated by excluding responses of “I don’t know,” and responses of “no minimum number threshold” were coded as 0.

The survey response rate was 100% (21 of 21). All experts were hospitalists, but 2 also identified themselves as intensivists. Experts practiced in a variety of hospital settings, including private university hospitals (43%), public university hospitals (19%), Veterans Affairs teaching hospitals (14%), community teaching hospitals (14%), and community nonteaching hospitals (10%). Most hospitals (90%) were teaching hospitals for internal medicine trainees. All experts have personally performed bedside procedures on a regular basis, and most (86%) had leadership roles in teaching procedures to students, residents, fellows, physician assistants, nurse practitioners, and/or physicians. Approximately half (57%) were involved in granting privileges for bedside procedures at their institutions.

Our survey identified 3 distinct differences between hospitalist procedure experts’ recommendations and their own hospitals’ current privileging practices. First, whereas experts recommended ultrasound guidance for thoracentesis, paracentesis, and CVC placement, it is rarely a current requirement. Second, experts recommend requiring minimum numbers of procedures for both initial and ongoing privileging even though such minimums are not currently required at half of their hospitals. Third, recommended minimum numbers were generally higher than those currently in place.

The routine use of ultrasound guidance for thoracentesis, paracentesis, and CVC placement is likely a result of increased adoption based on the literature showing clinical benefits.^6-9 Thus, the expert recommendations for required use of ultrasound guidance for these procedures seems both appropriate and feasible. The procedure minimums identified in our study are similar to prior ABIM guidelines when manual competency was required for board certification in internal medicine and are comparable to recent minimums proposed by the Society of Critical Care Medicine, both of which recommended a minimum of 5 to 10 per procedure.^10,11 Nevertheless, no commonly agreed-upon minimum number of procedures currently exists for certification of competency, and the variability seen in the experts’ responses further supports the idea that no specific number will guarantee competence. Thus, while requiring minimum numbers of procedures was generally considered necessary by our experts, minimums alone were also considered insufficient for initial privileging because most recommended that direct observation and simulation should be part of an initial privileging process.

These findings encourage more rigorous requirements for both initial and ongoing privileging of procedures. Nevertheless, our findings were rarely unanimous. The most frequently cited reason for disagreement on our findings was feasibility and capacity for direct observation, and the absence of ultrasound equipment or simulators, particularly in resource-limited clinical environments.

Our study has several strengths and limitations. One strength is the recruitment of study experts specifically composed of hospitalist procedure experts from diverse geographic and hospital settings. Yet, we acknowledge that our findings may not be generalizable to other specialties. Another strength is we obtained 100% participation from the experts surveyed. Weaknesses of this study include the relatively small number of experts who are likely to be biased in favor of both the use of ultrasound guidance and higher standards for privileging. We also relied on self-reported data about privileging processes rather than direct observation of those practices. Finally, questions were framed in the context of only 1 possible privileging pathway, and experts may respond differently to a different framing.

Our findings may guide the development of more standardized frameworks for initial and ongoing privileging of hospitalists for invasive bedside procedures. In particular, additional privileging requirements may include the routine use of ultrasound guidance for paracentesis, thoracentesis, and CVC insertion; simulation preceding direct observation of manual skills if possible; and higher required minimums of procedures for both initial and ongoing privileging. The goal of a standardized framework for privileging should be directed at improving the quality and safety of bedside procedures but must consider feasibility in diverse clinical settings where hospitalists work.

Acknowledgments

The authors thank the hospitalists on the SHM POCUS Task Force who provided data about their institutions’ privileging processes and requirements. They are also grateful to Loretta M. Grikis, MLS, AHIP, at the White River Junction Veterans Affairs Medical Center for her assistance as a medical librarian.

Disclosure

Brian P. Lucas (U.S. Department of Veterans Affairs, Veterans Health Administration, Office of Research and Development, Dartmouth SYNERGY, and the National Institutes of Health National Center for Advancing Translational Sciences [UL1TR001086]). Nilam Soni (U.S. Department of Veterans Affairs and Quality Enhancement Research Initiative Partnered Evaluation Initiative grant [HX002263-01A1]). The contents of this publication do not represent the views of the U.S. Department of Veterans Affairs or the U.S. Government.

Performance of 6 bedside procedures (paracentesis, thoracentesis, lumbar puncture, arthrocentesis, central venous catheter [CVC] placement, and arterial line placement) are considered core competencies for hospitalists.¹ Yet, the American Board of Internal Medicine (ABIM) no longer requires demonstration of manual competency for bedside procedures, and graduates may enter the workforce with minimal or no experience performing such procedures.² As such, the burden falls on hospital privileging committees to ensure providers have the necessary training and experience to competently perform invasive procedures before granting institutional privileges to perform them.³ Although recommendations for privileging to perform certain surgical procedures have been proposed,^4,5 there are no widely accepted guidelines for initial or ongoing privileging of common invasive bedside procedures performed by hospitalists, and current privileging practices vary significantly.

In 2015, the Society of Hospital Medicine (SHM) set up a Point-of-Care Ultrasound (POCUS) Task Force to draft evidence-based guidelines on the use of ultrasound to perform bedside procedures. The recommendations for certification of competency in ultrasound-guided procedures may guide institutional privileging. The purpose of this study was to better understand current hospital privileging practices for invasive bedside procedures both with and without ultrasound guidance and how current practices are perceived by experts.

Study Design, Setting, and Participants

After approval by the University of Texas Health Science Center at San Antonio Institutional Review Board, we conducted a survey of hospital privileging processes for bedside procedures from a convenience sample of hospitalist procedure experts on the SHM POCUS Task Force. All 21 hospitalists on the task force were invited to participate, including the authors of this article. These hospitalists represent 21 unique institutions, and all have clinical, educational, and/or research expertise in ultrasound-guided bedside procedures.

Survey Design

A 26-question, electronic survey on privileging for bedside procedures was conducted (Appendix A). Twenty questions addressed procedures in general, such as minimum numbers of procedures required and use of simulation. Six questions focused on the use of ultrasound guidance. To provide context, many questions were framed to assess a privileging process being drafted by the task force. Answers were either multiple choice or free text.

Data Collection and Analysis

All members of the task force were invited to complete the survey by e-mail during November 2016. A reminder e-mail was sent on the day after initial distribution. No compensation was offered, and participation was not required. Survey results were compiled electronically through Research Electronic Data Capture, or “REDCap”^TM (Nashville, Tennessee), and data analysis was performed with Stata version 14 (College Station, Texas). Means of current and recommended minimum thresholds were calculated by excluding responses of “I don’t know,” and responses of “no minimum number threshold” were coded as 0.

The survey response rate was 100% (21 of 21). All experts were hospitalists, but 2 also identified themselves as intensivists. Experts practiced in a variety of hospital settings, including private university hospitals (43%), public university hospitals (19%), Veterans Affairs teaching hospitals (14%), community teaching hospitals (14%), and community nonteaching hospitals (10%). Most hospitals (90%) were teaching hospitals for internal medicine trainees. All experts have personally performed bedside procedures on a regular basis, and most (86%) had leadership roles in teaching procedures to students, residents, fellows, physician assistants, nurse practitioners, and/or physicians. Approximately half (57%) were involved in granting privileges for bedside procedures at their institutions.

Our survey identified 3 distinct differences between hospitalist procedure experts’ recommendations and their own hospitals’ current privileging practices. First, whereas experts recommended ultrasound guidance for thoracentesis, paracentesis, and CVC placement, it is rarely a current requirement. Second, experts recommend requiring minimum numbers of procedures for both initial and ongoing privileging even though such minimums are not currently required at half of their hospitals. Third, recommended minimum numbers were generally higher than those currently in place.

The routine use of ultrasound guidance for thoracentesis, paracentesis, and CVC placement is likely a result of increased adoption based on the literature showing clinical benefits.^6-9 Thus, the expert recommendations for required use of ultrasound guidance for these procedures seems both appropriate and feasible. The procedure minimums identified in our study are similar to prior ABIM guidelines when manual competency was required for board certification in internal medicine and are comparable to recent minimums proposed by the Society of Critical Care Medicine, both of which recommended a minimum of 5 to 10 per procedure.^10,11 Nevertheless, no commonly agreed-upon minimum number of procedures currently exists for certification of competency, and the variability seen in the experts’ responses further supports the idea that no specific number will guarantee competence. Thus, while requiring minimum numbers of procedures was generally considered necessary by our experts, minimums alone were also considered insufficient for initial privileging because most recommended that direct observation and simulation should be part of an initial privileging process.

These findings encourage more rigorous requirements for both initial and ongoing privileging of procedures. Nevertheless, our findings were rarely unanimous. The most frequently cited reason for disagreement on our findings was feasibility and capacity for direct observation, and the absence of ultrasound equipment or simulators, particularly in resource-limited clinical environments.

Our study has several strengths and limitations. One strength is the recruitment of study experts specifically composed of hospitalist procedure experts from diverse geographic and hospital settings. Yet, we acknowledge that our findings may not be generalizable to other specialties. Another strength is we obtained 100% participation from the experts surveyed. Weaknesses of this study include the relatively small number of experts who are likely to be biased in favor of both the use of ultrasound guidance and higher standards for privileging. We also relied on self-reported data about privileging processes rather than direct observation of those practices. Finally, questions were framed in the context of only 1 possible privileging pathway, and experts may respond differently to a different framing.

Our findings may guide the development of more standardized frameworks for initial and ongoing privileging of hospitalists for invasive bedside procedures. In particular, additional privileging requirements may include the routine use of ultrasound guidance for paracentesis, thoracentesis, and CVC insertion; simulation preceding direct observation of manual skills if possible; and higher required minimums of procedures for both initial and ongoing privileging. The goal of a standardized framework for privileging should be directed at improving the quality and safety of bedside procedures but must consider feasibility in diverse clinical settings where hospitalists work.

Acknowledgments

The authors thank the hospitalists on the SHM POCUS Task Force who provided data about their institutions’ privileging processes and requirements. They are also grateful to Loretta M. Grikis, MLS, AHIP, at the White River Junction Veterans Affairs Medical Center for her assistance as a medical librarian.

Disclosure

Brian P. Lucas (U.S. Department of Veterans Affairs, Veterans Health Administration, Office of Research and Development, Dartmouth SYNERGY, and the National Institutes of Health National Center for Advancing Translational Sciences [UL1TR001086]). Nilam Soni (U.S. Department of Veterans Affairs and Quality Enhancement Research Initiative Partnered Evaluation Initiative grant [HX002263-01A1]). The contents of this publication do not represent the views of the U.S. Department of Veterans Affairs or the U.S. Government.