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Clinical Poster Highlights: Normal Sleep Patterns and a Healthy Skin Barrier in Infants and Children
This educational supplement to Pediatric News was sponsored by Johnson & Johnson Consumer Products Company.
Topic Highlights
- Introduction—Knowledge About Development and Maintenance of Normal Sleep and Healthy Skin in Infants and Children Continues to Evolve
- Sleep and Development in Infants and Toddlers
- Sleep in Young Children: A Cross-Cultural Perspective
- Sleep Education in Pediatric Residency Programs
- The Impact of Young Children’s Sleep on Maternal Sleep
- An iPhone® Application for Infant and Toddler Sleep: Concerns of Users
- Intra- and Interpersonal Changes in the Skin Microbiome from Infancy to Adulthood
- Chymotrypsin-Like Protease Activity in the Stratum Corneum is Increased in Atopic Dermatitis and Upon Washing with Soap
- Avena sativa Extracts in Atopic Eczema: A Two-Month Observational Study in Greece
Faculty/Faculty Disclosures
Paul Horowitz, MD, FAAP
Discovery Pediatrics
Valencia, California
Sherrill J. Rudy, MSN, CRNP
School of Nursing and Health Sciences
Robert Morris University
Pittsburgh, Pennsylvania
Dr. Horowitz discloses that he is a paid consultant and Advisory Board member to Johnson & Johnson Consumer Companies, Inc.
Ms. Rudy discloses that she is a paid consultant to Johnson & Johnson Consumer Companies, Inc.
This educational supplement to Pediatric News was sponsored by Johnson & Johnson Consumer Products Company.
Topic Highlights
- Introduction—Knowledge About Development and Maintenance of Normal Sleep and Healthy Skin in Infants and Children Continues to Evolve
- Sleep and Development in Infants and Toddlers
- Sleep in Young Children: A Cross-Cultural Perspective
- Sleep Education in Pediatric Residency Programs
- The Impact of Young Children’s Sleep on Maternal Sleep
- An iPhone® Application for Infant and Toddler Sleep: Concerns of Users
- Intra- and Interpersonal Changes in the Skin Microbiome from Infancy to Adulthood
- Chymotrypsin-Like Protease Activity in the Stratum Corneum is Increased in Atopic Dermatitis and Upon Washing with Soap
- Avena sativa Extracts in Atopic Eczema: A Two-Month Observational Study in Greece
Faculty/Faculty Disclosures
Paul Horowitz, MD, FAAP
Discovery Pediatrics
Valencia, California
Sherrill J. Rudy, MSN, CRNP
School of Nursing and Health Sciences
Robert Morris University
Pittsburgh, Pennsylvania
Dr. Horowitz discloses that he is a paid consultant and Advisory Board member to Johnson & Johnson Consumer Companies, Inc.
Ms. Rudy discloses that she is a paid consultant to Johnson & Johnson Consumer Companies, Inc.
This educational supplement to Pediatric News was sponsored by Johnson & Johnson Consumer Products Company.
Topic Highlights
- Introduction—Knowledge About Development and Maintenance of Normal Sleep and Healthy Skin in Infants and Children Continues to Evolve
- Sleep and Development in Infants and Toddlers
- Sleep in Young Children: A Cross-Cultural Perspective
- Sleep Education in Pediatric Residency Programs
- The Impact of Young Children’s Sleep on Maternal Sleep
- An iPhone® Application for Infant and Toddler Sleep: Concerns of Users
- Intra- and Interpersonal Changes in the Skin Microbiome from Infancy to Adulthood
- Chymotrypsin-Like Protease Activity in the Stratum Corneum is Increased in Atopic Dermatitis and Upon Washing with Soap
- Avena sativa Extracts in Atopic Eczema: A Two-Month Observational Study in Greece
Faculty/Faculty Disclosures
Paul Horowitz, MD, FAAP
Discovery Pediatrics
Valencia, California
Sherrill J. Rudy, MSN, CRNP
School of Nursing and Health Sciences
Robert Morris University
Pittsburgh, Pennsylvania
Dr. Horowitz discloses that he is a paid consultant and Advisory Board member to Johnson & Johnson Consumer Companies, Inc.
Ms. Rudy discloses that she is a paid consultant to Johnson & Johnson Consumer Companies, Inc.
Dawn of a new era: targeting the B-cell receptor signaling pathway to conquer B-cell lymphomas
Despite the advent of modern chemo- and radioimmunotherapies, the disease course in most mature B-cell malignancies (with the exception of diffuse large B-cell lymphoma [DLBCL] and Burkitt lymphoma) is highlighted by frequent relapses, progressively shorter remissions, and eventual emergence of therapy resistance. An effective salvage therapy in this setting remains an area of unmet medical need. Bruton’s tyrosine kinase (BTK) is a critical component of B-cell–receptor signaling that mediates interactions with the tumor microenvironment and promotes survival and proliferation of malignant B-cells.1,2 The BTK protein itself is a Tec family tyrosine kinase that is activated by spleen tyrosine kinase following B-cell-receptor stimulation and which is then required for downstream events including calcium release, activation of the NFB and NFAT pathways, cell survival and proliferation.1 The fundamental role of BTK in B-cell function is underscored by the human disease X-linked agammaglobulinemia, which is caused by loss of function mutations in BTK.3 These mutations result in the virtual absence of all B cells and immunoglobulins, leading to recurrent bacterial infections. Ibrutinib (formally known as PCI-32765) is the first-in-class BTK inhibitor to enter clinical trials. In a multicenter phase 1 dose-escalating study, 56 patients with relapsed or refractory B-cell lymphomas received escalated doses of oral ibrutinib either on an intermittent or continuous daily dosing schedule.4 The most common adverse effects were grade 1-2 nonhematologic toxicities, which included rash, nausea, fatigue, diarrhea, muscle spasms/myalgia, and arthralgia. An overall response rate (ORR) of 60% was achieved across all histological types with the best efficacy seen in patients with mantle cell lymphoma (MCL; 78%) and chronic lymphocytic leukemia (CLL; 68%).
Click on the PDF icon at the top of this article to read the full article.
Despite the advent of modern chemo- and radioimmunotherapies, the disease course in most mature B-cell malignancies (with the exception of diffuse large B-cell lymphoma [DLBCL] and Burkitt lymphoma) is highlighted by frequent relapses, progressively shorter remissions, and eventual emergence of therapy resistance. An effective salvage therapy in this setting remains an area of unmet medical need. Bruton’s tyrosine kinase (BTK) is a critical component of B-cell–receptor signaling that mediates interactions with the tumor microenvironment and promotes survival and proliferation of malignant B-cells.1,2 The BTK protein itself is a Tec family tyrosine kinase that is activated by spleen tyrosine kinase following B-cell-receptor stimulation and which is then required for downstream events including calcium release, activation of the NFB and NFAT pathways, cell survival and proliferation.1 The fundamental role of BTK in B-cell function is underscored by the human disease X-linked agammaglobulinemia, which is caused by loss of function mutations in BTK.3 These mutations result in the virtual absence of all B cells and immunoglobulins, leading to recurrent bacterial infections. Ibrutinib (formally known as PCI-32765) is the first-in-class BTK inhibitor to enter clinical trials. In a multicenter phase 1 dose-escalating study, 56 patients with relapsed or refractory B-cell lymphomas received escalated doses of oral ibrutinib either on an intermittent or continuous daily dosing schedule.4 The most common adverse effects were grade 1-2 nonhematologic toxicities, which included rash, nausea, fatigue, diarrhea, muscle spasms/myalgia, and arthralgia. An overall response rate (ORR) of 60% was achieved across all histological types with the best efficacy seen in patients with mantle cell lymphoma (MCL; 78%) and chronic lymphocytic leukemia (CLL; 68%).
Click on the PDF icon at the top of this article to read the full article.
Despite the advent of modern chemo- and radioimmunotherapies, the disease course in most mature B-cell malignancies (with the exception of diffuse large B-cell lymphoma [DLBCL] and Burkitt lymphoma) is highlighted by frequent relapses, progressively shorter remissions, and eventual emergence of therapy resistance. An effective salvage therapy in this setting remains an area of unmet medical need. Bruton’s tyrosine kinase (BTK) is a critical component of B-cell–receptor signaling that mediates interactions with the tumor microenvironment and promotes survival and proliferation of malignant B-cells.1,2 The BTK protein itself is a Tec family tyrosine kinase that is activated by spleen tyrosine kinase following B-cell-receptor stimulation and which is then required for downstream events including calcium release, activation of the NFB and NFAT pathways, cell survival and proliferation.1 The fundamental role of BTK in B-cell function is underscored by the human disease X-linked agammaglobulinemia, which is caused by loss of function mutations in BTK.3 These mutations result in the virtual absence of all B cells and immunoglobulins, leading to recurrent bacterial infections. Ibrutinib (formally known as PCI-32765) is the first-in-class BTK inhibitor to enter clinical trials. In a multicenter phase 1 dose-escalating study, 56 patients with relapsed or refractory B-cell lymphomas received escalated doses of oral ibrutinib either on an intermittent or continuous daily dosing schedule.4 The most common adverse effects were grade 1-2 nonhematologic toxicities, which included rash, nausea, fatigue, diarrhea, muscle spasms/myalgia, and arthralgia. An overall response rate (ORR) of 60% was achieved across all histological types with the best efficacy seen in patients with mantle cell lymphoma (MCL; 78%) and chronic lymphocytic leukemia (CLL; 68%).
Click on the PDF icon at the top of this article to read the full article.
Pazopanib shows promise as pediatric sarcoma therapy
Pazopanib was well tolerated and appeared to be of clinical benefit in children with soft tissue sarcoma in a phase I study. Although the findings are preliminary, eight children in the trial achieved stable disease and two achieved a partial response.
"The clinical activity of pazopanib is encouraging in this heavily pretreated pediatric population," said Dr. Julia Glad Bender, of Columbia University Medical Center, New York, and her associates (J. Clin. Oncol. 2013;31:3034-43).
Pazopanib (Votrient) is approved by the Food and Drug Administration as a treatment for adult patients with soft tissue sarcoma and in those with advanced renal cell carcinoma. The drug inhibited cell proliferation, angiogenesis, and possibly tumor growth in pediatric xenografts, prompting the research team to evaluate pazopanib’s therapeutic potential in children.
The multicenter phase I study examined the pharmacokinetic and pharmacodynamic properties of two formulations of pazopanib in children with soft tissue sarcoma or other refractory solid tumors. Overall, 51 children with a median age of 12.9 years and recurrent or refractory solid or primary central nervous system tumors were evaluated in the trial.
For the first component of the trial, the maximum tolerated dose (MTD) of a tablet formulation of pazopanib was determined in 25 children who had a median age of 13.5 years. The starting dose of pazopanib was 275 mg/m2 given every day in 28-day cycles for up to a maximum of 24 cycles. The MTD was found to be 450 mg/m2.
The researchers next determined the MTD of a powder suspension formulation of the drug based on the tablet MTD in 16 children with a median age of 10.5 years. The suspension MTD was found to be 160 mg/m2.
Finally, dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) was used at the start of and after 15 days’ treatment in 10 children with a median age of 17.2 years. All received pazopanib tablets at the MTD of 450 mg/m2. The aim was to see if there was any sign of a change in tumor angiogenesis in response to treatment.
The most common adverse effects seen with pazopanib treatment were gastrointestinal (diarrhea, nausea, and vomiting), fatigue, proteinuria, and hypertension. Grade 3-4 toxicities that limited dosing in the first cycle of treatment included elevations in lipase, amylase and alanine transaminase, proteinuria, and hypertension. There was a single (grade 4) case of intracranial hemorrhage in a child with occult brain metastases.
"Overall toxicity seemed to correlate with exposure rather than dose," the researchers wrote. The bioavailability of pazopanib appeared to be higher with the suspension than with the tablet formulation, so there might be a relationship between higher steady state plasma trough concentrations and the development of hypertension.
"In adults, elevated blood pressure has been suggested as a correlative marker for improved antitumor efficacy of VEGF [vascular endothelial growth factor] pathway inhibitors," the researchers wrote. "Additional studies are warranted to determine whether hypertension can be used to optimize dose or predict clinical benefit in children."
Eight patients in the trial had stable disease for 6 months or more, and seven of those children had soft tissue sarcomas. Partial responses were seen in two children – one with a desmoplastic small round cell tumor and one with a hepatoblastoma. The latter patient had to be removed from the study due to recurrent neutropenia after 12 cycles.
Results of the DCE-MRI analysis showed a decrease in tumor blood volume from a mean of 16% at the start of treatment to 7% at the end of pazopanib treatment (P = .004).
"To our knowledge, this is the first pediatric, multicenter trial to systematically evaluate DCE-MRI in soft tissue sarcoma, demonstrating the feasibility of performing such studies in a clinical trial network," Dr. Bender and team commented.
"Within the imaging stratum, all patients with interpretable studies had a decrease in tumor blood volume and permeability consistent with the antiangiogenic mechanism of pazopanib." Due to the small number of children evaluated, however, it is not possible to correlate the decrease in tumor blood volume with any clinical benefit.
A phase II trial is planned to further determine the pharmacokinetics and pharmacodynamic of pazopanib in children with soft tissue sarcomas and other refractory solid tumors.
The study was supported by grants from the Alex’s Lemonade Stand Foundation, Columbia University, GlaxoSmithKline, and the National Institutes of Health. Dr. Bender has acted as an unpaid advisor to GlaxoSmithKline. The other authors reported no conflicts of interest.
Pazopanib was well tolerated and appeared to be of clinical benefit in children with soft tissue sarcoma in a phase I study. Although the findings are preliminary, eight children in the trial achieved stable disease and two achieved a partial response.
"The clinical activity of pazopanib is encouraging in this heavily pretreated pediatric population," said Dr. Julia Glad Bender, of Columbia University Medical Center, New York, and her associates (J. Clin. Oncol. 2013;31:3034-43).
Pazopanib (Votrient) is approved by the Food and Drug Administration as a treatment for adult patients with soft tissue sarcoma and in those with advanced renal cell carcinoma. The drug inhibited cell proliferation, angiogenesis, and possibly tumor growth in pediatric xenografts, prompting the research team to evaluate pazopanib’s therapeutic potential in children.
The multicenter phase I study examined the pharmacokinetic and pharmacodynamic properties of two formulations of pazopanib in children with soft tissue sarcoma or other refractory solid tumors. Overall, 51 children with a median age of 12.9 years and recurrent or refractory solid or primary central nervous system tumors were evaluated in the trial.
For the first component of the trial, the maximum tolerated dose (MTD) of a tablet formulation of pazopanib was determined in 25 children who had a median age of 13.5 years. The starting dose of pazopanib was 275 mg/m2 given every day in 28-day cycles for up to a maximum of 24 cycles. The MTD was found to be 450 mg/m2.
The researchers next determined the MTD of a powder suspension formulation of the drug based on the tablet MTD in 16 children with a median age of 10.5 years. The suspension MTD was found to be 160 mg/m2.
Finally, dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) was used at the start of and after 15 days’ treatment in 10 children with a median age of 17.2 years. All received pazopanib tablets at the MTD of 450 mg/m2. The aim was to see if there was any sign of a change in tumor angiogenesis in response to treatment.
The most common adverse effects seen with pazopanib treatment were gastrointestinal (diarrhea, nausea, and vomiting), fatigue, proteinuria, and hypertension. Grade 3-4 toxicities that limited dosing in the first cycle of treatment included elevations in lipase, amylase and alanine transaminase, proteinuria, and hypertension. There was a single (grade 4) case of intracranial hemorrhage in a child with occult brain metastases.
"Overall toxicity seemed to correlate with exposure rather than dose," the researchers wrote. The bioavailability of pazopanib appeared to be higher with the suspension than with the tablet formulation, so there might be a relationship between higher steady state plasma trough concentrations and the development of hypertension.
"In adults, elevated blood pressure has been suggested as a correlative marker for improved antitumor efficacy of VEGF [vascular endothelial growth factor] pathway inhibitors," the researchers wrote. "Additional studies are warranted to determine whether hypertension can be used to optimize dose or predict clinical benefit in children."
Eight patients in the trial had stable disease for 6 months or more, and seven of those children had soft tissue sarcomas. Partial responses were seen in two children – one with a desmoplastic small round cell tumor and one with a hepatoblastoma. The latter patient had to be removed from the study due to recurrent neutropenia after 12 cycles.
Results of the DCE-MRI analysis showed a decrease in tumor blood volume from a mean of 16% at the start of treatment to 7% at the end of pazopanib treatment (P = .004).
"To our knowledge, this is the first pediatric, multicenter trial to systematically evaluate DCE-MRI in soft tissue sarcoma, demonstrating the feasibility of performing such studies in a clinical trial network," Dr. Bender and team commented.
"Within the imaging stratum, all patients with interpretable studies had a decrease in tumor blood volume and permeability consistent with the antiangiogenic mechanism of pazopanib." Due to the small number of children evaluated, however, it is not possible to correlate the decrease in tumor blood volume with any clinical benefit.
A phase II trial is planned to further determine the pharmacokinetics and pharmacodynamic of pazopanib in children with soft tissue sarcomas and other refractory solid tumors.
The study was supported by grants from the Alex’s Lemonade Stand Foundation, Columbia University, GlaxoSmithKline, and the National Institutes of Health. Dr. Bender has acted as an unpaid advisor to GlaxoSmithKline. The other authors reported no conflicts of interest.
Pazopanib was well tolerated and appeared to be of clinical benefit in children with soft tissue sarcoma in a phase I study. Although the findings are preliminary, eight children in the trial achieved stable disease and two achieved a partial response.
"The clinical activity of pazopanib is encouraging in this heavily pretreated pediatric population," said Dr. Julia Glad Bender, of Columbia University Medical Center, New York, and her associates (J. Clin. Oncol. 2013;31:3034-43).
Pazopanib (Votrient) is approved by the Food and Drug Administration as a treatment for adult patients with soft tissue sarcoma and in those with advanced renal cell carcinoma. The drug inhibited cell proliferation, angiogenesis, and possibly tumor growth in pediatric xenografts, prompting the research team to evaluate pazopanib’s therapeutic potential in children.
The multicenter phase I study examined the pharmacokinetic and pharmacodynamic properties of two formulations of pazopanib in children with soft tissue sarcoma or other refractory solid tumors. Overall, 51 children with a median age of 12.9 years and recurrent or refractory solid or primary central nervous system tumors were evaluated in the trial.
For the first component of the trial, the maximum tolerated dose (MTD) of a tablet formulation of pazopanib was determined in 25 children who had a median age of 13.5 years. The starting dose of pazopanib was 275 mg/m2 given every day in 28-day cycles for up to a maximum of 24 cycles. The MTD was found to be 450 mg/m2.
The researchers next determined the MTD of a powder suspension formulation of the drug based on the tablet MTD in 16 children with a median age of 10.5 years. The suspension MTD was found to be 160 mg/m2.
Finally, dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) was used at the start of and after 15 days’ treatment in 10 children with a median age of 17.2 years. All received pazopanib tablets at the MTD of 450 mg/m2. The aim was to see if there was any sign of a change in tumor angiogenesis in response to treatment.
The most common adverse effects seen with pazopanib treatment were gastrointestinal (diarrhea, nausea, and vomiting), fatigue, proteinuria, and hypertension. Grade 3-4 toxicities that limited dosing in the first cycle of treatment included elevations in lipase, amylase and alanine transaminase, proteinuria, and hypertension. There was a single (grade 4) case of intracranial hemorrhage in a child with occult brain metastases.
"Overall toxicity seemed to correlate with exposure rather than dose," the researchers wrote. The bioavailability of pazopanib appeared to be higher with the suspension than with the tablet formulation, so there might be a relationship between higher steady state plasma trough concentrations and the development of hypertension.
"In adults, elevated blood pressure has been suggested as a correlative marker for improved antitumor efficacy of VEGF [vascular endothelial growth factor] pathway inhibitors," the researchers wrote. "Additional studies are warranted to determine whether hypertension can be used to optimize dose or predict clinical benefit in children."
Eight patients in the trial had stable disease for 6 months or more, and seven of those children had soft tissue sarcomas. Partial responses were seen in two children – one with a desmoplastic small round cell tumor and one with a hepatoblastoma. The latter patient had to be removed from the study due to recurrent neutropenia after 12 cycles.
Results of the DCE-MRI analysis showed a decrease in tumor blood volume from a mean of 16% at the start of treatment to 7% at the end of pazopanib treatment (P = .004).
"To our knowledge, this is the first pediatric, multicenter trial to systematically evaluate DCE-MRI in soft tissue sarcoma, demonstrating the feasibility of performing such studies in a clinical trial network," Dr. Bender and team commented.
"Within the imaging stratum, all patients with interpretable studies had a decrease in tumor blood volume and permeability consistent with the antiangiogenic mechanism of pazopanib." Due to the small number of children evaluated, however, it is not possible to correlate the decrease in tumor blood volume with any clinical benefit.
A phase II trial is planned to further determine the pharmacokinetics and pharmacodynamic of pazopanib in children with soft tissue sarcomas and other refractory solid tumors.
The study was supported by grants from the Alex’s Lemonade Stand Foundation, Columbia University, GlaxoSmithKline, and the National Institutes of Health. Dr. Bender has acted as an unpaid advisor to GlaxoSmithKline. The other authors reported no conflicts of interest.
FROM THE JOURNAL OF CLINICAL ONCOLOGY
Major finding: Results of the DCE-MRI analysis showed a decrease in tumor blood volume from a mean of 16% at the start of treatment to 7% at the end of pazopanib treatment (P = .004).
Data source: Multicenter phase I pharmacokinetic and pharmacodynamic study of 51 children with soft tissue sarcoma or other refractory solid tumors.
Disclosures: The study was supported by grants from the Alex’s Lemonade Stand Foundation, Columbia University, GlaxoSmithKline, and the National Institutes of Health. Dr. Bender has acted as an unpaid advisor to GlaxoSmithKline. The other authors reported no conflicts of interest.
Study IDs predictors of unplanned hospital readmission after CEA
SAN FRANCISCO – The 30-day unplanned readmission rate following carotid endarterectomy was 6.5% in a single-center study.
In addition, four variables were significantly associated with unplanned readmission: in-hospital postoperative congestive heart failure (CHF) exacerbation; in-hospital postoperative stroke; in-hospital postoperative hematoma; and prior coronary artery bypass graft (CABG).
"Whether these complications are completely avoidable is unknown, but we do identify a group of patients who would probably benefit from more comprehensive discharge planning and careful postdischarge care," Dr. Karen J. Ho said at the Society for Vascular Surgery annual meeting earlier this year.
According to a study of Medicare claims data from 2003 to 2004, 20% of Medicare beneficiaries discharged from a hospital were rehospitalized within 30 days (N. Eng. J. Med. 2009;360:1418-28). The 30-day rehospitalization rate after vascular surgery was 24%, "the highest of all surgical specialties examined in the study," said Dr. Ho of the surgery department at Brigham and Women’s Hospital, Boston, who was not involved with the published study. "Medicare has started to decrease reimbursements for hospitals with excess readmissions after acute MI, heart failure, and pneumonia. Hip and knee replacements and chronic obstructive pulmonary disease will be added in 2014, and we anticipate that additional surgical procedures will be added thereafter," she said.
In an effort to determine the rate of 30-day unplanned readmission after carotid endarterectomy (CEA), Dr. Ho and her associates conducted a retrospective study of a prospectively collected vascular surgery database at Brigham and Women’s Hospital. The cohort included 896 consecutive CEAs performed between 2002 and 2011. Combined CABG/CEA procedures were excluded.
The primary endpoint was unplanned readmission within 30 days, defined as "any unanticipated, nonelective hospital readmission," she said. The secondary endpoint was 1-year survival.
The mean age of the patients was 70 years, 60% were male, and 95% were white. More than half (65%) had asymptomatic evidence of carotid artery disease.
Dr. Ho reported that the median postoperative length of stay was 1 day and that 9.9% of patients had at least one in-hospital complication. The most frequent in-hospital complication was bleeding/hematoma (4.1%), followed by arrhythmia (2.1%), dysphagia (1.7%), stroke (1.3%), and myocardial infarction (1.2%). Only 3% of patients required a reoperation, while most (94%) were discharged to home. The 30-day stroke rate was 1.7%, while the 30-day death rate was 0.6%.
The overall 30-day readmission rate was 8.6%, while the unplanned 30-day readmission rate was 6.5%. "Most of the overall readmissions (80%) occurred in the first 10 days, and the median time to unplanned readmission was 4 days," Dr. Ho said.
The most common reason for an unplanned readmission was a cardiac complication, followed by headache, bleeding/hematoma, stroke/transient ischemic attack/intracerebral hemorrhage, or other medical emergency. More than one-quarter of patients (27.5%) had more than one reason for an unplanned readmission, while 87.9% of patients had a CEA-related unplanned readmission.
When the researchers performed a univariate analysis followed by analysis with a multivariable Cox model for unplanned readmission, four variables were independently associated with unplanned readmission: in-hospital postoperative CHF exacerbation (hazard ratio, 15.1), in-hospital postoperative stroke (HR, 5.0), in-hospital postoperative hematoma (HR, 3.1), and prior CABG (HR, 2.0).
They also observed a significant difference in survival at 1 year between patients who had an unplanned readmission and those who did not (91% vs. 96%, respectively; P less than .01.) "It’s unclear whether these deaths in the unplanned readmission group were preventable or if they were related to carotid disease or to a procedure-related complication," Dr. Ho said. "Our guess is that the increased overall burden of comorbid disease in these patients, rather than the readmission itself, predicted decreased survival."
Limitations of the study included its retrospective design and the fact that it was conducted at a single center, she said, "but we do know that our unplanned readmission rate is comparable to estimates from recent Medicare data."
Dr. Ho said she had no relevant financial disclosures.
Over the past several years, the role of carotid endarterectomy (CEA) for asymptomatic carotid stenosis has, again, come under the microscope; with many proponents still advocating CEA as the treatment of choice for asymptomatic patients with greater than or equal to 60% stenosis, while some propose greater than or equal to 70-80% stenosis in good surgical risk patients. Meanwhile, others oppose this philosophy because of the advances in modern medical therapy for patients with atherosclerosis, in general, with emphasis on risk modification. The findings of this article are quite disturbing, since the authors concluded that the 30-day unplanned re-admission rate after CEA was 6.5%; this is especially surprising to me, coming from this institution.
Dr. AbuRahma |
The authors also concluded that unplanned re-admission rate was influenced by congestive heart failure, in-hospital postoperative stroke, in-hospital postoperative hematoma, and prior coronary artery bypass grafting. This emphasizes the importance of selection, selection, selection for asymptomatic carotid artery stenosis, if the outcome is to be acceptable to those who still advocate carotid endarterectomy for asymptomatic carotid disease.
Perhaps this procedure should not be encouraged for patients with congestive heart failure or those with severe coronary artery disease, unstable angina. Today, Level I evidence still supports carotid endarterectomy for patients with severe carotid artery stenosis, provided the patient is a good surgical risk, with relatively good longevity; with perioperative stroke and/or death rates of less than 3%. Several modern clinical series have concluded that CEA can be done in these patients with a stroke and/or death rate of less than 1-2%, which was produced most recently in the CREST trial. For those clinicians who cannot keep these numbers down, perhaps this procedure should not be done for asymptomatic carotid disease. What’s also surprising to me, is the in-hospital postoperative hematomas, which I presume necessitated the re-admission and, perhaps, reoperation. This should highlight the fact that, perhaps, we need to look further as to whether or not these patients should be on a combined regimen of aspirin and Plavix, preoperatively and postoperatively, as prescribed by many clinicians.
There is no Level I evidence to support that the combination of aspirin and Plavix, postoperatvely, for these patients would yield a better outcome than simple aspirin daily. It is difficult to determine from this study whether a significant portion of their patients were on dual antiplatelet therapy.
It is also interesting to notice that the authors found that almost 10% of patients had at least one in-hospital complication; some of which were major complications, e.g. stroke, MI, and dysphagia. Including bleeding/hematoma in these complications, which may not have necessitated surgery, may have inflated this number. A similar observation can be made regarding postoperative arrhythmias, particularly if they did not necessitate extra therapy. However, the fact of the matter is that it should be emphasized that the selection of patients for carotid endarterectomy in asymptomatic patients is extremely critical if this procedure is to be continued or blessed.
Dr. Ali F. AbuRahma is Professor of Surgery and Chief, Vascular & Endovascular Surgery, and Director, Vascular Surgery Fellowship and Residency Programs, and Medical Director, Vascular Laboratory, Co-Director, Vascular Center of Excellence, Robert C. Byrd Health Sciences Center, West Virginia University, Charleston Area Medical Center, Charleston. He is a also an associate medical editor of Vascular Specialist.
Over the past several years, the role of carotid endarterectomy (CEA) for asymptomatic carotid stenosis has, again, come under the microscope; with many proponents still advocating CEA as the treatment of choice for asymptomatic patients with greater than or equal to 60% stenosis, while some propose greater than or equal to 70-80% stenosis in good surgical risk patients. Meanwhile, others oppose this philosophy because of the advances in modern medical therapy for patients with atherosclerosis, in general, with emphasis on risk modification. The findings of this article are quite disturbing, since the authors concluded that the 30-day unplanned re-admission rate after CEA was 6.5%; this is especially surprising to me, coming from this institution.
Dr. AbuRahma |
The authors also concluded that unplanned re-admission rate was influenced by congestive heart failure, in-hospital postoperative stroke, in-hospital postoperative hematoma, and prior coronary artery bypass grafting. This emphasizes the importance of selection, selection, selection for asymptomatic carotid artery stenosis, if the outcome is to be acceptable to those who still advocate carotid endarterectomy for asymptomatic carotid disease.
Perhaps this procedure should not be encouraged for patients with congestive heart failure or those with severe coronary artery disease, unstable angina. Today, Level I evidence still supports carotid endarterectomy for patients with severe carotid artery stenosis, provided the patient is a good surgical risk, with relatively good longevity; with perioperative stroke and/or death rates of less than 3%. Several modern clinical series have concluded that CEA can be done in these patients with a stroke and/or death rate of less than 1-2%, which was produced most recently in the CREST trial. For those clinicians who cannot keep these numbers down, perhaps this procedure should not be done for asymptomatic carotid disease. What’s also surprising to me, is the in-hospital postoperative hematomas, which I presume necessitated the re-admission and, perhaps, reoperation. This should highlight the fact that, perhaps, we need to look further as to whether or not these patients should be on a combined regimen of aspirin and Plavix, preoperatively and postoperatively, as prescribed by many clinicians.
There is no Level I evidence to support that the combination of aspirin and Plavix, postoperatvely, for these patients would yield a better outcome than simple aspirin daily. It is difficult to determine from this study whether a significant portion of their patients were on dual antiplatelet therapy.
It is also interesting to notice that the authors found that almost 10% of patients had at least one in-hospital complication; some of which were major complications, e.g. stroke, MI, and dysphagia. Including bleeding/hematoma in these complications, which may not have necessitated surgery, may have inflated this number. A similar observation can be made regarding postoperative arrhythmias, particularly if they did not necessitate extra therapy. However, the fact of the matter is that it should be emphasized that the selection of patients for carotid endarterectomy in asymptomatic patients is extremely critical if this procedure is to be continued or blessed.
Dr. Ali F. AbuRahma is Professor of Surgery and Chief, Vascular & Endovascular Surgery, and Director, Vascular Surgery Fellowship and Residency Programs, and Medical Director, Vascular Laboratory, Co-Director, Vascular Center of Excellence, Robert C. Byrd Health Sciences Center, West Virginia University, Charleston Area Medical Center, Charleston. He is a also an associate medical editor of Vascular Specialist.
Over the past several years, the role of carotid endarterectomy (CEA) for asymptomatic carotid stenosis has, again, come under the microscope; with many proponents still advocating CEA as the treatment of choice for asymptomatic patients with greater than or equal to 60% stenosis, while some propose greater than or equal to 70-80% stenosis in good surgical risk patients. Meanwhile, others oppose this philosophy because of the advances in modern medical therapy for patients with atherosclerosis, in general, with emphasis on risk modification. The findings of this article are quite disturbing, since the authors concluded that the 30-day unplanned re-admission rate after CEA was 6.5%; this is especially surprising to me, coming from this institution.
Dr. AbuRahma |
The authors also concluded that unplanned re-admission rate was influenced by congestive heart failure, in-hospital postoperative stroke, in-hospital postoperative hematoma, and prior coronary artery bypass grafting. This emphasizes the importance of selection, selection, selection for asymptomatic carotid artery stenosis, if the outcome is to be acceptable to those who still advocate carotid endarterectomy for asymptomatic carotid disease.
Perhaps this procedure should not be encouraged for patients with congestive heart failure or those with severe coronary artery disease, unstable angina. Today, Level I evidence still supports carotid endarterectomy for patients with severe carotid artery stenosis, provided the patient is a good surgical risk, with relatively good longevity; with perioperative stroke and/or death rates of less than 3%. Several modern clinical series have concluded that CEA can be done in these patients with a stroke and/or death rate of less than 1-2%, which was produced most recently in the CREST trial. For those clinicians who cannot keep these numbers down, perhaps this procedure should not be done for asymptomatic carotid disease. What’s also surprising to me, is the in-hospital postoperative hematomas, which I presume necessitated the re-admission and, perhaps, reoperation. This should highlight the fact that, perhaps, we need to look further as to whether or not these patients should be on a combined regimen of aspirin and Plavix, preoperatively and postoperatively, as prescribed by many clinicians.
There is no Level I evidence to support that the combination of aspirin and Plavix, postoperatvely, for these patients would yield a better outcome than simple aspirin daily. It is difficult to determine from this study whether a significant portion of their patients were on dual antiplatelet therapy.
It is also interesting to notice that the authors found that almost 10% of patients had at least one in-hospital complication; some of which were major complications, e.g. stroke, MI, and dysphagia. Including bleeding/hematoma in these complications, which may not have necessitated surgery, may have inflated this number. A similar observation can be made regarding postoperative arrhythmias, particularly if they did not necessitate extra therapy. However, the fact of the matter is that it should be emphasized that the selection of patients for carotid endarterectomy in asymptomatic patients is extremely critical if this procedure is to be continued or blessed.
Dr. Ali F. AbuRahma is Professor of Surgery and Chief, Vascular & Endovascular Surgery, and Director, Vascular Surgery Fellowship and Residency Programs, and Medical Director, Vascular Laboratory, Co-Director, Vascular Center of Excellence, Robert C. Byrd Health Sciences Center, West Virginia University, Charleston Area Medical Center, Charleston. He is a also an associate medical editor of Vascular Specialist.
SAN FRANCISCO – The 30-day unplanned readmission rate following carotid endarterectomy was 6.5% in a single-center study.
In addition, four variables were significantly associated with unplanned readmission: in-hospital postoperative congestive heart failure (CHF) exacerbation; in-hospital postoperative stroke; in-hospital postoperative hematoma; and prior coronary artery bypass graft (CABG).
"Whether these complications are completely avoidable is unknown, but we do identify a group of patients who would probably benefit from more comprehensive discharge planning and careful postdischarge care," Dr. Karen J. Ho said at the Society for Vascular Surgery annual meeting earlier this year.
According to a study of Medicare claims data from 2003 to 2004, 20% of Medicare beneficiaries discharged from a hospital were rehospitalized within 30 days (N. Eng. J. Med. 2009;360:1418-28). The 30-day rehospitalization rate after vascular surgery was 24%, "the highest of all surgical specialties examined in the study," said Dr. Ho of the surgery department at Brigham and Women’s Hospital, Boston, who was not involved with the published study. "Medicare has started to decrease reimbursements for hospitals with excess readmissions after acute MI, heart failure, and pneumonia. Hip and knee replacements and chronic obstructive pulmonary disease will be added in 2014, and we anticipate that additional surgical procedures will be added thereafter," she said.
In an effort to determine the rate of 30-day unplanned readmission after carotid endarterectomy (CEA), Dr. Ho and her associates conducted a retrospective study of a prospectively collected vascular surgery database at Brigham and Women’s Hospital. The cohort included 896 consecutive CEAs performed between 2002 and 2011. Combined CABG/CEA procedures were excluded.
The primary endpoint was unplanned readmission within 30 days, defined as "any unanticipated, nonelective hospital readmission," she said. The secondary endpoint was 1-year survival.
The mean age of the patients was 70 years, 60% were male, and 95% were white. More than half (65%) had asymptomatic evidence of carotid artery disease.
Dr. Ho reported that the median postoperative length of stay was 1 day and that 9.9% of patients had at least one in-hospital complication. The most frequent in-hospital complication was bleeding/hematoma (4.1%), followed by arrhythmia (2.1%), dysphagia (1.7%), stroke (1.3%), and myocardial infarction (1.2%). Only 3% of patients required a reoperation, while most (94%) were discharged to home. The 30-day stroke rate was 1.7%, while the 30-day death rate was 0.6%.
The overall 30-day readmission rate was 8.6%, while the unplanned 30-day readmission rate was 6.5%. "Most of the overall readmissions (80%) occurred in the first 10 days, and the median time to unplanned readmission was 4 days," Dr. Ho said.
The most common reason for an unplanned readmission was a cardiac complication, followed by headache, bleeding/hematoma, stroke/transient ischemic attack/intracerebral hemorrhage, or other medical emergency. More than one-quarter of patients (27.5%) had more than one reason for an unplanned readmission, while 87.9% of patients had a CEA-related unplanned readmission.
When the researchers performed a univariate analysis followed by analysis with a multivariable Cox model for unplanned readmission, four variables were independently associated with unplanned readmission: in-hospital postoperative CHF exacerbation (hazard ratio, 15.1), in-hospital postoperative stroke (HR, 5.0), in-hospital postoperative hematoma (HR, 3.1), and prior CABG (HR, 2.0).
They also observed a significant difference in survival at 1 year between patients who had an unplanned readmission and those who did not (91% vs. 96%, respectively; P less than .01.) "It’s unclear whether these deaths in the unplanned readmission group were preventable or if they were related to carotid disease or to a procedure-related complication," Dr. Ho said. "Our guess is that the increased overall burden of comorbid disease in these patients, rather than the readmission itself, predicted decreased survival."
Limitations of the study included its retrospective design and the fact that it was conducted at a single center, she said, "but we do know that our unplanned readmission rate is comparable to estimates from recent Medicare data."
Dr. Ho said she had no relevant financial disclosures.
SAN FRANCISCO – The 30-day unplanned readmission rate following carotid endarterectomy was 6.5% in a single-center study.
In addition, four variables were significantly associated with unplanned readmission: in-hospital postoperative congestive heart failure (CHF) exacerbation; in-hospital postoperative stroke; in-hospital postoperative hematoma; and prior coronary artery bypass graft (CABG).
"Whether these complications are completely avoidable is unknown, but we do identify a group of patients who would probably benefit from more comprehensive discharge planning and careful postdischarge care," Dr. Karen J. Ho said at the Society for Vascular Surgery annual meeting earlier this year.
According to a study of Medicare claims data from 2003 to 2004, 20% of Medicare beneficiaries discharged from a hospital were rehospitalized within 30 days (N. Eng. J. Med. 2009;360:1418-28). The 30-day rehospitalization rate after vascular surgery was 24%, "the highest of all surgical specialties examined in the study," said Dr. Ho of the surgery department at Brigham and Women’s Hospital, Boston, who was not involved with the published study. "Medicare has started to decrease reimbursements for hospitals with excess readmissions after acute MI, heart failure, and pneumonia. Hip and knee replacements and chronic obstructive pulmonary disease will be added in 2014, and we anticipate that additional surgical procedures will be added thereafter," she said.
In an effort to determine the rate of 30-day unplanned readmission after carotid endarterectomy (CEA), Dr. Ho and her associates conducted a retrospective study of a prospectively collected vascular surgery database at Brigham and Women’s Hospital. The cohort included 896 consecutive CEAs performed between 2002 and 2011. Combined CABG/CEA procedures were excluded.
The primary endpoint was unplanned readmission within 30 days, defined as "any unanticipated, nonelective hospital readmission," she said. The secondary endpoint was 1-year survival.
The mean age of the patients was 70 years, 60% were male, and 95% were white. More than half (65%) had asymptomatic evidence of carotid artery disease.
Dr. Ho reported that the median postoperative length of stay was 1 day and that 9.9% of patients had at least one in-hospital complication. The most frequent in-hospital complication was bleeding/hematoma (4.1%), followed by arrhythmia (2.1%), dysphagia (1.7%), stroke (1.3%), and myocardial infarction (1.2%). Only 3% of patients required a reoperation, while most (94%) were discharged to home. The 30-day stroke rate was 1.7%, while the 30-day death rate was 0.6%.
The overall 30-day readmission rate was 8.6%, while the unplanned 30-day readmission rate was 6.5%. "Most of the overall readmissions (80%) occurred in the first 10 days, and the median time to unplanned readmission was 4 days," Dr. Ho said.
The most common reason for an unplanned readmission was a cardiac complication, followed by headache, bleeding/hematoma, stroke/transient ischemic attack/intracerebral hemorrhage, or other medical emergency. More than one-quarter of patients (27.5%) had more than one reason for an unplanned readmission, while 87.9% of patients had a CEA-related unplanned readmission.
When the researchers performed a univariate analysis followed by analysis with a multivariable Cox model for unplanned readmission, four variables were independently associated with unplanned readmission: in-hospital postoperative CHF exacerbation (hazard ratio, 15.1), in-hospital postoperative stroke (HR, 5.0), in-hospital postoperative hematoma (HR, 3.1), and prior CABG (HR, 2.0).
They also observed a significant difference in survival at 1 year between patients who had an unplanned readmission and those who did not (91% vs. 96%, respectively; P less than .01.) "It’s unclear whether these deaths in the unplanned readmission group were preventable or if they were related to carotid disease or to a procedure-related complication," Dr. Ho said. "Our guess is that the increased overall burden of comorbid disease in these patients, rather than the readmission itself, predicted decreased survival."
Limitations of the study included its retrospective design and the fact that it was conducted at a single center, she said, "but we do know that our unplanned readmission rate is comparable to estimates from recent Medicare data."
Dr. Ho said she had no relevant financial disclosures.
Major finding: Four variables were independently associated with unplanned readmission: in-hospital postoperative CHF exacerbation (hazard ratio, 15.1), in-hospital postoperative stroke (HR, 5.0), in-hospital postoperative hematoma (HR, 3.1), and prior CABG (HR, 2.0).
Data source: A study of 896 consecutive CEAs performed between 2002 and 2011 at Brigham and Women’s Hospital, Boston.
Disclosures: Dr. Ho said she had no relevant financial disclosures.
Physician Burnout Meta‐analysis
Hospital medicine is a rapidly growing field of US clinical practice.[1] Almost since its advent, concerns have been expressed about the potential for hospitalists to burn out.[2] Hospitalists are not unique in this; similar concerns heralded the arrival of other location‐defined specialties, including emergency medicine[3] and the full‐time intensivist model,[4] a fact that has not gone unnoted in the literature about hospitalists.[5]
The existing international literature on physician burnout provides good reason for this concern. Inpatient‐based physicians tend to work unpredictable schedules, with substantial impact on home life.[6] They tend to be young, and much burnout literature suggests a higher risk among younger, less‐experienced physicians.[7] When surveyed, hospitalists have expressed more concerns about their potential for burnout than their outpatient‐based colleagues.[8]
In fact, data suggesting a correlation between inpatient practice and burnout predate the advent of the US hospitalist movement. Increased hospital time was reported to correlate with higher rates of burnout in internists,[9] family practitioners,[10] palliative physicians,[11] junior doctors,[12] radiologists,[13] and cystic fibrosis caregivers.[14] In 1987, Keinan and Melamed[15] noted, Hospital work by its very nature, as compared to the work of a general practitioner, deals with the more severe and complicated illnesses, coupled with continuous daily contacts with patients and their anxious families. In addition, these physicians may find themselves embroiled in the power struggles and competition so common in their work environment.
There are other features, however, that may protect inpatient physicians from burnout. Hospital practice can facilitate favorable social relations involving colleagues, co‐workers, and patients,[16] a factor that may be protective.[17] A hospitalist schedule also can allow more focused time for continuing medical education, research, and teaching,[18] which have all been associated with reduced risk of burnout in some studies.[17] Studies of psychiatrists[19] and pediatricians[20] have shown a lower rate of burnout among physicians with more inpatient duties. Finally, a practice model involving a seemingly stable cadre of inpatient physicians has existed in Europe for decades,[2] indicating at least a degree of sustainability.
Information suggesting a higher rate of burnout among inpatient physicians could be used to target therapeutic interventions and to adjust schedules, whereas the opposite outcome could refute a pervasive myth. We therefore endeavored to summarize the literature on burnout among inpatient versus outpatient physicians in a systematic fashion, and to include data not only from the US hospitalist experience but also from other countries that have used a similar model for decades. Our primary hypothesis was that inpatient physicians experience more burnout than outpatient physicians.
It is important to distinguish burnout from depression, job dissatisfaction, and occupational stress, all of which have been studied extensively in physicians. Burnout, as introduced by Freudenberger[21] and further characterized by Maslach,[22] is a condition in which emotional exhaustion, depersonalization, and a low sense of personal accomplishment combine to negatively affect work life (as opposed to clinical depression, which affects all aspects of life). Job satisfaction can correlate inversely with burnout, but it is a separate process[23] and the subject of a recent systematic review.[24] The importance of distinguishing burnout from job dissatisfaction is illustrated by a survey of head and neck surgeons, in which 97% of those surveyed indicated satisfaction with their jobs and 34% of the same group answered in the affirmative when asked if they felt burned out.[25]
One obstacle to the meaningful comparison of burnout prevalence across time, geography, and specialty is the myriad ways in which burnout is measured and reported. The oldest and most commonly used instrument to measure burnout is the Maslach Burnout Inventory (MBI), which contains 22 items assessing 3 components of burnout (emotional exhaustion, depersonalization, and low personal accomplishment).[26] Other measures include the Copenhagen Burnout Inventory[27] (19 items with the components personal burnout, work‐related burnout, and client‐related burnout), Utrecht Burnout Inventory[28] (20‐item modification of the MBI), Boudreau Burnout Questionnaire[29] (30 items), Arbeitsbezogenes Verhaltens und Erlebensmuster[30] (66‐item questionnaire assessing professional commitment, resistance to stress, and emotional well‐being), Shirom‐Melamed Burnout Measure[31] (22 items with subscales for physical fatigue, cognitive weariness, tension, and listlessness), and a validated single‐item questionnaire.[32]
METHODS
Electronic searches of MEDLINE, EMBASE, PsycINFO, SCOPUS, and PubMed were undertaken for articles published from January 1, 1974 (the year in which burnout was first described by Freudenberger[21]) to 2012 (last accessed, September 12, 2012) using the Medical Subject Headings (MeSH) terms stress, psychological; burnout, professional; adaptation, psychological; and the keyword burnout. The same sources were searched to create another set for the MeSH terms hospitalists, physician's practice patterns, physicians/px, professional practice location, and the keyword hospitalist#. Where exact subject headings did not exist in databases, comparable subject headings or keywords were used. The 2 sets were then combined using the operator and. Abstracts from the Society of Hospital Medicine annual conferences were hand‐searched, as were reference lists from identified articles. To ensure that pertinent international literature was captured, there was no language restriction in the search.
A 2‐stage screening process was used. The titles and abstracts of all articles identified in the search were independently reviewed by 2 investigators (D.L.R. and K.J.C.) who had no knowledge of each other's results. An article was obtained when either reviewer deemed it worthy of full‐text review.
All full‐text articles were independently reviewed by the same 2 investigators. The inclusion criterion was the measurement of burnout in physicians who are stated to or can be reasonably assumed to spend the substantial majority of their clinical practice exclusively in either the inpatient or the outpatient setting. Studies of emergency department physicians or specialists who invariably spend substantial amounts of time in both settings (eg, surgeons, anesthesiologists) were excluded. Studies limited to trainees or nonphysicians were also excluded. For both stages of review, agreement between the 2 investigators was assessed by calculating the statistic. Disagreements about inclusion were adjudicated by a third investigator (A.I.B.).
Because our goal was to establish and compare the rate of burnout among US hospitalists and other inpatient physicians around the world, we included studies of hospitalists according to the definition in use at the time of the individual study, noting that the formal definition of a hospitalist has changed over the years.[33] Because practice patterns for physicians described as primary care physicians, family doctors, hospital doctors, and others differ substantially from country to country, we otherwise included only the studies where the practice location was stated explicitly or where the authors confirmed that their study participants either are known or can be reasonably assumed to spend more than 75% of their time caring for hospital inpatients, or are known or can be reasonably assumed to spend the vast majority of their time caring for outpatients.
Data were abstracted using a standardized form and included the measure of burnout used in the study, results, practice location of study subjects, and total number of study subjects. When data were not clear (eg, burnout measured but not reported by the authors, practice location of study subjects not clear), authors were contacted by email, or when no current email address could be located or no response was received, by telephone or letter. In instances where burnout was measured repeatedly over time or before and after a specific intervention, only the baseline measurement was recorded. Because all studies were expected to be nonrandomized, methodological quality was assessed using a version of the tool of Downs and Black,[34] adapted where necessary by omitting questions not applicable to the specific study type (eg randomization for survey studies)[35] and giving a maximum of 1 point for the inclusion of a power calculation.
Two a priori analyses were planned: (1) a statistical comparison of articles directly comparing burnout among inpatient and outpatient physicians, and (2) a statistical comparison of articles measuring burnout among inpatient physicians with articles measuring burnout among outpatient physicians by the most frequently reported measuremean subset scores for emotional exhaustion, depersonalization, and personal accomplishment on the MBI.
The primary outcome measures were the differences between mean subset scores for emotional exhaustion, depersonalization, and personal accomplishment on the MBI. All differences are expressed as (outpatient meaninpatient mean). The variance of each outcome was calculated with standard formulas.[36] To calculate the overall estimate, each study was weighted by the reciprocal of its variance. Studies with fewer than 10 subjects were excluded from statistical analysis but retained in the systematic review.
For studies that reported data for both inpatient and outpatient physicians (double‐armed studies), Cochran Q test and the I2 value were used to assess heterogeneity.[37, 38] Substantial heterogeneity was expected because these individual studies were conducted for different populations in different settings with different study designs, and this expectation was confirmed statistically. Therefore, we used a random effects model to estimate the overall effect, providing a conservative approach that accounted for heterogeneity among studies.[39]
To assess the durability of our findings, we performed separate multivariate meta‐regression analyses by including single‐armed studies only and including both single‐armed and double‐armed studies. For these meta‐regressions, means were again weighted by the reciprocal of their variances, and the arms of 2‐armed studies were considered separately. This approach allowed us to generate an estimate of the differences between MBI subset scores from studies that did not include such an estimate when analyzed separately.[40]
We examined the potential for publication bias in double‐armed studies by constructing a funnel plot, in which mean scores were plotted against their standard errors.[41] The trim‐and‐fill method was used to determine whether adjustment for publication bias was necessary. In addition, Begg's rank correlation test[42] was completed to test for statistically significant publication bias.
Stata 10.0 statistical software (StataCorp, College Station, TX) was used for data analyses. A P value of 0.05 or less was deemed statistically significant. The Preferred Reporting Items for Systematic Reviews and Meta‐analysis checklist was used for the design and execution of the systematic review and meta‐analysis.[43]
Subgroup analyses based on location were undertaken a posteriori. All data (double‐armed meta‐analysis, meta‐regression of single‐armed studies, and meta‐regression of single‐ and double‐armed studies) were analyzed by location (United States vs other; United States vs Europe vs other).
RESULTS
The search results are outlined in Figure 1. In total, 1704 articles met the criteria for full‐text review. A review of pertinent reference lists and author contacts led to the addition of 149 articles. Twenty‐nine references could not be located by any means, despite repeated attempts. Therefore, 1824 articles were subjected to full‐text review by the 2 investigators.

Initially, 57 articles were found that met criteria for inclusion. Of these, 2 articles reported data in formats that could not be interpreted.[44, 45] When efforts to clarify the data with the authors were unsuccessful, these studies were excluded. A study specifically designed to assess the response of physicians to a recent series of terrorist attacks[46] was excluded a posteriori because of lack of generalizability. Of the other 54 studies, 15 reported burnout data on both outpatient physicians and inpatient physicians, 22 reported data on outpatient physicians only, and 17 reported data on inpatient physicians only. Table 1 summarizes the results of the 37 studies involving outpatient physicians; Table 2 summarizes the 32 studies involving inpatient physicians.
Lead Author, Publication Year | Study Population and Location | Instrument | No. of Participants | EE Score (SD)a | DP Score (SD) | PA Score (SD) | Other Results |
---|---|---|---|---|---|---|---|
| |||||||
Schweitzer, 1994[12] | Young physicians of various specialties in South Africa | Single‐item survey | 7 | 6 (83%) endorsed burnout | |||
Aasland, 1997 [54]b | General practitioners in Norway | Modified MBI (22 items; scale, 15) | 298 | 2.65 (0.80) | 1.90 (0.59) | 3.45 (0.40) | |
Grassi, 2000 [58] | General practitioners in Italy | MBI | 182 | 18.49 (11.49) | 6.11 (5.86) | 38.52 (7.60) | |
McManus, 2000 [59]b | General practitioners in United Kingdom | Modified MBI (9 items; scale, 06) | 800 | 8.34 (4.39) | 3.18 (3.40) | 14.16 (2.95) | |
Yaman, 2002 [60] | General practitioners in 8 European nations | MBI | 98 | 25.1 (8.50) | 7.3 (4.92) | 34.5 (7.67) | |
Cathbras, 2004 [61] | General practitioners in France | MBI | 306 | 21.85 (12.4) | 9.13 (6.7) | 38.7 (7.1) | |
Goehring, 2005 [63] | General practitioners, general internists, pediatricians in Switzerland | MBI | 1755 | 17.9 (9.8) | 6.5 (4.7) | 39.6 (6.5) | |
Esteva, 2006 [64] | General practitioners, pediatricians in Spain | MBI | 261 | 27.4 (11.8) | 10.07 (6.4) | 35.9 (7.06) | |
Gandini, 2006 [65]b | Physicians of various specialties in Argentina | MBI | 67 | 31.0 (13.8) | 10.2 (6.6) | 38.4 (6.8) | |
Ozyurt, 2006 [66] | General practitioners in Turkey | Modified MBI (22 items; scale, 04) | 55 | 15.23 (5.80) | 4.47 (3.31) | 23.38 (4.29) | |
Deighton, 2007 [67]b | Psychiatrists in several German‐speaking nations | MBI | 19 | 30.68 (9.92) | 13.42 (4.23) | 37.16 (3.39) | |
Dunwoodie, 2007 [68]b | Palliative care physicians in Australia | MBI | 21 | 14.95 (9.14) | 3.95 (3.40) | 38.90 (2.88) | |
Srgaard, 2007 [69]b | Psychiatrists in 5 European nations | MBI | 22 | 19.41 (8.08) | 6.68 (4.93) | 39.00 (4.40) | |
Sosa Oberlin, 2007 [56]b | Physicians of various specialties in Argentina | Author‐designed instrument | 33 | 26 (78.8%) had 4 burnout symptoms, 6.15 symptoms per physician | |||
Voltmer, 2007 [57]b | Physicians of various specialties in Germany | AVEM | 46 | 11 (23.9%) exhibited burnout (type B) pattern | |||
dm, 2008 [70]b | Physicians of various specialties in Hungary | MBI | 163 | 17.45 (11.12) | 4.86 (4.91) | 36.56 (7.03) | |
Di Iorio, 2008 [71]b | Dialysis physicians in Italy | Author‐designed instrument | 54 | Work: 2.6 (1.5), Material: 3.1 (2.1), Climate: 3.0 (1.1), Objectives: 3.4 (1.6), Quality: 2.2 (1.5), Justification: 3.2 (2.0) | |||
Lee, 2008 [49]b | Family physicians in Canada | MBI | 123 | 26.26 (9.53) | 10.20 (5.22) | 38.43 (7.34) | |
Truchot, 2008 [72] | General practitioners in France | MBI | 259 | 25.4 (11.7) | 7.5 (5.5) | 36.5 (7.1) | |
Twellaar, 2008 [73]b | General practitioners in the Netherlands | Utrecht Burnout Inventory | 349 | 2.06 (1.11) | 1.71 (1.05) | 5.08 (0.77) | |
Arigoni, 2009 [17] | General practitioners, pediatricians in Switzerland | MBI | 258 | 22.8 (12.0) | 6.9 (6.1) | 39.0 (7.2) | |
Bernhardt, 2009 [75] | Clinical geneticists in United States | MBI | 72 | 25.8 (10.01)c | 10.9 (4.16)c | 34.8 (5.43)c | |
Bressi, 2009 [76]b | Psychiatrists in Italy | MBI | 53 | 23.15 (11.99) | 7.02 (6.29) | 36.41 (7.54) | |
Krasner, 2009 [77] | General practitioners in United States | MBI | 60 | 26.8 (10.9)d | 8.4 (5.1)d | 40.2 (5.3)d | |
Lasalvia, 2009 [55]b | Psychiatrists in Italy | Modified MBI (16 items; scale, 06) | 38 | 2.37 (1.27) | 1.51 (1.15) | 4.46 (0.87) | |
Peisah, 2009 [79]b | Physicians of various specialties in Australia | MBI | 28 | 13.92 (9.24) | 3.66 (3.95) | 39.34 (8.55) | |
Shanafelt, 2009 [80]b | Physicians of various specialties in United States | MBI | 408 | 20.5 (11.10) | 4.3 (4.74) | 40.8 (6.26) | |
Zantinge, 2009 [81] | General practitioners in the Netherlands | Utrecht Burnout Inventory | 126 | 1.58 (0.79) | 1.32 (0.72) | 4.27 (0.77) | |
Voltmer, 2010 [83]b | Psychiatrists in Germany | AVEM | 526 | 114 (21.7%) exhibited burnout (type B) pattern | |||
Maccacaro, 2011 [85]b | Physicians of various specialties in Italy | MBI | 42 | 14.31 (11.98) | 3.62 (4.95) | 38.24 (6.22) | |
Lucas, 2011 [84]b | Outpatient physicians periodically staffing an academic hospital teaching service in United States | MBI (EE only) | 30 | 24.37 (14.95) | |||
Shanafelt, 2012 [87]b | General internists in United States | MBI | 447 | 25.4 (14.0) | 7.5 (6.3) | 41.4 (6.0) | |
Kushnir, 2004 [62] | General practitioners and pediatricians in Israel | MBI (DP only) and SMBM | 309 | 9.15 (3.95) | SMBM mean (SD), 2.73 per item (0.86) | ||
Vela‐Bueno, 2008 [74]b | General practitioners in Spain | MBI | 240 | 26.91 (11.61) | 9.20 (6.35) | 35.92 (7.92) | |
Lesic, 2009 [78]b | General practitioners in Serbia | MBI | 38 | 24.71 (10.81) | 7.47 (5.51) | 37.21 (7.44) | |
Demirci, 2010 [82]b | Medical specialists related to oncology practice in Hungary | MBI | 26 | 23.31 (11.2) | 6.46 (5.7) | 37.7 (8.14) | |
Putnik, 2011 [86]b | General practitioners in Hungary | MBI | 370 | 22.22 (11.75) | 3.66 (4.40) | 41.40 (6.85) |
Lead Author, Publication Year | Study Population and Location | Instrument | No. of Participants | EE Score (SD)a | DP Score (SD) | PA Score (SD) | Other Results |
---|---|---|---|---|---|---|---|
| |||||||
Varga, 1996 [88] | Hospital doctors in Spain | MBI | 179 | 21.61b | 7.33b | 35.28b | |
Aasland, 1997 [54] | Hospital doctors in Norway | Modified MBI (22 items; scale, 15) | 582 | 2.39 (0.80) | 1.81 (0.65) | 3.51 (0.46) | |
Bargellini, 2000 [89] | Hospital doctors in Italy | MBI | 51 | 17.45 (9.87) | 7.06 (5.54) | 35.33 (7.90) | |
Grassi, 2000 [58] | Hospital doctors in Italy | MBI | 146 | 16.17 (9.64) | 5.32 (4.76) | 38.71 (7.28) | |
Hoff, 2001 [33] | Hospitalists in United States | Single‐item surveyc | 393 | 12.9% burned out (>4/5), 24.9% at risk for burnout (34/5), 62.2% at no current risk (mean, 2.86 on 15 scale) | |||
Trichard, 2005 [90] | Hospital doctors in France | MBI | 199 | 16 (10.7) | 6.6 (5.7) | 38.5 (6.5) | |
Gandini, 2006 [65]d | Hospital doctors in Argentina | MBI | 290 | 25.0 (12.7) | 7.9 (6.2) | 40.1 (7.0) | |
Dunwoodie, 2007 [68]d | Palliative care doctors in Australia | MBI | 14 | 18.29 (14.24) | 5.29 (5.89) | 38.86 (3.42) | |
Srgaard, 2007 [69]d | Psychiatrists in 5 European nations | MBI | 18 | 18.56 (9.32) | 5.50 (3.79) | 39.08 (5.39) | |
Sosa Oberlin, 2007 [56]d | Hospital doctors in Argentina | Author‐designed instrument | 3 | 3 (100%) had 4 burnout symptoms, 8.67 symptoms per physician | |||
Voltmer, 2007 [57]d | Hospital doctors in Germany | AVEM | 271 | 77 (28.4%) exhibited burnout (type B) pattern | |||
dm, 2008 [70]b | Physicians of various specialties in Hungary | MBI | 194 | 19.23 (10.79) | 4.88 (4.61) | 35.26 (8.42) | |
Di Iorio, 2008 [71]d | Dialysis physicians in Italy | Author‐designed instrument | 62 | Work, mean (SD), 3.1 (1.4); Material, mean (SD), 3.3 (1.5); Climate, mean (SD), 2.9 (1.1); Objectives, mean (SD), 2.5 (1.5); Quality, mean (SD), 3.0 (1.1); Justification, mean (SD), 3.1 (2.1) | |||
Fuss, 2008 [91]d | Hospital doctors in Germany | Copenhagen Burnout Inventory | 292 | Mean Copenhagen Burnout Inventory, mean (SD), 46.90 (18.45) | |||
Marner, 2008 [92]d | Psychiatrists and 1 generalist in United States | MBI | 9 | 20.67 (9.75) | 7.78 (5.14) | 35.33 (6.44) | |
Shehabi, 2008 [93]d | Intensivists in Australia | Modified MBI (6 items; scale, 15) | 86 | 2.85 (0.93) | 2.64 (0.85) | 2.58 (0.83) | |
Bressi, 2009 [76]d | Psychiatrists in Italy | MBI | 28 | 17.89 (14.46) | 5.32 (7.01) | 34.57 (11.27) | |
Brown, 2009 [94] | Hospital doctors in Australia | MBI | 12 | 22.25 (8.59) | 6.33 (2.71) | 39.83 (7.31) | |
Lasalvia, 2009 [55]d | Psychiatrists in Italy | Modified MBI (16 items; scale, 06) | 21 | 1.95 (1.04) | 1.35 (0.85) | 4.46 (1.04) | |
Peisah, 2009 [79]d | Hospital doctors in Australia | MBI | 62 | 20.09 (9.91) | 6.34 (4.90) | 35.06 (7.33) | |
Shanafelt, 2009 [80]d | Hospitalists and intensivists in United States | MBI | 19 | 25.2 (11.59) | 4.4 (3.79) | 38.5 (8.04) | |
Tunc, 2009 [95] | Hospital doctors in Turkey | Modified MBI (22 items; scale, 04) | 62 | 1.18 (0.78) | 0.81 (0.73) | 3.10 (0.59)e | |
Cocco, 2010 [96]d | Hospital geriatricians in Italy | MBI | 38 | 16.21 (11.56) | 4.53 (4.63) | 39.13 (7.09) | |
Doppia, 2011 [97]d | Hospital doctors in France | Copenhagen Burnout Inventory | 1,684 | Mean work‐related burnout score, 2.72 (0.75) | |||
Glasheen, 2011 [98] | Hospitalists in United States | Single‐item survey | 265 | Mean, 2.08 on 15 scale 62 (23.4%) burned out | |||
Lucas, 2011 [84]d | Academic hospitalists in United States | MBI (EE only) | 26 | 19.54 (12.85) | |||
Thorsen, 2011 [99] | Hospital doctors in Malawi | MBI | 2 | 25.5 (4.95) | 8.5 (6.36) | 25.0 (5.66) | |
Hinami, 2012 [50]d | Hospital doctors in United States | Single‐item survey | 793 | Mean, 2.24 on 15 scale 261 (27.2%) burned out | |||
Quenot, 2012 [100]d | Intensivists in France | MBI | 4 | 33.25 (4.57) | 13.50 (5.45) | 35.25 (4.86) | |
Ruitenburg, 2012 [101] | Hospital doctors in the Netherlands | MBI (EE and DP only) | 214 | 13.3 (8.0) | 4.5 (4.1) | ||
Seibt, 2012 [102]d | Hospital doctors in Germany | Modified MBI (16 items; scale, 06, reported per item rather than totals) | 2,154 | 2.2 (1.4) | 1.4 (1.2) | 5.1 (0.9) | |
Shanafelt, 2012 [87]d | Hospitalists in United States | MBI | 130 | 24.7 (12.5) | 9.1 (6.9) | 39.0 (7.6) |
Table 3 summarizes the results of the 15 studies that reported burnout data for both inpatient and outpatient physicians, allowing direct comparisons to be made. Nine studies reported MBI subset totals with standard deviations, 2 used different modifications of the MBI, 2 used different author‐derived measures, 1 used only the emotional exhaustion subscale of the MBI, and 1 used the Arbeitsbezogenes Verhaltens und Erlebensmuster. Therefore, statistical comparison was attempted only for the 9 studies reporting comparable MBI data, comprising burnout data on 1390 outpatient physicians and 899 inpatient physicians.
Lead Author, Publication Year | Location | Instrument | Inpatient‐Based Physicians | Outpatient‐Based Physicians | ||
---|---|---|---|---|---|---|
No. | Results, Score (SD)a | No. | Results, Score (SD)a | |||
| ||||||
Aasland, 1997 [54]b | Norway | Modified MBI (22 items; scale, 15) | 582 | EE, 2.39 (0.80); DP, 1.81 (0.65); PA, 3.51 (0.46) | 298 | EE, 2.65 (0.80); DP, 1.90 (0.59); PA, 3.45 (0.40) |
Grassi, 2000 [58] | Italy | MBI | 146 | EE, 16.17 (9.64); DP, 5.32 (4.76); PA, 38.71 (7.28) | 182 | EE, 18.49 (11.49); DP, 6.11 (5.86); PA, 38.52 (7.60) |
Gandini, 2006 [65]b | Argentina | MBI | 290 | EE, 25.0 (12.7);DP, 7.9 (6.2); PA, 40.1 (7.0) | 67 | EE, 31.0 (13.8); DP, 10.2 (6.6); PA, 38.4 (6.8) |
Dunwoodie, 2007 [68]b | Australia | MBI | 14 | EE, 18.29 (14.24); DP, 5.29 (5.89); PA, 38.86 (3.42) | 21 | EE, 14.95 (9.14); DP, 3.95 (3.40); PA, 38.90 (2.88) |
Srgaard, 2007 [69]b | 5 European nations | MBI | 18 | EE, 18.56 (9.32); DP, 5.50 (3.79); PA, 39.08 (5.39) | 22 | EE, 19.41 (8.08); DP, 6.68 (4.93); PA, 39.00 (4.40) |
Sosa Oberlin, 2007 [56]b | Argentina | Author‐designed instrument | 3 | 3 (100%) had 4 burnout symptoms, 8.67 symptoms per physician | 33 | 26 (78.8%) had 4 burnout symptoms, 6.15 symptoms per physician |
Voltmer, 2007 [57]b | Germany | AVEM | 271 | 77 (28.4%) exhibited burnout (type B) pattern | 46 | 11 (23.9%) exhibited burnout (type B) pattern |
dm, 2008 [70]b | Hungary | MBI | 194 | EE, 19.23 (10.79); DP, 4.88 (4.61); PA, 35.26 (8.42) | 163 | EE, 17.45 (11.12); DP, 4.86 (4.91); PA, 36.56 (7.03) |
Di Iorio, 2008 [71]b | Italy | Author‐designed instrument | 62 | Work: 3.1 (1.4); material: 3.3 (1.5); climate: 2.9 (1.1); objectives: 2.5 (1.5); quality: 3.0 (1.1); justification: 3.1 (2.1) | 54 | Work: 2.6 (1.5); material: 3.1 (2.1); climate: 3.0 (1.1); objectives: 3.4 (1.6); quality: 2.2 (1.5); justification: 3.2 (2.0) |
Bressi, 2009 [76]b | Italy | MBI | 28 | EE, 17.89 (14.46); DP, 5.32 (7.01); PA, 34.57 (11.27) | 53 | EE, 23.15 (11.99); DP, 7.02 (6.29); PA, 36.41 (7.54) |
Lasalvia, 2009[55]b | Italy | Modified MBI (16 items; scale, 06) | 21 | EE, 1.95 (1.04); DP, 1.35 (0.85); PA, 4.46 (1.04) | 38 | EE, 2.37 (1.27); DP, 1.51 (1.15); PA, 4.46 (0.87) |
Peisah, 2009 [79]b | Australia | MBI | 62 | EE, 20.09 (9.91); DP, 6.34 (4.90); PA, 35.06 (7.33) | 28 | EE, 13.92 (9.24); DP, 3.66 (3.95); PA, 39.34 (8.55) |
Shanafelt, 2009 [80]b | United States | MBI | 19 | EE, 25.2 (11.59); DP, 4.4 (3.79); PA, 38.5 (8.04) | 408 | EE, 20.5 (11.10); DP, 4.3 (4.74); PA, 40.8 (6.26) |
Lucas, 2011 [84]b | United States | MBI (EE only) | 26 | EE, 19.54 (12.85) | 30 | EE, 24.37 (14.95) |
Shanafelt, 2012 [87]b | United States | MBI | 130 | EE, 24.7 (12.5); DP, 9.1 (6.9); PA, 39.0 (7.6) | 447 | EE, 25.4 (14.0); DP, 7.5 (6.3); PA, 41.4 (6.0) |
Figure 2 shows that no significant difference existed between the groups regarding emotional exhaustion (mean difference, 0.11 points on a 54‐point scale; 95% confidence interval [CI], 2.40 to 2.61; P=0.94). In addition, there was no significant difference between the groups regarding depersonalization (Figure 3; mean difference, 0.00 points on a 30‐point scale; 95% CI, 1.03 to 1.02; P=0.99) and personal accomplishment (Figure 4; mean difference, 0.93 points on a 48‐point scale; 95% CI, 0.23 to 2.09; P=0.11).



We used meta‐regression to allow the incorporation of single‐armed MBI studies. Whether single‐armed studies were analyzed separately (15 outpatient studies comprising 3927 physicians, 4 inpatient studies comprising 300 physicians) or analyzed with double‐armed studies (24 outpatient arms comprising 5318 physicians, 13 inpatient arms comprising 1301 physicians), the lack of a significant difference between the groups persisted for the depersonalization and personal accomplishment scales (Figure 5). Emotional exhaustion was significantly higher in outpatient physicians when single‐armed studies were considered separately (mean difference, 6.36 points; 95% CI, 2.24 to 10.48; P=0.002), and this difference persisted when all studies were combined (mean difference, 3.00 points; 95% CI, 0.05 to 5.94, P=0.046).

Subgroup analysis by geographic location showed US outpatient physicians had a significantly higher personal accomplishment score than US inpatient physicians (mean difference, 2.38 points; 95% CI, 1.22 to 3.55; P<0.001) in double‐armed studies. This difference did not persist when single‐armed studies were included through meta‐regression (mean difference, 0.55 points, 95% CI, 4.30 to 5.40, P=0.83).
Table 4 demonstrates that methodological quality was generally good from the standpoint of the reporting and bias subsections of the Downs and Black tool. External validity was scored lower for many studies due to the use of convenience samples and lack of information about physicians who declined to participate.
Lead Author, Publication Year | Reporting | External Validity | Internal Validity: Bias | Internal Validity: Confounding | Power |
---|---|---|---|---|---|
Schweitzer, 1994 [12] | 5 of 6 points | 1 of 2 points | 3 of 4 points | 0 of 1 point | 0 of 1 point |
Varga, 1996 [88] | 5 of 6 points | 1 of 2 points | 3 of 4 points | 1 of 1 point | 0 of 1 point |
Aasland, 1997 [54] | 3 of 6 points | 2 of 2 points | 3 of 4 points | 1 of 1 point | 0 of 1 point |
Bargellini, 2000 [89] | 5 of 6 points | 0 of 2 points | 4 of 4 points | 1 of 1 point | 0 of 1 point |
Grassi, 2000 [58] | 6 of 6 points | 0 of 2 points | 3 of 4 points | 0 of 1 point | 0 of 1 point |
McManus, 2000 [59] | 5 of 6 points | 2 of 2 points | 4 of 4 points | 1 of 1 point | 0 of 1 point |
Hoff, 2001 [33] | 6 of 6 points | 2 of 2 points | 2 of 4 points | 1 of 1 point | 0 of 1 point |
Yaman, 2002 [60] | 5 of 6 points | 0 of 2 points | 4 of 4 points | 0 of 1 point | 0 of 1 point |
Cathbras, 2004 [61] | 6 of 6 points | 0 of 2 points | 4 of 4 points | 0 of 1 point | 0 of 1 point |
Kushnir, 2004 [62] | 5 of 6 points | 0 of 2 points | 3 of 4 points | 0 of 1 point | 0 of 1 point |
Goehring, 2005 [63] | 6 of 6 points | 1 of 2 points | 3 of 4 points | 1 of 1 point | 0 of 1 point |
Trichard, 2005 [90] | 3 of 6 points | 1 of 2 points | 3 of 4 points | 0 of 1 point | 0 of 1 point |
Esteva, 2006 [64] | 6 of 6 points | 2 of 2 points | 4 of 4 points | 1 of 1 point | 0 of 1 point |
Gandini, 2006 [65] | 6 of 6 points | 1 of 2 points | 3 of 4 points | 1 of 1 point | 0 of 1 point |
Ozyurt, 2006 [66] | 6 of 6 points | 2 of 2 points | 4 of 4 points | 1 of 1 point | 0 of 1 point |
Deighton, 2007 [67] | 5 of 6 points | 0 of 2 points | 4 of 4 points | 0 of 1 point | 0 of 1 point |
Dunwoodie, 2007 [68] | 5 of 6 points | 2 of 2 points | 4 of 4 points | 0 of 1 point | 0 of 1 point |
Srgaard, 2007 [69] | 6 of 6 points | 0 of 2 points | 3 of 4 points | 1 of 1 point | 1 of 1 point |
Sosa Oberlin, 2007 [56] | 4 of 6 points | 0 of 2 points | 3 of 4 points | 0 of 1 point | 0 of 1 point |
Voltmer, 2007 [57] | 4 of 6 points | 0 of 2 points | 4 of 4 points | 0 of 1 point | 0 of 1 point |
dm, 2008 [70] | 5 of 6 points | 2 of 2 points | 3 of 4 points | 1 of 1 point | 0 of 1 point |
Di Iorio, 2008 [71] | 6 of 6 points | 0 of 2 points | 2 of 4 points | 0 of 1 point | 0 of 1 point |
Fuss, 2008 [91] | 6 of 6 points | 0 of 2 points | 3 of 4 points | 0 of 1 point | 0 of 1 point |
Lee, 2008 [49] | 4 of 6 points | 2 of 2 points | 4 of 4 points | 0 of 1 point | 1 of 1 point |
Marner, 2008 [92] | 6 of 6 points | 0 of 2 points | 4 of 4 points | 0 of 1 point | 0 of 1 point |
Shehabi, 2008 [93] | 3 of 6 points | 1 of 2 points | 3 of 4 points | 0 of 1 point | 0 of 1 point |
Truchot, 2008 [72] | 5 of 6 points | 1 of 2 points | 3 of 4 points | 0 of 1 point | 0 of 1 point |
Twellaar, 2008 [73] | 6 of 6 points | 2 of 2 points | 3 of 4 points | 0 of 1 point | 0 of 1 point |
Vela‐Bueno, 2008 [74] | 5 of 6 points | 2 of 2 points | 4 of 4 points | 1 of 1 point | 0 of 1 point |
Arigoni, 2009 [17] | 6 of 6 points | 2 of 2 points | 4 of 4 points | 1 of 1 point | 0 of 1 point |
Bernhardt, 2009 [75] | 6 of 6 points | 2 of 2 points | 4 of 4 points | 1 of 1 point | 0 of 1 point |
Bressi, 2009 [76] | 6 of 6 points | 0 of 2 points | 3 of 4 points | 1 of 1 point | 0 of 1 point |
Brown, 2009 [94] | 6 of 6 points | 0 of 2 points | 4 of 4 points | 0 of 1 point | 0 of 1 point |
Krasner, 2009 [77] | 9 of 11 points | 0 of 3 points | 6 of 7 points | 1 of 2 points | 1 of 1 point |
Lasalvia, 2009 [55] | 6 of 6 points | 2 of 2 points | 4 of 4 points | 1 of 1 point | 0 of 1 point |
Lesic, 2009 [78] | 5 of 6 points | 0 of 2 points | 4 of 4 points | 0 of 1 point | 0 of 1 point |
Peisah, 2009 [79] | 6 of 6 points | 2 of 2 points | 3 of 4 points | 1 of 1 point | 0 of 1 point |
Shanafelt, 2009 [80] | 6 of 6 points | 2 of 2 points | 4 of 4 points | 1 of 1 point | 0 of 1 point |
Tunc, 2009 [95] | 6 of 6 points | 2 of 2 points | 4 of 4 points | 1 of 1 point | 0 of 1 point |
Zantinge, 2009 [81] | 5 of 6 points | 0 of 2 points | 3 of 4 points | 1 of 1 point | 0 of 1 point |
Cocco, 2010 [96] | 4 of 6 points | 0 of 2 points | 4 of 4 points | 0 of 1 point | 0 of 1 point |
Demirci, 2010 [82] | 6 of 6 points | 0 of 2 points | 4 of 4 points | 0 of 1 point | 0 of 1 point |
Voltmer, 2010 [83] | 6 of 6 points | 2 of 2 points | 4 of 4 points | 1 of 1 point | 0 of 1 point |
Doppia, 2011 [97] | 5 of 6 points | 2 of 2 points | 4 of 4 points | 1 of 1 point | 0 of 1 point |
Glasheen, 2011 [98] | 5 of 6 points | 0 of 2 points | 4 of 4 points | 1 of 1 point | 0 of 1 point |
Lucas, 2011 [84] | 10 of 11 points | 2 of 3 points | 7 of 7 points | 5 of 6 points | 1 of 1 point |
Maccacaro, 2011 [85] | 5 of 6 points | 0 of 2 points | 4 of 4 points | 1 of 1 point | 0 of 1 point |
Putnik, 2011 [86] | 6 of 6 points | 1 of 2 points | 4 of 4 points | 0 of 1 point | 0 of 1 point |
Thorsen, 2011 [99] | 6 of 6 points | 0 of 2 points | 4 of 4 points | 0 of 1 point | 0 of 1 point |
Hinami, 2012 [50] | 6 of 6 points | 2 of 2 points | 4 of 4 points | 1 of 1 point | 1 of 1 point |
Quenot, 2012 [100] | 8 of 11 points | 1 of 3 points | 6 of 7 points | 1 of 2 points | 0 of 1 point |
Ruitenburg, 2012 [101] | 6 of 6 points | 2 of 2 points | 4 of 4 points | 0 of 1 point | 0 of 1 point |
Seibt, 2012 [102] | 6 of 6 points | 0 of 2 points | 4 of 4 points | 1 of 1 point | 0 of 1 point |
Shanafelt, 2012 [87] | 6 of 6 points | 2 of 2 points | 4 of 4 points | 1 of 1 point | 0 of 1 point |
Funnel plots were used to evaluate for publication bias in the meta‐analysis of the 8 double‐armed studies (Figure 6). We found no significant evidence of bias, which was supported by Begg's test P values of 0.90 for emotional exhaustion, >0.99 for depersonalization, and 0.54 for personal accomplishment. A trim‐and‐fill analysis determined that no adjustment was necessary.

DISCUSSION
There appears to be no support for the long‐held belief that inpatient physicians are particularly prone to burnout. Among studies for which practice location was stated explicitly or could be obtained from the authors, and who used the MBI, no differences were found among inpatient and outpatient physicians with regard to depersonalization or personal accomplishment. This finding persisted whether double‐armed studies were compared directly, single‐armed studies were incorporated into this analysis, or single‐armed studies were analyzed separately. Outpatient physicians had a higher degree of emotional exhaustion when all studies were considered.
There are several reasons why outpatient physicians may be more prone to emotional exhaustion than their inpatient colleagues. Although it is by no means true that all inpatient physicians work in shifts, the increased availability of shift work may allow some inpatient physicians to better balance their professional and personal lives, a factor of work with which some outpatient physicians have struggled.[47] Inpatient practice may also afford more opportunity for teamwork, a factor that has been shown to correlate with reduced burnout.[48] When surveyed about burnout, outpatient physicians have cited patient volumes, paperwork, medicolegal concerns, and lack of community support as factors.[49] Inpatient physicians are not immune to these forces, but they arguably experience them to different degrees.
The absence of a higher rate of depersonalization among inpatient physicians is particularly reassuring in light of concerns expressed with the advent of US hospital medicinethat some hospitalists would be prone to viewing patients as an impediment to the efficient running of the hospital,[2] the very definition of depersonalization.
Although the difference in the whole sample was not statistically significant, the consistent tendency toward a greater sense of personal accomplishment among outpatient physicians is also noteworthy, particularly because post hoc subgroup analysis of US physicians did show statistical significance in both 2‐armed studies. Without detailed age data for the physicians in each study, we could not separate the possible impact of age on personal accomplishment; hospital medicine is a newer specialty staffed by generally younger physicians, and hospitalists may not have had time to develop a sense of accomplishment. When surveyed about job satisfaction, hospitalists have also reported the feeling that they were treated as glorified residents,[50] a factor that, if shared by other inpatient physicians, must surely affect their sense of personal accomplishment. The lack of longitudinal care for patients and the substantial provision of end‐of‐life care also may diminish the sense of personal accomplishment among inpatient physicians.
Another important finding from this systematic review is the marked heterogeneity of the instruments used to measure physician burnout. Many of the identified studies could not be subjected to meta‐analysis because of their use of differing burnout measures. Drawing more substantial conclusions about burnout and practice location is limited by the fact that, although the majority of studies used the full MBI, the largest study of European hospital doctors used the Copenhagen Burnout Inventory, and the studies thus far of US hospitalists have used single‐item surveys or portions of the MBI. Not reflected in this review is the fact that a large study of US burnout and job satisfaction[51] did not formally address practice location (M. Linzer, personal communication, August 2012). Similarly, a large study of British hospital doctors[52] is not included herein because many of the physicians involved had substantial outpatient duties (C. Taylor, personal communication, July 2012). Varying burnout measures have complicated a previous systematic review of burnout in oncologists.[53] Two studies that directly compared inpatient and outpatient physicians but that were excluded from our statistical analysis because of their modified versions of the MBI,[54, 55] showed higher burnout scores in outpatient physicians. Two other studies that provided direct inpatient versus outpatient comparisons but that used alternative burnout measures[56, 57] showed a greater frequency of burnout in inpatient physicians, but of these, 1 study[56] involved only 3 inpatient physicians.
Several limitations of our study should be considered. Although we endeavored to obtain information from authors (with some success) about specific local practice patterns and eliminated many studies because of incomplete data or mixed practice patterns (eg, general practitioners who take frequent hospital calls, hospital physicians with extensive outpatient duties in a clinic attached to their hospital), it remains likely that many physicians identified as outpatient provided some inpatient care (attending a few weeks per year on a teaching service, for example) and that some physicians identified as inpatient have minimal outpatient duties.
More importantly, the dataset analyzed is heterogeneous. Studies of the incidence of burnout are naturally observational and therefore not randomized. Inclusion of international studies is necessary to answer the research question (because published data on US hospitalists are sparse) but naturally introduces differences in practice settings, local factors, and other factors for which we cannot possibly account fully.
Our meta‐analysis therefore addressed a broad question about burnout among inpatient and outpatient physicians in various diverse settings. Applying it to any 1 population (including US hospitalists) is, by necessity, imprecise.
Post hoc analysis should be viewed with caution. For example, the finding of a statistical difference between US inpatient and outpatient physicians with regard to personal accomplishment score is compelling from the standpoint of hypothesis generation. However, it is worth bearing in mind that this analysis contained only 2 studies, both by the same primary author, and compared 855 outpatient physicians to only 149 hospitalists. This difference was no longer significant when 2 outpatient studies were added through meta‐regression.
Finally, the specific focus of this study on practice location precluded comparison with emergency physicians and anesthesiologists, 2 specialist types that have been the subject of particularly robust burnout literature. As the literature on hospitalist burnout becomes more extensive, comparative studies with these groups and with intensivists might prove instructive.
In summary, analysis of 24 studies comprising data on 5318 outpatient physicians and 1301 inpatient physicians provides no support for the commonly held belief that hospital‐based physicians are particularly prone to burnout. Outpatient physicians reported higher emotional exhaustion. Further studies of the incidence and severity of burnout according to practice location are indicated. We propose that in future studies, to avoid the difficulties with statistical analysis summarized herein, investigators ask about and explicitly report practice location (inpatient vs outpatient vs both) and report mean MBI subset data and standard deviations. Such information about US hospitalists would allow comparison with a robust (if heterogeneous) international literature on burnout.
Acknowledgments
The authors gratefully acknowledge all of the study authors who contributed clarification and guidance for this project, particularly the following authors who provided unpublished data for further analysis: Olaf Aasland, MD; Szilvia dm, PhD; Annalisa Bargellini, PhD; Cinzia Bressi, MD, PhD; Darrell Campbell Jr, MD; Ennio Cocco, MD; Russell Deighton, PhD; Senem Demirci Alanyali, MD; Biagio Di Iorio, MD, PhD; David Dunwoodie, MBBS; Sharon Einav, MD; Madeleine Estryn‐Behar, PhD; Bernardo Gandini, MD; Keiki Hinami, MD; Antonio Lasalvia, MD, PhD; Joseph Lee, MD; Guido Maccacaro, MD; Swati Marner, EdD; Chris McManus, MD, PhD; Carmelle Peisah, MBBS, MD; Katarina Putnik, MSc; Alfredo Rodrguez‐Muoz, PhD; Yahya Shehabi, MD; Evelyn Sosa Oberlin, MD; Jean Karl Soler, MD, MSc; Knut Srgaard, PhD; Cath Taylor; Viva Thorsen, MPH; Mascha Twellaar, MD; Edgar Voltmer, MD; Colin West, MD, PhD; and Deborah Whippen. The authors also thank the following colleagues for their help with translation: Dusanka Anastasijevic (Norwegian); Joyce Cheung‐Flynn, PhD (simplified Chinese); Ales Hlubocky, MD (Czech); Lena Jungheim, RN (Swedish); Erez Kessler (Hebrew); Kanae Mukai, MD (Japanese); Eliane Purchase (French); Aaron Shmookler, MD (Russian); Jan Stepanek, MD (German); Fernando Tondato, MD (Portuguese); Laszlo Vaszar, MD (Hungarian); and Joseph Verheidje, PhD (Dutch). Finally, the authors thank Cynthia Heltne and Diana Rogers for their expert and tireless library assistance, Bonnie Schimek for her help with figures, and Cindy Laureano and Elizabeth Jones for their help with author contact.
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Hospital medicine is a rapidly growing field of US clinical practice.[1] Almost since its advent, concerns have been expressed about the potential for hospitalists to burn out.[2] Hospitalists are not unique in this; similar concerns heralded the arrival of other location‐defined specialties, including emergency medicine[3] and the full‐time intensivist model,[4] a fact that has not gone unnoted in the literature about hospitalists.[5]
The existing international literature on physician burnout provides good reason for this concern. Inpatient‐based physicians tend to work unpredictable schedules, with substantial impact on home life.[6] They tend to be young, and much burnout literature suggests a higher risk among younger, less‐experienced physicians.[7] When surveyed, hospitalists have expressed more concerns about their potential for burnout than their outpatient‐based colleagues.[8]
In fact, data suggesting a correlation between inpatient practice and burnout predate the advent of the US hospitalist movement. Increased hospital time was reported to correlate with higher rates of burnout in internists,[9] family practitioners,[10] palliative physicians,[11] junior doctors,[12] radiologists,[13] and cystic fibrosis caregivers.[14] In 1987, Keinan and Melamed[15] noted, Hospital work by its very nature, as compared to the work of a general practitioner, deals with the more severe and complicated illnesses, coupled with continuous daily contacts with patients and their anxious families. In addition, these physicians may find themselves embroiled in the power struggles and competition so common in their work environment.
There are other features, however, that may protect inpatient physicians from burnout. Hospital practice can facilitate favorable social relations involving colleagues, co‐workers, and patients,[16] a factor that may be protective.[17] A hospitalist schedule also can allow more focused time for continuing medical education, research, and teaching,[18] which have all been associated with reduced risk of burnout in some studies.[17] Studies of psychiatrists[19] and pediatricians[20] have shown a lower rate of burnout among physicians with more inpatient duties. Finally, a practice model involving a seemingly stable cadre of inpatient physicians has existed in Europe for decades,[2] indicating at least a degree of sustainability.
Information suggesting a higher rate of burnout among inpatient physicians could be used to target therapeutic interventions and to adjust schedules, whereas the opposite outcome could refute a pervasive myth. We therefore endeavored to summarize the literature on burnout among inpatient versus outpatient physicians in a systematic fashion, and to include data not only from the US hospitalist experience but also from other countries that have used a similar model for decades. Our primary hypothesis was that inpatient physicians experience more burnout than outpatient physicians.
It is important to distinguish burnout from depression, job dissatisfaction, and occupational stress, all of which have been studied extensively in physicians. Burnout, as introduced by Freudenberger[21] and further characterized by Maslach,[22] is a condition in which emotional exhaustion, depersonalization, and a low sense of personal accomplishment combine to negatively affect work life (as opposed to clinical depression, which affects all aspects of life). Job satisfaction can correlate inversely with burnout, but it is a separate process[23] and the subject of a recent systematic review.[24] The importance of distinguishing burnout from job dissatisfaction is illustrated by a survey of head and neck surgeons, in which 97% of those surveyed indicated satisfaction with their jobs and 34% of the same group answered in the affirmative when asked if they felt burned out.[25]
One obstacle to the meaningful comparison of burnout prevalence across time, geography, and specialty is the myriad ways in which burnout is measured and reported. The oldest and most commonly used instrument to measure burnout is the Maslach Burnout Inventory (MBI), which contains 22 items assessing 3 components of burnout (emotional exhaustion, depersonalization, and low personal accomplishment).[26] Other measures include the Copenhagen Burnout Inventory[27] (19 items with the components personal burnout, work‐related burnout, and client‐related burnout), Utrecht Burnout Inventory[28] (20‐item modification of the MBI), Boudreau Burnout Questionnaire[29] (30 items), Arbeitsbezogenes Verhaltens und Erlebensmuster[30] (66‐item questionnaire assessing professional commitment, resistance to stress, and emotional well‐being), Shirom‐Melamed Burnout Measure[31] (22 items with subscales for physical fatigue, cognitive weariness, tension, and listlessness), and a validated single‐item questionnaire.[32]
METHODS
Electronic searches of MEDLINE, EMBASE, PsycINFO, SCOPUS, and PubMed were undertaken for articles published from January 1, 1974 (the year in which burnout was first described by Freudenberger[21]) to 2012 (last accessed, September 12, 2012) using the Medical Subject Headings (MeSH) terms stress, psychological; burnout, professional; adaptation, psychological; and the keyword burnout. The same sources were searched to create another set for the MeSH terms hospitalists, physician's practice patterns, physicians/px, professional practice location, and the keyword hospitalist#. Where exact subject headings did not exist in databases, comparable subject headings or keywords were used. The 2 sets were then combined using the operator and. Abstracts from the Society of Hospital Medicine annual conferences were hand‐searched, as were reference lists from identified articles. To ensure that pertinent international literature was captured, there was no language restriction in the search.
A 2‐stage screening process was used. The titles and abstracts of all articles identified in the search were independently reviewed by 2 investigators (D.L.R. and K.J.C.) who had no knowledge of each other's results. An article was obtained when either reviewer deemed it worthy of full‐text review.
All full‐text articles were independently reviewed by the same 2 investigators. The inclusion criterion was the measurement of burnout in physicians who are stated to or can be reasonably assumed to spend the substantial majority of their clinical practice exclusively in either the inpatient or the outpatient setting. Studies of emergency department physicians or specialists who invariably spend substantial amounts of time in both settings (eg, surgeons, anesthesiologists) were excluded. Studies limited to trainees or nonphysicians were also excluded. For both stages of review, agreement between the 2 investigators was assessed by calculating the statistic. Disagreements about inclusion were adjudicated by a third investigator (A.I.B.).
Because our goal was to establish and compare the rate of burnout among US hospitalists and other inpatient physicians around the world, we included studies of hospitalists according to the definition in use at the time of the individual study, noting that the formal definition of a hospitalist has changed over the years.[33] Because practice patterns for physicians described as primary care physicians, family doctors, hospital doctors, and others differ substantially from country to country, we otherwise included only the studies where the practice location was stated explicitly or where the authors confirmed that their study participants either are known or can be reasonably assumed to spend more than 75% of their time caring for hospital inpatients, or are known or can be reasonably assumed to spend the vast majority of their time caring for outpatients.
Data were abstracted using a standardized form and included the measure of burnout used in the study, results, practice location of study subjects, and total number of study subjects. When data were not clear (eg, burnout measured but not reported by the authors, practice location of study subjects not clear), authors were contacted by email, or when no current email address could be located or no response was received, by telephone or letter. In instances where burnout was measured repeatedly over time or before and after a specific intervention, only the baseline measurement was recorded. Because all studies were expected to be nonrandomized, methodological quality was assessed using a version of the tool of Downs and Black,[34] adapted where necessary by omitting questions not applicable to the specific study type (eg randomization for survey studies)[35] and giving a maximum of 1 point for the inclusion of a power calculation.
Two a priori analyses were planned: (1) a statistical comparison of articles directly comparing burnout among inpatient and outpatient physicians, and (2) a statistical comparison of articles measuring burnout among inpatient physicians with articles measuring burnout among outpatient physicians by the most frequently reported measuremean subset scores for emotional exhaustion, depersonalization, and personal accomplishment on the MBI.
The primary outcome measures were the differences between mean subset scores for emotional exhaustion, depersonalization, and personal accomplishment on the MBI. All differences are expressed as (outpatient meaninpatient mean). The variance of each outcome was calculated with standard formulas.[36] To calculate the overall estimate, each study was weighted by the reciprocal of its variance. Studies with fewer than 10 subjects were excluded from statistical analysis but retained in the systematic review.
For studies that reported data for both inpatient and outpatient physicians (double‐armed studies), Cochran Q test and the I2 value were used to assess heterogeneity.[37, 38] Substantial heterogeneity was expected because these individual studies were conducted for different populations in different settings with different study designs, and this expectation was confirmed statistically. Therefore, we used a random effects model to estimate the overall effect, providing a conservative approach that accounted for heterogeneity among studies.[39]
To assess the durability of our findings, we performed separate multivariate meta‐regression analyses by including single‐armed studies only and including both single‐armed and double‐armed studies. For these meta‐regressions, means were again weighted by the reciprocal of their variances, and the arms of 2‐armed studies were considered separately. This approach allowed us to generate an estimate of the differences between MBI subset scores from studies that did not include such an estimate when analyzed separately.[40]
We examined the potential for publication bias in double‐armed studies by constructing a funnel plot, in which mean scores were plotted against their standard errors.[41] The trim‐and‐fill method was used to determine whether adjustment for publication bias was necessary. In addition, Begg's rank correlation test[42] was completed to test for statistically significant publication bias.
Stata 10.0 statistical software (StataCorp, College Station, TX) was used for data analyses. A P value of 0.05 or less was deemed statistically significant. The Preferred Reporting Items for Systematic Reviews and Meta‐analysis checklist was used for the design and execution of the systematic review and meta‐analysis.[43]
Subgroup analyses based on location were undertaken a posteriori. All data (double‐armed meta‐analysis, meta‐regression of single‐armed studies, and meta‐regression of single‐ and double‐armed studies) were analyzed by location (United States vs other; United States vs Europe vs other).
RESULTS
The search results are outlined in Figure 1. In total, 1704 articles met the criteria for full‐text review. A review of pertinent reference lists and author contacts led to the addition of 149 articles. Twenty‐nine references could not be located by any means, despite repeated attempts. Therefore, 1824 articles were subjected to full‐text review by the 2 investigators.

Initially, 57 articles were found that met criteria for inclusion. Of these, 2 articles reported data in formats that could not be interpreted.[44, 45] When efforts to clarify the data with the authors were unsuccessful, these studies were excluded. A study specifically designed to assess the response of physicians to a recent series of terrorist attacks[46] was excluded a posteriori because of lack of generalizability. Of the other 54 studies, 15 reported burnout data on both outpatient physicians and inpatient physicians, 22 reported data on outpatient physicians only, and 17 reported data on inpatient physicians only. Table 1 summarizes the results of the 37 studies involving outpatient physicians; Table 2 summarizes the 32 studies involving inpatient physicians.
Lead Author, Publication Year | Study Population and Location | Instrument | No. of Participants | EE Score (SD)a | DP Score (SD) | PA Score (SD) | Other Results |
---|---|---|---|---|---|---|---|
| |||||||
Schweitzer, 1994[12] | Young physicians of various specialties in South Africa | Single‐item survey | 7 | 6 (83%) endorsed burnout | |||
Aasland, 1997 [54]b | General practitioners in Norway | Modified MBI (22 items; scale, 15) | 298 | 2.65 (0.80) | 1.90 (0.59) | 3.45 (0.40) | |
Grassi, 2000 [58] | General practitioners in Italy | MBI | 182 | 18.49 (11.49) | 6.11 (5.86) | 38.52 (7.60) | |
McManus, 2000 [59]b | General practitioners in United Kingdom | Modified MBI (9 items; scale, 06) | 800 | 8.34 (4.39) | 3.18 (3.40) | 14.16 (2.95) | |
Yaman, 2002 [60] | General practitioners in 8 European nations | MBI | 98 | 25.1 (8.50) | 7.3 (4.92) | 34.5 (7.67) | |
Cathbras, 2004 [61] | General practitioners in France | MBI | 306 | 21.85 (12.4) | 9.13 (6.7) | 38.7 (7.1) | |
Goehring, 2005 [63] | General practitioners, general internists, pediatricians in Switzerland | MBI | 1755 | 17.9 (9.8) | 6.5 (4.7) | 39.6 (6.5) | |
Esteva, 2006 [64] | General practitioners, pediatricians in Spain | MBI | 261 | 27.4 (11.8) | 10.07 (6.4) | 35.9 (7.06) | |
Gandini, 2006 [65]b | Physicians of various specialties in Argentina | MBI | 67 | 31.0 (13.8) | 10.2 (6.6) | 38.4 (6.8) | |
Ozyurt, 2006 [66] | General practitioners in Turkey | Modified MBI (22 items; scale, 04) | 55 | 15.23 (5.80) | 4.47 (3.31) | 23.38 (4.29) | |
Deighton, 2007 [67]b | Psychiatrists in several German‐speaking nations | MBI | 19 | 30.68 (9.92) | 13.42 (4.23) | 37.16 (3.39) | |
Dunwoodie, 2007 [68]b | Palliative care physicians in Australia | MBI | 21 | 14.95 (9.14) | 3.95 (3.40) | 38.90 (2.88) | |
Srgaard, 2007 [69]b | Psychiatrists in 5 European nations | MBI | 22 | 19.41 (8.08) | 6.68 (4.93) | 39.00 (4.40) | |
Sosa Oberlin, 2007 [56]b | Physicians of various specialties in Argentina | Author‐designed instrument | 33 | 26 (78.8%) had 4 burnout symptoms, 6.15 symptoms per physician | |||
Voltmer, 2007 [57]b | Physicians of various specialties in Germany | AVEM | 46 | 11 (23.9%) exhibited burnout (type B) pattern | |||
dm, 2008 [70]b | Physicians of various specialties in Hungary | MBI | 163 | 17.45 (11.12) | 4.86 (4.91) | 36.56 (7.03) | |
Di Iorio, 2008 [71]b | Dialysis physicians in Italy | Author‐designed instrument | 54 | Work: 2.6 (1.5), Material: 3.1 (2.1), Climate: 3.0 (1.1), Objectives: 3.4 (1.6), Quality: 2.2 (1.5), Justification: 3.2 (2.0) | |||
Lee, 2008 [49]b | Family physicians in Canada | MBI | 123 | 26.26 (9.53) | 10.20 (5.22) | 38.43 (7.34) | |
Truchot, 2008 [72] | General practitioners in France | MBI | 259 | 25.4 (11.7) | 7.5 (5.5) | 36.5 (7.1) | |
Twellaar, 2008 [73]b | General practitioners in the Netherlands | Utrecht Burnout Inventory | 349 | 2.06 (1.11) | 1.71 (1.05) | 5.08 (0.77) | |
Arigoni, 2009 [17] | General practitioners, pediatricians in Switzerland | MBI | 258 | 22.8 (12.0) | 6.9 (6.1) | 39.0 (7.2) | |
Bernhardt, 2009 [75] | Clinical geneticists in United States | MBI | 72 | 25.8 (10.01)c | 10.9 (4.16)c | 34.8 (5.43)c | |
Bressi, 2009 [76]b | Psychiatrists in Italy | MBI | 53 | 23.15 (11.99) | 7.02 (6.29) | 36.41 (7.54) | |
Krasner, 2009 [77] | General practitioners in United States | MBI | 60 | 26.8 (10.9)d | 8.4 (5.1)d | 40.2 (5.3)d | |
Lasalvia, 2009 [55]b | Psychiatrists in Italy | Modified MBI (16 items; scale, 06) | 38 | 2.37 (1.27) | 1.51 (1.15) | 4.46 (0.87) | |
Peisah, 2009 [79]b | Physicians of various specialties in Australia | MBI | 28 | 13.92 (9.24) | 3.66 (3.95) | 39.34 (8.55) | |
Shanafelt, 2009 [80]b | Physicians of various specialties in United States | MBI | 408 | 20.5 (11.10) | 4.3 (4.74) | 40.8 (6.26) | |
Zantinge, 2009 [81] | General practitioners in the Netherlands | Utrecht Burnout Inventory | 126 | 1.58 (0.79) | 1.32 (0.72) | 4.27 (0.77) | |
Voltmer, 2010 [83]b | Psychiatrists in Germany | AVEM | 526 | 114 (21.7%) exhibited burnout (type B) pattern | |||
Maccacaro, 2011 [85]b | Physicians of various specialties in Italy | MBI | 42 | 14.31 (11.98) | 3.62 (4.95) | 38.24 (6.22) | |
Lucas, 2011 [84]b | Outpatient physicians periodically staffing an academic hospital teaching service in United States | MBI (EE only) | 30 | 24.37 (14.95) | |||
Shanafelt, 2012 [87]b | General internists in United States | MBI | 447 | 25.4 (14.0) | 7.5 (6.3) | 41.4 (6.0) | |
Kushnir, 2004 [62] | General practitioners and pediatricians in Israel | MBI (DP only) and SMBM | 309 | 9.15 (3.95) | SMBM mean (SD), 2.73 per item (0.86) | ||
Vela‐Bueno, 2008 [74]b | General practitioners in Spain | MBI | 240 | 26.91 (11.61) | 9.20 (6.35) | 35.92 (7.92) | |
Lesic, 2009 [78]b | General practitioners in Serbia | MBI | 38 | 24.71 (10.81) | 7.47 (5.51) | 37.21 (7.44) | |
Demirci, 2010 [82]b | Medical specialists related to oncology practice in Hungary | MBI | 26 | 23.31 (11.2) | 6.46 (5.7) | 37.7 (8.14) | |
Putnik, 2011 [86]b | General practitioners in Hungary | MBI | 370 | 22.22 (11.75) | 3.66 (4.40) | 41.40 (6.85) |
Lead Author, Publication Year | Study Population and Location | Instrument | No. of Participants | EE Score (SD)a | DP Score (SD) | PA Score (SD) | Other Results |
---|---|---|---|---|---|---|---|
| |||||||
Varga, 1996 [88] | Hospital doctors in Spain | MBI | 179 | 21.61b | 7.33b | 35.28b | |
Aasland, 1997 [54] | Hospital doctors in Norway | Modified MBI (22 items; scale, 15) | 582 | 2.39 (0.80) | 1.81 (0.65) | 3.51 (0.46) | |
Bargellini, 2000 [89] | Hospital doctors in Italy | MBI | 51 | 17.45 (9.87) | 7.06 (5.54) | 35.33 (7.90) | |
Grassi, 2000 [58] | Hospital doctors in Italy | MBI | 146 | 16.17 (9.64) | 5.32 (4.76) | 38.71 (7.28) | |
Hoff, 2001 [33] | Hospitalists in United States | Single‐item surveyc | 393 | 12.9% burned out (>4/5), 24.9% at risk for burnout (34/5), 62.2% at no current risk (mean, 2.86 on 15 scale) | |||
Trichard, 2005 [90] | Hospital doctors in France | MBI | 199 | 16 (10.7) | 6.6 (5.7) | 38.5 (6.5) | |
Gandini, 2006 [65]d | Hospital doctors in Argentina | MBI | 290 | 25.0 (12.7) | 7.9 (6.2) | 40.1 (7.0) | |
Dunwoodie, 2007 [68]d | Palliative care doctors in Australia | MBI | 14 | 18.29 (14.24) | 5.29 (5.89) | 38.86 (3.42) | |
Srgaard, 2007 [69]d | Psychiatrists in 5 European nations | MBI | 18 | 18.56 (9.32) | 5.50 (3.79) | 39.08 (5.39) | |
Sosa Oberlin, 2007 [56]d | Hospital doctors in Argentina | Author‐designed instrument | 3 | 3 (100%) had 4 burnout symptoms, 8.67 symptoms per physician | |||
Voltmer, 2007 [57]d | Hospital doctors in Germany | AVEM | 271 | 77 (28.4%) exhibited burnout (type B) pattern | |||
dm, 2008 [70]b | Physicians of various specialties in Hungary | MBI | 194 | 19.23 (10.79) | 4.88 (4.61) | 35.26 (8.42) | |
Di Iorio, 2008 [71]d | Dialysis physicians in Italy | Author‐designed instrument | 62 | Work, mean (SD), 3.1 (1.4); Material, mean (SD), 3.3 (1.5); Climate, mean (SD), 2.9 (1.1); Objectives, mean (SD), 2.5 (1.5); Quality, mean (SD), 3.0 (1.1); Justification, mean (SD), 3.1 (2.1) | |||
Fuss, 2008 [91]d | Hospital doctors in Germany | Copenhagen Burnout Inventory | 292 | Mean Copenhagen Burnout Inventory, mean (SD), 46.90 (18.45) | |||
Marner, 2008 [92]d | Psychiatrists and 1 generalist in United States | MBI | 9 | 20.67 (9.75) | 7.78 (5.14) | 35.33 (6.44) | |
Shehabi, 2008 [93]d | Intensivists in Australia | Modified MBI (6 items; scale, 15) | 86 | 2.85 (0.93) | 2.64 (0.85) | 2.58 (0.83) | |
Bressi, 2009 [76]d | Psychiatrists in Italy | MBI | 28 | 17.89 (14.46) | 5.32 (7.01) | 34.57 (11.27) | |
Brown, 2009 [94] | Hospital doctors in Australia | MBI | 12 | 22.25 (8.59) | 6.33 (2.71) | 39.83 (7.31) | |
Lasalvia, 2009 [55]d | Psychiatrists in Italy | Modified MBI (16 items; scale, 06) | 21 | 1.95 (1.04) | 1.35 (0.85) | 4.46 (1.04) | |
Peisah, 2009 [79]d | Hospital doctors in Australia | MBI | 62 | 20.09 (9.91) | 6.34 (4.90) | 35.06 (7.33) | |
Shanafelt, 2009 [80]d | Hospitalists and intensivists in United States | MBI | 19 | 25.2 (11.59) | 4.4 (3.79) | 38.5 (8.04) | |
Tunc, 2009 [95] | Hospital doctors in Turkey | Modified MBI (22 items; scale, 04) | 62 | 1.18 (0.78) | 0.81 (0.73) | 3.10 (0.59)e | |
Cocco, 2010 [96]d | Hospital geriatricians in Italy | MBI | 38 | 16.21 (11.56) | 4.53 (4.63) | 39.13 (7.09) | |
Doppia, 2011 [97]d | Hospital doctors in France | Copenhagen Burnout Inventory | 1,684 | Mean work‐related burnout score, 2.72 (0.75) | |||
Glasheen, 2011 [98] | Hospitalists in United States | Single‐item survey | 265 | Mean, 2.08 on 15 scale 62 (23.4%) burned out | |||
Lucas, 2011 [84]d | Academic hospitalists in United States | MBI (EE only) | 26 | 19.54 (12.85) | |||
Thorsen, 2011 [99] | Hospital doctors in Malawi | MBI | 2 | 25.5 (4.95) | 8.5 (6.36) | 25.0 (5.66) | |
Hinami, 2012 [50]d | Hospital doctors in United States | Single‐item survey | 793 | Mean, 2.24 on 15 scale 261 (27.2%) burned out | |||
Quenot, 2012 [100]d | Intensivists in France | MBI | 4 | 33.25 (4.57) | 13.50 (5.45) | 35.25 (4.86) | |
Ruitenburg, 2012 [101] | Hospital doctors in the Netherlands | MBI (EE and DP only) | 214 | 13.3 (8.0) | 4.5 (4.1) | ||
Seibt, 2012 [102]d | Hospital doctors in Germany | Modified MBI (16 items; scale, 06, reported per item rather than totals) | 2,154 | 2.2 (1.4) | 1.4 (1.2) | 5.1 (0.9) | |
Shanafelt, 2012 [87]d | Hospitalists in United States | MBI | 130 | 24.7 (12.5) | 9.1 (6.9) | 39.0 (7.6) |
Table 3 summarizes the results of the 15 studies that reported burnout data for both inpatient and outpatient physicians, allowing direct comparisons to be made. Nine studies reported MBI subset totals with standard deviations, 2 used different modifications of the MBI, 2 used different author‐derived measures, 1 used only the emotional exhaustion subscale of the MBI, and 1 used the Arbeitsbezogenes Verhaltens und Erlebensmuster. Therefore, statistical comparison was attempted only for the 9 studies reporting comparable MBI data, comprising burnout data on 1390 outpatient physicians and 899 inpatient physicians.
Lead Author, Publication Year | Location | Instrument | Inpatient‐Based Physicians | Outpatient‐Based Physicians | ||
---|---|---|---|---|---|---|
No. | Results, Score (SD)a | No. | Results, Score (SD)a | |||
| ||||||
Aasland, 1997 [54]b | Norway | Modified MBI (22 items; scale, 15) | 582 | EE, 2.39 (0.80); DP, 1.81 (0.65); PA, 3.51 (0.46) | 298 | EE, 2.65 (0.80); DP, 1.90 (0.59); PA, 3.45 (0.40) |
Grassi, 2000 [58] | Italy | MBI | 146 | EE, 16.17 (9.64); DP, 5.32 (4.76); PA, 38.71 (7.28) | 182 | EE, 18.49 (11.49); DP, 6.11 (5.86); PA, 38.52 (7.60) |
Gandini, 2006 [65]b | Argentina | MBI | 290 | EE, 25.0 (12.7);DP, 7.9 (6.2); PA, 40.1 (7.0) | 67 | EE, 31.0 (13.8); DP, 10.2 (6.6); PA, 38.4 (6.8) |
Dunwoodie, 2007 [68]b | Australia | MBI | 14 | EE, 18.29 (14.24); DP, 5.29 (5.89); PA, 38.86 (3.42) | 21 | EE, 14.95 (9.14); DP, 3.95 (3.40); PA, 38.90 (2.88) |
Srgaard, 2007 [69]b | 5 European nations | MBI | 18 | EE, 18.56 (9.32); DP, 5.50 (3.79); PA, 39.08 (5.39) | 22 | EE, 19.41 (8.08); DP, 6.68 (4.93); PA, 39.00 (4.40) |
Sosa Oberlin, 2007 [56]b | Argentina | Author‐designed instrument | 3 | 3 (100%) had 4 burnout symptoms, 8.67 symptoms per physician | 33 | 26 (78.8%) had 4 burnout symptoms, 6.15 symptoms per physician |
Voltmer, 2007 [57]b | Germany | AVEM | 271 | 77 (28.4%) exhibited burnout (type B) pattern | 46 | 11 (23.9%) exhibited burnout (type B) pattern |
dm, 2008 [70]b | Hungary | MBI | 194 | EE, 19.23 (10.79); DP, 4.88 (4.61); PA, 35.26 (8.42) | 163 | EE, 17.45 (11.12); DP, 4.86 (4.91); PA, 36.56 (7.03) |
Di Iorio, 2008 [71]b | Italy | Author‐designed instrument | 62 | Work: 3.1 (1.4); material: 3.3 (1.5); climate: 2.9 (1.1); objectives: 2.5 (1.5); quality: 3.0 (1.1); justification: 3.1 (2.1) | 54 | Work: 2.6 (1.5); material: 3.1 (2.1); climate: 3.0 (1.1); objectives: 3.4 (1.6); quality: 2.2 (1.5); justification: 3.2 (2.0) |
Bressi, 2009 [76]b | Italy | MBI | 28 | EE, 17.89 (14.46); DP, 5.32 (7.01); PA, 34.57 (11.27) | 53 | EE, 23.15 (11.99); DP, 7.02 (6.29); PA, 36.41 (7.54) |
Lasalvia, 2009[55]b | Italy | Modified MBI (16 items; scale, 06) | 21 | EE, 1.95 (1.04); DP, 1.35 (0.85); PA, 4.46 (1.04) | 38 | EE, 2.37 (1.27); DP, 1.51 (1.15); PA, 4.46 (0.87) |
Peisah, 2009 [79]b | Australia | MBI | 62 | EE, 20.09 (9.91); DP, 6.34 (4.90); PA, 35.06 (7.33) | 28 | EE, 13.92 (9.24); DP, 3.66 (3.95); PA, 39.34 (8.55) |
Shanafelt, 2009 [80]b | United States | MBI | 19 | EE, 25.2 (11.59); DP, 4.4 (3.79); PA, 38.5 (8.04) | 408 | EE, 20.5 (11.10); DP, 4.3 (4.74); PA, 40.8 (6.26) |
Lucas, 2011 [84]b | United States | MBI (EE only) | 26 | EE, 19.54 (12.85) | 30 | EE, 24.37 (14.95) |
Shanafelt, 2012 [87]b | United States | MBI | 130 | EE, 24.7 (12.5); DP, 9.1 (6.9); PA, 39.0 (7.6) | 447 | EE, 25.4 (14.0); DP, 7.5 (6.3); PA, 41.4 (6.0) |
Figure 2 shows that no significant difference existed between the groups regarding emotional exhaustion (mean difference, 0.11 points on a 54‐point scale; 95% confidence interval [CI], 2.40 to 2.61; P=0.94). In addition, there was no significant difference between the groups regarding depersonalization (Figure 3; mean difference, 0.00 points on a 30‐point scale; 95% CI, 1.03 to 1.02; P=0.99) and personal accomplishment (Figure 4; mean difference, 0.93 points on a 48‐point scale; 95% CI, 0.23 to 2.09; P=0.11).



We used meta‐regression to allow the incorporation of single‐armed MBI studies. Whether single‐armed studies were analyzed separately (15 outpatient studies comprising 3927 physicians, 4 inpatient studies comprising 300 physicians) or analyzed with double‐armed studies (24 outpatient arms comprising 5318 physicians, 13 inpatient arms comprising 1301 physicians), the lack of a significant difference between the groups persisted for the depersonalization and personal accomplishment scales (Figure 5). Emotional exhaustion was significantly higher in outpatient physicians when single‐armed studies were considered separately (mean difference, 6.36 points; 95% CI, 2.24 to 10.48; P=0.002), and this difference persisted when all studies were combined (mean difference, 3.00 points; 95% CI, 0.05 to 5.94, P=0.046).

Subgroup analysis by geographic location showed US outpatient physicians had a significantly higher personal accomplishment score than US inpatient physicians (mean difference, 2.38 points; 95% CI, 1.22 to 3.55; P<0.001) in double‐armed studies. This difference did not persist when single‐armed studies were included through meta‐regression (mean difference, 0.55 points, 95% CI, 4.30 to 5.40, P=0.83).
Table 4 demonstrates that methodological quality was generally good from the standpoint of the reporting and bias subsections of the Downs and Black tool. External validity was scored lower for many studies due to the use of convenience samples and lack of information about physicians who declined to participate.
Lead Author, Publication Year | Reporting | External Validity | Internal Validity: Bias | Internal Validity: Confounding | Power |
---|---|---|---|---|---|
Schweitzer, 1994 [12] | 5 of 6 points | 1 of 2 points | 3 of 4 points | 0 of 1 point | 0 of 1 point |
Varga, 1996 [88] | 5 of 6 points | 1 of 2 points | 3 of 4 points | 1 of 1 point | 0 of 1 point |
Aasland, 1997 [54] | 3 of 6 points | 2 of 2 points | 3 of 4 points | 1 of 1 point | 0 of 1 point |
Bargellini, 2000 [89] | 5 of 6 points | 0 of 2 points | 4 of 4 points | 1 of 1 point | 0 of 1 point |
Grassi, 2000 [58] | 6 of 6 points | 0 of 2 points | 3 of 4 points | 0 of 1 point | 0 of 1 point |
McManus, 2000 [59] | 5 of 6 points | 2 of 2 points | 4 of 4 points | 1 of 1 point | 0 of 1 point |
Hoff, 2001 [33] | 6 of 6 points | 2 of 2 points | 2 of 4 points | 1 of 1 point | 0 of 1 point |
Yaman, 2002 [60] | 5 of 6 points | 0 of 2 points | 4 of 4 points | 0 of 1 point | 0 of 1 point |
Cathbras, 2004 [61] | 6 of 6 points | 0 of 2 points | 4 of 4 points | 0 of 1 point | 0 of 1 point |
Kushnir, 2004 [62] | 5 of 6 points | 0 of 2 points | 3 of 4 points | 0 of 1 point | 0 of 1 point |
Goehring, 2005 [63] | 6 of 6 points | 1 of 2 points | 3 of 4 points | 1 of 1 point | 0 of 1 point |
Trichard, 2005 [90] | 3 of 6 points | 1 of 2 points | 3 of 4 points | 0 of 1 point | 0 of 1 point |
Esteva, 2006 [64] | 6 of 6 points | 2 of 2 points | 4 of 4 points | 1 of 1 point | 0 of 1 point |
Gandini, 2006 [65] | 6 of 6 points | 1 of 2 points | 3 of 4 points | 1 of 1 point | 0 of 1 point |
Ozyurt, 2006 [66] | 6 of 6 points | 2 of 2 points | 4 of 4 points | 1 of 1 point | 0 of 1 point |
Deighton, 2007 [67] | 5 of 6 points | 0 of 2 points | 4 of 4 points | 0 of 1 point | 0 of 1 point |
Dunwoodie, 2007 [68] | 5 of 6 points | 2 of 2 points | 4 of 4 points | 0 of 1 point | 0 of 1 point |
Srgaard, 2007 [69] | 6 of 6 points | 0 of 2 points | 3 of 4 points | 1 of 1 point | 1 of 1 point |
Sosa Oberlin, 2007 [56] | 4 of 6 points | 0 of 2 points | 3 of 4 points | 0 of 1 point | 0 of 1 point |
Voltmer, 2007 [57] | 4 of 6 points | 0 of 2 points | 4 of 4 points | 0 of 1 point | 0 of 1 point |
dm, 2008 [70] | 5 of 6 points | 2 of 2 points | 3 of 4 points | 1 of 1 point | 0 of 1 point |
Di Iorio, 2008 [71] | 6 of 6 points | 0 of 2 points | 2 of 4 points | 0 of 1 point | 0 of 1 point |
Fuss, 2008 [91] | 6 of 6 points | 0 of 2 points | 3 of 4 points | 0 of 1 point | 0 of 1 point |
Lee, 2008 [49] | 4 of 6 points | 2 of 2 points | 4 of 4 points | 0 of 1 point | 1 of 1 point |
Marner, 2008 [92] | 6 of 6 points | 0 of 2 points | 4 of 4 points | 0 of 1 point | 0 of 1 point |
Shehabi, 2008 [93] | 3 of 6 points | 1 of 2 points | 3 of 4 points | 0 of 1 point | 0 of 1 point |
Truchot, 2008 [72] | 5 of 6 points | 1 of 2 points | 3 of 4 points | 0 of 1 point | 0 of 1 point |
Twellaar, 2008 [73] | 6 of 6 points | 2 of 2 points | 3 of 4 points | 0 of 1 point | 0 of 1 point |
Vela‐Bueno, 2008 [74] | 5 of 6 points | 2 of 2 points | 4 of 4 points | 1 of 1 point | 0 of 1 point |
Arigoni, 2009 [17] | 6 of 6 points | 2 of 2 points | 4 of 4 points | 1 of 1 point | 0 of 1 point |
Bernhardt, 2009 [75] | 6 of 6 points | 2 of 2 points | 4 of 4 points | 1 of 1 point | 0 of 1 point |
Bressi, 2009 [76] | 6 of 6 points | 0 of 2 points | 3 of 4 points | 1 of 1 point | 0 of 1 point |
Brown, 2009 [94] | 6 of 6 points | 0 of 2 points | 4 of 4 points | 0 of 1 point | 0 of 1 point |
Krasner, 2009 [77] | 9 of 11 points | 0 of 3 points | 6 of 7 points | 1 of 2 points | 1 of 1 point |
Lasalvia, 2009 [55] | 6 of 6 points | 2 of 2 points | 4 of 4 points | 1 of 1 point | 0 of 1 point |
Lesic, 2009 [78] | 5 of 6 points | 0 of 2 points | 4 of 4 points | 0 of 1 point | 0 of 1 point |
Peisah, 2009 [79] | 6 of 6 points | 2 of 2 points | 3 of 4 points | 1 of 1 point | 0 of 1 point |
Shanafelt, 2009 [80] | 6 of 6 points | 2 of 2 points | 4 of 4 points | 1 of 1 point | 0 of 1 point |
Tunc, 2009 [95] | 6 of 6 points | 2 of 2 points | 4 of 4 points | 1 of 1 point | 0 of 1 point |
Zantinge, 2009 [81] | 5 of 6 points | 0 of 2 points | 3 of 4 points | 1 of 1 point | 0 of 1 point |
Cocco, 2010 [96] | 4 of 6 points | 0 of 2 points | 4 of 4 points | 0 of 1 point | 0 of 1 point |
Demirci, 2010 [82] | 6 of 6 points | 0 of 2 points | 4 of 4 points | 0 of 1 point | 0 of 1 point |
Voltmer, 2010 [83] | 6 of 6 points | 2 of 2 points | 4 of 4 points | 1 of 1 point | 0 of 1 point |
Doppia, 2011 [97] | 5 of 6 points | 2 of 2 points | 4 of 4 points | 1 of 1 point | 0 of 1 point |
Glasheen, 2011 [98] | 5 of 6 points | 0 of 2 points | 4 of 4 points | 1 of 1 point | 0 of 1 point |
Lucas, 2011 [84] | 10 of 11 points | 2 of 3 points | 7 of 7 points | 5 of 6 points | 1 of 1 point |
Maccacaro, 2011 [85] | 5 of 6 points | 0 of 2 points | 4 of 4 points | 1 of 1 point | 0 of 1 point |
Putnik, 2011 [86] | 6 of 6 points | 1 of 2 points | 4 of 4 points | 0 of 1 point | 0 of 1 point |
Thorsen, 2011 [99] | 6 of 6 points | 0 of 2 points | 4 of 4 points | 0 of 1 point | 0 of 1 point |
Hinami, 2012 [50] | 6 of 6 points | 2 of 2 points | 4 of 4 points | 1 of 1 point | 1 of 1 point |
Quenot, 2012 [100] | 8 of 11 points | 1 of 3 points | 6 of 7 points | 1 of 2 points | 0 of 1 point |
Ruitenburg, 2012 [101] | 6 of 6 points | 2 of 2 points | 4 of 4 points | 0 of 1 point | 0 of 1 point |
Seibt, 2012 [102] | 6 of 6 points | 0 of 2 points | 4 of 4 points | 1 of 1 point | 0 of 1 point |
Shanafelt, 2012 [87] | 6 of 6 points | 2 of 2 points | 4 of 4 points | 1 of 1 point | 0 of 1 point |
Funnel plots were used to evaluate for publication bias in the meta‐analysis of the 8 double‐armed studies (Figure 6). We found no significant evidence of bias, which was supported by Begg's test P values of 0.90 for emotional exhaustion, >0.99 for depersonalization, and 0.54 for personal accomplishment. A trim‐and‐fill analysis determined that no adjustment was necessary.

DISCUSSION
There appears to be no support for the long‐held belief that inpatient physicians are particularly prone to burnout. Among studies for which practice location was stated explicitly or could be obtained from the authors, and who used the MBI, no differences were found among inpatient and outpatient physicians with regard to depersonalization or personal accomplishment. This finding persisted whether double‐armed studies were compared directly, single‐armed studies were incorporated into this analysis, or single‐armed studies were analyzed separately. Outpatient physicians had a higher degree of emotional exhaustion when all studies were considered.
There are several reasons why outpatient physicians may be more prone to emotional exhaustion than their inpatient colleagues. Although it is by no means true that all inpatient physicians work in shifts, the increased availability of shift work may allow some inpatient physicians to better balance their professional and personal lives, a factor of work with which some outpatient physicians have struggled.[47] Inpatient practice may also afford more opportunity for teamwork, a factor that has been shown to correlate with reduced burnout.[48] When surveyed about burnout, outpatient physicians have cited patient volumes, paperwork, medicolegal concerns, and lack of community support as factors.[49] Inpatient physicians are not immune to these forces, but they arguably experience them to different degrees.
The absence of a higher rate of depersonalization among inpatient physicians is particularly reassuring in light of concerns expressed with the advent of US hospital medicinethat some hospitalists would be prone to viewing patients as an impediment to the efficient running of the hospital,[2] the very definition of depersonalization.
Although the difference in the whole sample was not statistically significant, the consistent tendency toward a greater sense of personal accomplishment among outpatient physicians is also noteworthy, particularly because post hoc subgroup analysis of US physicians did show statistical significance in both 2‐armed studies. Without detailed age data for the physicians in each study, we could not separate the possible impact of age on personal accomplishment; hospital medicine is a newer specialty staffed by generally younger physicians, and hospitalists may not have had time to develop a sense of accomplishment. When surveyed about job satisfaction, hospitalists have also reported the feeling that they were treated as glorified residents,[50] a factor that, if shared by other inpatient physicians, must surely affect their sense of personal accomplishment. The lack of longitudinal care for patients and the substantial provision of end‐of‐life care also may diminish the sense of personal accomplishment among inpatient physicians.
Another important finding from this systematic review is the marked heterogeneity of the instruments used to measure physician burnout. Many of the identified studies could not be subjected to meta‐analysis because of their use of differing burnout measures. Drawing more substantial conclusions about burnout and practice location is limited by the fact that, although the majority of studies used the full MBI, the largest study of European hospital doctors used the Copenhagen Burnout Inventory, and the studies thus far of US hospitalists have used single‐item surveys or portions of the MBI. Not reflected in this review is the fact that a large study of US burnout and job satisfaction[51] did not formally address practice location (M. Linzer, personal communication, August 2012). Similarly, a large study of British hospital doctors[52] is not included herein because many of the physicians involved had substantial outpatient duties (C. Taylor, personal communication, July 2012). Varying burnout measures have complicated a previous systematic review of burnout in oncologists.[53] Two studies that directly compared inpatient and outpatient physicians but that were excluded from our statistical analysis because of their modified versions of the MBI,[54, 55] showed higher burnout scores in outpatient physicians. Two other studies that provided direct inpatient versus outpatient comparisons but that used alternative burnout measures[56, 57] showed a greater frequency of burnout in inpatient physicians, but of these, 1 study[56] involved only 3 inpatient physicians.
Several limitations of our study should be considered. Although we endeavored to obtain information from authors (with some success) about specific local practice patterns and eliminated many studies because of incomplete data or mixed practice patterns (eg, general practitioners who take frequent hospital calls, hospital physicians with extensive outpatient duties in a clinic attached to their hospital), it remains likely that many physicians identified as outpatient provided some inpatient care (attending a few weeks per year on a teaching service, for example) and that some physicians identified as inpatient have minimal outpatient duties.
More importantly, the dataset analyzed is heterogeneous. Studies of the incidence of burnout are naturally observational and therefore not randomized. Inclusion of international studies is necessary to answer the research question (because published data on US hospitalists are sparse) but naturally introduces differences in practice settings, local factors, and other factors for which we cannot possibly account fully.
Our meta‐analysis therefore addressed a broad question about burnout among inpatient and outpatient physicians in various diverse settings. Applying it to any 1 population (including US hospitalists) is, by necessity, imprecise.
Post hoc analysis should be viewed with caution. For example, the finding of a statistical difference between US inpatient and outpatient physicians with regard to personal accomplishment score is compelling from the standpoint of hypothesis generation. However, it is worth bearing in mind that this analysis contained only 2 studies, both by the same primary author, and compared 855 outpatient physicians to only 149 hospitalists. This difference was no longer significant when 2 outpatient studies were added through meta‐regression.
Finally, the specific focus of this study on practice location precluded comparison with emergency physicians and anesthesiologists, 2 specialist types that have been the subject of particularly robust burnout literature. As the literature on hospitalist burnout becomes more extensive, comparative studies with these groups and with intensivists might prove instructive.
In summary, analysis of 24 studies comprising data on 5318 outpatient physicians and 1301 inpatient physicians provides no support for the commonly held belief that hospital‐based physicians are particularly prone to burnout. Outpatient physicians reported higher emotional exhaustion. Further studies of the incidence and severity of burnout according to practice location are indicated. We propose that in future studies, to avoid the difficulties with statistical analysis summarized herein, investigators ask about and explicitly report practice location (inpatient vs outpatient vs both) and report mean MBI subset data and standard deviations. Such information about US hospitalists would allow comparison with a robust (if heterogeneous) international literature on burnout.
Acknowledgments
The authors gratefully acknowledge all of the study authors who contributed clarification and guidance for this project, particularly the following authors who provided unpublished data for further analysis: Olaf Aasland, MD; Szilvia dm, PhD; Annalisa Bargellini, PhD; Cinzia Bressi, MD, PhD; Darrell Campbell Jr, MD; Ennio Cocco, MD; Russell Deighton, PhD; Senem Demirci Alanyali, MD; Biagio Di Iorio, MD, PhD; David Dunwoodie, MBBS; Sharon Einav, MD; Madeleine Estryn‐Behar, PhD; Bernardo Gandini, MD; Keiki Hinami, MD; Antonio Lasalvia, MD, PhD; Joseph Lee, MD; Guido Maccacaro, MD; Swati Marner, EdD; Chris McManus, MD, PhD; Carmelle Peisah, MBBS, MD; Katarina Putnik, MSc; Alfredo Rodrguez‐Muoz, PhD; Yahya Shehabi, MD; Evelyn Sosa Oberlin, MD; Jean Karl Soler, MD, MSc; Knut Srgaard, PhD; Cath Taylor; Viva Thorsen, MPH; Mascha Twellaar, MD; Edgar Voltmer, MD; Colin West, MD, PhD; and Deborah Whippen. The authors also thank the following colleagues for their help with translation: Dusanka Anastasijevic (Norwegian); Joyce Cheung‐Flynn, PhD (simplified Chinese); Ales Hlubocky, MD (Czech); Lena Jungheim, RN (Swedish); Erez Kessler (Hebrew); Kanae Mukai, MD (Japanese); Eliane Purchase (French); Aaron Shmookler, MD (Russian); Jan Stepanek, MD (German); Fernando Tondato, MD (Portuguese); Laszlo Vaszar, MD (Hungarian); and Joseph Verheidje, PhD (Dutch). Finally, the authors thank Cynthia Heltne and Diana Rogers for their expert and tireless library assistance, Bonnie Schimek for her help with figures, and Cindy Laureano and Elizabeth Jones for their help with author contact.
Hospital medicine is a rapidly growing field of US clinical practice.[1] Almost since its advent, concerns have been expressed about the potential for hospitalists to burn out.[2] Hospitalists are not unique in this; similar concerns heralded the arrival of other location‐defined specialties, including emergency medicine[3] and the full‐time intensivist model,[4] a fact that has not gone unnoted in the literature about hospitalists.[5]
The existing international literature on physician burnout provides good reason for this concern. Inpatient‐based physicians tend to work unpredictable schedules, with substantial impact on home life.[6] They tend to be young, and much burnout literature suggests a higher risk among younger, less‐experienced physicians.[7] When surveyed, hospitalists have expressed more concerns about their potential for burnout than their outpatient‐based colleagues.[8]
In fact, data suggesting a correlation between inpatient practice and burnout predate the advent of the US hospitalist movement. Increased hospital time was reported to correlate with higher rates of burnout in internists,[9] family practitioners,[10] palliative physicians,[11] junior doctors,[12] radiologists,[13] and cystic fibrosis caregivers.[14] In 1987, Keinan and Melamed[15] noted, Hospital work by its very nature, as compared to the work of a general practitioner, deals with the more severe and complicated illnesses, coupled with continuous daily contacts with patients and their anxious families. In addition, these physicians may find themselves embroiled in the power struggles and competition so common in their work environment.
There are other features, however, that may protect inpatient physicians from burnout. Hospital practice can facilitate favorable social relations involving colleagues, co‐workers, and patients,[16] a factor that may be protective.[17] A hospitalist schedule also can allow more focused time for continuing medical education, research, and teaching,[18] which have all been associated with reduced risk of burnout in some studies.[17] Studies of psychiatrists[19] and pediatricians[20] have shown a lower rate of burnout among physicians with more inpatient duties. Finally, a practice model involving a seemingly stable cadre of inpatient physicians has existed in Europe for decades,[2] indicating at least a degree of sustainability.
Information suggesting a higher rate of burnout among inpatient physicians could be used to target therapeutic interventions and to adjust schedules, whereas the opposite outcome could refute a pervasive myth. We therefore endeavored to summarize the literature on burnout among inpatient versus outpatient physicians in a systematic fashion, and to include data not only from the US hospitalist experience but also from other countries that have used a similar model for decades. Our primary hypothesis was that inpatient physicians experience more burnout than outpatient physicians.
It is important to distinguish burnout from depression, job dissatisfaction, and occupational stress, all of which have been studied extensively in physicians. Burnout, as introduced by Freudenberger[21] and further characterized by Maslach,[22] is a condition in which emotional exhaustion, depersonalization, and a low sense of personal accomplishment combine to negatively affect work life (as opposed to clinical depression, which affects all aspects of life). Job satisfaction can correlate inversely with burnout, but it is a separate process[23] and the subject of a recent systematic review.[24] The importance of distinguishing burnout from job dissatisfaction is illustrated by a survey of head and neck surgeons, in which 97% of those surveyed indicated satisfaction with their jobs and 34% of the same group answered in the affirmative when asked if they felt burned out.[25]
One obstacle to the meaningful comparison of burnout prevalence across time, geography, and specialty is the myriad ways in which burnout is measured and reported. The oldest and most commonly used instrument to measure burnout is the Maslach Burnout Inventory (MBI), which contains 22 items assessing 3 components of burnout (emotional exhaustion, depersonalization, and low personal accomplishment).[26] Other measures include the Copenhagen Burnout Inventory[27] (19 items with the components personal burnout, work‐related burnout, and client‐related burnout), Utrecht Burnout Inventory[28] (20‐item modification of the MBI), Boudreau Burnout Questionnaire[29] (30 items), Arbeitsbezogenes Verhaltens und Erlebensmuster[30] (66‐item questionnaire assessing professional commitment, resistance to stress, and emotional well‐being), Shirom‐Melamed Burnout Measure[31] (22 items with subscales for physical fatigue, cognitive weariness, tension, and listlessness), and a validated single‐item questionnaire.[32]
METHODS
Electronic searches of MEDLINE, EMBASE, PsycINFO, SCOPUS, and PubMed were undertaken for articles published from January 1, 1974 (the year in which burnout was first described by Freudenberger[21]) to 2012 (last accessed, September 12, 2012) using the Medical Subject Headings (MeSH) terms stress, psychological; burnout, professional; adaptation, psychological; and the keyword burnout. The same sources were searched to create another set for the MeSH terms hospitalists, physician's practice patterns, physicians/px, professional practice location, and the keyword hospitalist#. Where exact subject headings did not exist in databases, comparable subject headings or keywords were used. The 2 sets were then combined using the operator and. Abstracts from the Society of Hospital Medicine annual conferences were hand‐searched, as were reference lists from identified articles. To ensure that pertinent international literature was captured, there was no language restriction in the search.
A 2‐stage screening process was used. The titles and abstracts of all articles identified in the search were independently reviewed by 2 investigators (D.L.R. and K.J.C.) who had no knowledge of each other's results. An article was obtained when either reviewer deemed it worthy of full‐text review.
All full‐text articles were independently reviewed by the same 2 investigators. The inclusion criterion was the measurement of burnout in physicians who are stated to or can be reasonably assumed to spend the substantial majority of their clinical practice exclusively in either the inpatient or the outpatient setting. Studies of emergency department physicians or specialists who invariably spend substantial amounts of time in both settings (eg, surgeons, anesthesiologists) were excluded. Studies limited to trainees or nonphysicians were also excluded. For both stages of review, agreement between the 2 investigators was assessed by calculating the statistic. Disagreements about inclusion were adjudicated by a third investigator (A.I.B.).
Because our goal was to establish and compare the rate of burnout among US hospitalists and other inpatient physicians around the world, we included studies of hospitalists according to the definition in use at the time of the individual study, noting that the formal definition of a hospitalist has changed over the years.[33] Because practice patterns for physicians described as primary care physicians, family doctors, hospital doctors, and others differ substantially from country to country, we otherwise included only the studies where the practice location was stated explicitly or where the authors confirmed that their study participants either are known or can be reasonably assumed to spend more than 75% of their time caring for hospital inpatients, or are known or can be reasonably assumed to spend the vast majority of their time caring for outpatients.
Data were abstracted using a standardized form and included the measure of burnout used in the study, results, practice location of study subjects, and total number of study subjects. When data were not clear (eg, burnout measured but not reported by the authors, practice location of study subjects not clear), authors were contacted by email, or when no current email address could be located or no response was received, by telephone or letter. In instances where burnout was measured repeatedly over time or before and after a specific intervention, only the baseline measurement was recorded. Because all studies were expected to be nonrandomized, methodological quality was assessed using a version of the tool of Downs and Black,[34] adapted where necessary by omitting questions not applicable to the specific study type (eg randomization for survey studies)[35] and giving a maximum of 1 point for the inclusion of a power calculation.
Two a priori analyses were planned: (1) a statistical comparison of articles directly comparing burnout among inpatient and outpatient physicians, and (2) a statistical comparison of articles measuring burnout among inpatient physicians with articles measuring burnout among outpatient physicians by the most frequently reported measuremean subset scores for emotional exhaustion, depersonalization, and personal accomplishment on the MBI.
The primary outcome measures were the differences between mean subset scores for emotional exhaustion, depersonalization, and personal accomplishment on the MBI. All differences are expressed as (outpatient meaninpatient mean). The variance of each outcome was calculated with standard formulas.[36] To calculate the overall estimate, each study was weighted by the reciprocal of its variance. Studies with fewer than 10 subjects were excluded from statistical analysis but retained in the systematic review.
For studies that reported data for both inpatient and outpatient physicians (double‐armed studies), Cochran Q test and the I2 value were used to assess heterogeneity.[37, 38] Substantial heterogeneity was expected because these individual studies were conducted for different populations in different settings with different study designs, and this expectation was confirmed statistically. Therefore, we used a random effects model to estimate the overall effect, providing a conservative approach that accounted for heterogeneity among studies.[39]
To assess the durability of our findings, we performed separate multivariate meta‐regression analyses by including single‐armed studies only and including both single‐armed and double‐armed studies. For these meta‐regressions, means were again weighted by the reciprocal of their variances, and the arms of 2‐armed studies were considered separately. This approach allowed us to generate an estimate of the differences between MBI subset scores from studies that did not include such an estimate when analyzed separately.[40]
We examined the potential for publication bias in double‐armed studies by constructing a funnel plot, in which mean scores were plotted against their standard errors.[41] The trim‐and‐fill method was used to determine whether adjustment for publication bias was necessary. In addition, Begg's rank correlation test[42] was completed to test for statistically significant publication bias.
Stata 10.0 statistical software (StataCorp, College Station, TX) was used for data analyses. A P value of 0.05 or less was deemed statistically significant. The Preferred Reporting Items for Systematic Reviews and Meta‐analysis checklist was used for the design and execution of the systematic review and meta‐analysis.[43]
Subgroup analyses based on location were undertaken a posteriori. All data (double‐armed meta‐analysis, meta‐regression of single‐armed studies, and meta‐regression of single‐ and double‐armed studies) were analyzed by location (United States vs other; United States vs Europe vs other).
RESULTS
The search results are outlined in Figure 1. In total, 1704 articles met the criteria for full‐text review. A review of pertinent reference lists and author contacts led to the addition of 149 articles. Twenty‐nine references could not be located by any means, despite repeated attempts. Therefore, 1824 articles were subjected to full‐text review by the 2 investigators.

Initially, 57 articles were found that met criteria for inclusion. Of these, 2 articles reported data in formats that could not be interpreted.[44, 45] When efforts to clarify the data with the authors were unsuccessful, these studies were excluded. A study specifically designed to assess the response of physicians to a recent series of terrorist attacks[46] was excluded a posteriori because of lack of generalizability. Of the other 54 studies, 15 reported burnout data on both outpatient physicians and inpatient physicians, 22 reported data on outpatient physicians only, and 17 reported data on inpatient physicians only. Table 1 summarizes the results of the 37 studies involving outpatient physicians; Table 2 summarizes the 32 studies involving inpatient physicians.
Lead Author, Publication Year | Study Population and Location | Instrument | No. of Participants | EE Score (SD)a | DP Score (SD) | PA Score (SD) | Other Results |
---|---|---|---|---|---|---|---|
| |||||||
Schweitzer, 1994[12] | Young physicians of various specialties in South Africa | Single‐item survey | 7 | 6 (83%) endorsed burnout | |||
Aasland, 1997 [54]b | General practitioners in Norway | Modified MBI (22 items; scale, 15) | 298 | 2.65 (0.80) | 1.90 (0.59) | 3.45 (0.40) | |
Grassi, 2000 [58] | General practitioners in Italy | MBI | 182 | 18.49 (11.49) | 6.11 (5.86) | 38.52 (7.60) | |
McManus, 2000 [59]b | General practitioners in United Kingdom | Modified MBI (9 items; scale, 06) | 800 | 8.34 (4.39) | 3.18 (3.40) | 14.16 (2.95) | |
Yaman, 2002 [60] | General practitioners in 8 European nations | MBI | 98 | 25.1 (8.50) | 7.3 (4.92) | 34.5 (7.67) | |
Cathbras, 2004 [61] | General practitioners in France | MBI | 306 | 21.85 (12.4) | 9.13 (6.7) | 38.7 (7.1) | |
Goehring, 2005 [63] | General practitioners, general internists, pediatricians in Switzerland | MBI | 1755 | 17.9 (9.8) | 6.5 (4.7) | 39.6 (6.5) | |
Esteva, 2006 [64] | General practitioners, pediatricians in Spain | MBI | 261 | 27.4 (11.8) | 10.07 (6.4) | 35.9 (7.06) | |
Gandini, 2006 [65]b | Physicians of various specialties in Argentina | MBI | 67 | 31.0 (13.8) | 10.2 (6.6) | 38.4 (6.8) | |
Ozyurt, 2006 [66] | General practitioners in Turkey | Modified MBI (22 items; scale, 04) | 55 | 15.23 (5.80) | 4.47 (3.31) | 23.38 (4.29) | |
Deighton, 2007 [67]b | Psychiatrists in several German‐speaking nations | MBI | 19 | 30.68 (9.92) | 13.42 (4.23) | 37.16 (3.39) | |
Dunwoodie, 2007 [68]b | Palliative care physicians in Australia | MBI | 21 | 14.95 (9.14) | 3.95 (3.40) | 38.90 (2.88) | |
Srgaard, 2007 [69]b | Psychiatrists in 5 European nations | MBI | 22 | 19.41 (8.08) | 6.68 (4.93) | 39.00 (4.40) | |
Sosa Oberlin, 2007 [56]b | Physicians of various specialties in Argentina | Author‐designed instrument | 33 | 26 (78.8%) had 4 burnout symptoms, 6.15 symptoms per physician | |||
Voltmer, 2007 [57]b | Physicians of various specialties in Germany | AVEM | 46 | 11 (23.9%) exhibited burnout (type B) pattern | |||
dm, 2008 [70]b | Physicians of various specialties in Hungary | MBI | 163 | 17.45 (11.12) | 4.86 (4.91) | 36.56 (7.03) | |
Di Iorio, 2008 [71]b | Dialysis physicians in Italy | Author‐designed instrument | 54 | Work: 2.6 (1.5), Material: 3.1 (2.1), Climate: 3.0 (1.1), Objectives: 3.4 (1.6), Quality: 2.2 (1.5), Justification: 3.2 (2.0) | |||
Lee, 2008 [49]b | Family physicians in Canada | MBI | 123 | 26.26 (9.53) | 10.20 (5.22) | 38.43 (7.34) | |
Truchot, 2008 [72] | General practitioners in France | MBI | 259 | 25.4 (11.7) | 7.5 (5.5) | 36.5 (7.1) | |
Twellaar, 2008 [73]b | General practitioners in the Netherlands | Utrecht Burnout Inventory | 349 | 2.06 (1.11) | 1.71 (1.05) | 5.08 (0.77) | |
Arigoni, 2009 [17] | General practitioners, pediatricians in Switzerland | MBI | 258 | 22.8 (12.0) | 6.9 (6.1) | 39.0 (7.2) | |
Bernhardt, 2009 [75] | Clinical geneticists in United States | MBI | 72 | 25.8 (10.01)c | 10.9 (4.16)c | 34.8 (5.43)c | |
Bressi, 2009 [76]b | Psychiatrists in Italy | MBI | 53 | 23.15 (11.99) | 7.02 (6.29) | 36.41 (7.54) | |
Krasner, 2009 [77] | General practitioners in United States | MBI | 60 | 26.8 (10.9)d | 8.4 (5.1)d | 40.2 (5.3)d | |
Lasalvia, 2009 [55]b | Psychiatrists in Italy | Modified MBI (16 items; scale, 06) | 38 | 2.37 (1.27) | 1.51 (1.15) | 4.46 (0.87) | |
Peisah, 2009 [79]b | Physicians of various specialties in Australia | MBI | 28 | 13.92 (9.24) | 3.66 (3.95) | 39.34 (8.55) | |
Shanafelt, 2009 [80]b | Physicians of various specialties in United States | MBI | 408 | 20.5 (11.10) | 4.3 (4.74) | 40.8 (6.26) | |
Zantinge, 2009 [81] | General practitioners in the Netherlands | Utrecht Burnout Inventory | 126 | 1.58 (0.79) | 1.32 (0.72) | 4.27 (0.77) | |
Voltmer, 2010 [83]b | Psychiatrists in Germany | AVEM | 526 | 114 (21.7%) exhibited burnout (type B) pattern | |||
Maccacaro, 2011 [85]b | Physicians of various specialties in Italy | MBI | 42 | 14.31 (11.98) | 3.62 (4.95) | 38.24 (6.22) | |
Lucas, 2011 [84]b | Outpatient physicians periodically staffing an academic hospital teaching service in United States | MBI (EE only) | 30 | 24.37 (14.95) | |||
Shanafelt, 2012 [87]b | General internists in United States | MBI | 447 | 25.4 (14.0) | 7.5 (6.3) | 41.4 (6.0) | |
Kushnir, 2004 [62] | General practitioners and pediatricians in Israel | MBI (DP only) and SMBM | 309 | 9.15 (3.95) | SMBM mean (SD), 2.73 per item (0.86) | ||
Vela‐Bueno, 2008 [74]b | General practitioners in Spain | MBI | 240 | 26.91 (11.61) | 9.20 (6.35) | 35.92 (7.92) | |
Lesic, 2009 [78]b | General practitioners in Serbia | MBI | 38 | 24.71 (10.81) | 7.47 (5.51) | 37.21 (7.44) | |
Demirci, 2010 [82]b | Medical specialists related to oncology practice in Hungary | MBI | 26 | 23.31 (11.2) | 6.46 (5.7) | 37.7 (8.14) | |
Putnik, 2011 [86]b | General practitioners in Hungary | MBI | 370 | 22.22 (11.75) | 3.66 (4.40) | 41.40 (6.85) |
Lead Author, Publication Year | Study Population and Location | Instrument | No. of Participants | EE Score (SD)a | DP Score (SD) | PA Score (SD) | Other Results |
---|---|---|---|---|---|---|---|
| |||||||
Varga, 1996 [88] | Hospital doctors in Spain | MBI | 179 | 21.61b | 7.33b | 35.28b | |
Aasland, 1997 [54] | Hospital doctors in Norway | Modified MBI (22 items; scale, 15) | 582 | 2.39 (0.80) | 1.81 (0.65) | 3.51 (0.46) | |
Bargellini, 2000 [89] | Hospital doctors in Italy | MBI | 51 | 17.45 (9.87) | 7.06 (5.54) | 35.33 (7.90) | |
Grassi, 2000 [58] | Hospital doctors in Italy | MBI | 146 | 16.17 (9.64) | 5.32 (4.76) | 38.71 (7.28) | |
Hoff, 2001 [33] | Hospitalists in United States | Single‐item surveyc | 393 | 12.9% burned out (>4/5), 24.9% at risk for burnout (34/5), 62.2% at no current risk (mean, 2.86 on 15 scale) | |||
Trichard, 2005 [90] | Hospital doctors in France | MBI | 199 | 16 (10.7) | 6.6 (5.7) | 38.5 (6.5) | |
Gandini, 2006 [65]d | Hospital doctors in Argentina | MBI | 290 | 25.0 (12.7) | 7.9 (6.2) | 40.1 (7.0) | |
Dunwoodie, 2007 [68]d | Palliative care doctors in Australia | MBI | 14 | 18.29 (14.24) | 5.29 (5.89) | 38.86 (3.42) | |
Srgaard, 2007 [69]d | Psychiatrists in 5 European nations | MBI | 18 | 18.56 (9.32) | 5.50 (3.79) | 39.08 (5.39) | |
Sosa Oberlin, 2007 [56]d | Hospital doctors in Argentina | Author‐designed instrument | 3 | 3 (100%) had 4 burnout symptoms, 8.67 symptoms per physician | |||
Voltmer, 2007 [57]d | Hospital doctors in Germany | AVEM | 271 | 77 (28.4%) exhibited burnout (type B) pattern | |||
dm, 2008 [70]b | Physicians of various specialties in Hungary | MBI | 194 | 19.23 (10.79) | 4.88 (4.61) | 35.26 (8.42) | |
Di Iorio, 2008 [71]d | Dialysis physicians in Italy | Author‐designed instrument | 62 | Work, mean (SD), 3.1 (1.4); Material, mean (SD), 3.3 (1.5); Climate, mean (SD), 2.9 (1.1); Objectives, mean (SD), 2.5 (1.5); Quality, mean (SD), 3.0 (1.1); Justification, mean (SD), 3.1 (2.1) | |||
Fuss, 2008 [91]d | Hospital doctors in Germany | Copenhagen Burnout Inventory | 292 | Mean Copenhagen Burnout Inventory, mean (SD), 46.90 (18.45) | |||
Marner, 2008 [92]d | Psychiatrists and 1 generalist in United States | MBI | 9 | 20.67 (9.75) | 7.78 (5.14) | 35.33 (6.44) | |
Shehabi, 2008 [93]d | Intensivists in Australia | Modified MBI (6 items; scale, 15) | 86 | 2.85 (0.93) | 2.64 (0.85) | 2.58 (0.83) | |
Bressi, 2009 [76]d | Psychiatrists in Italy | MBI | 28 | 17.89 (14.46) | 5.32 (7.01) | 34.57 (11.27) | |
Brown, 2009 [94] | Hospital doctors in Australia | MBI | 12 | 22.25 (8.59) | 6.33 (2.71) | 39.83 (7.31) | |
Lasalvia, 2009 [55]d | Psychiatrists in Italy | Modified MBI (16 items; scale, 06) | 21 | 1.95 (1.04) | 1.35 (0.85) | 4.46 (1.04) | |
Peisah, 2009 [79]d | Hospital doctors in Australia | MBI | 62 | 20.09 (9.91) | 6.34 (4.90) | 35.06 (7.33) | |
Shanafelt, 2009 [80]d | Hospitalists and intensivists in United States | MBI | 19 | 25.2 (11.59) | 4.4 (3.79) | 38.5 (8.04) | |
Tunc, 2009 [95] | Hospital doctors in Turkey | Modified MBI (22 items; scale, 04) | 62 | 1.18 (0.78) | 0.81 (0.73) | 3.10 (0.59)e | |
Cocco, 2010 [96]d | Hospital geriatricians in Italy | MBI | 38 | 16.21 (11.56) | 4.53 (4.63) | 39.13 (7.09) | |
Doppia, 2011 [97]d | Hospital doctors in France | Copenhagen Burnout Inventory | 1,684 | Mean work‐related burnout score, 2.72 (0.75) | |||
Glasheen, 2011 [98] | Hospitalists in United States | Single‐item survey | 265 | Mean, 2.08 on 15 scale 62 (23.4%) burned out | |||
Lucas, 2011 [84]d | Academic hospitalists in United States | MBI (EE only) | 26 | 19.54 (12.85) | |||
Thorsen, 2011 [99] | Hospital doctors in Malawi | MBI | 2 | 25.5 (4.95) | 8.5 (6.36) | 25.0 (5.66) | |
Hinami, 2012 [50]d | Hospital doctors in United States | Single‐item survey | 793 | Mean, 2.24 on 15 scale 261 (27.2%) burned out | |||
Quenot, 2012 [100]d | Intensivists in France | MBI | 4 | 33.25 (4.57) | 13.50 (5.45) | 35.25 (4.86) | |
Ruitenburg, 2012 [101] | Hospital doctors in the Netherlands | MBI (EE and DP only) | 214 | 13.3 (8.0) | 4.5 (4.1) | ||
Seibt, 2012 [102]d | Hospital doctors in Germany | Modified MBI (16 items; scale, 06, reported per item rather than totals) | 2,154 | 2.2 (1.4) | 1.4 (1.2) | 5.1 (0.9) | |
Shanafelt, 2012 [87]d | Hospitalists in United States | MBI | 130 | 24.7 (12.5) | 9.1 (6.9) | 39.0 (7.6) |
Table 3 summarizes the results of the 15 studies that reported burnout data for both inpatient and outpatient physicians, allowing direct comparisons to be made. Nine studies reported MBI subset totals with standard deviations, 2 used different modifications of the MBI, 2 used different author‐derived measures, 1 used only the emotional exhaustion subscale of the MBI, and 1 used the Arbeitsbezogenes Verhaltens und Erlebensmuster. Therefore, statistical comparison was attempted only for the 9 studies reporting comparable MBI data, comprising burnout data on 1390 outpatient physicians and 899 inpatient physicians.
Lead Author, Publication Year | Location | Instrument | Inpatient‐Based Physicians | Outpatient‐Based Physicians | ||
---|---|---|---|---|---|---|
No. | Results, Score (SD)a | No. | Results, Score (SD)a | |||
| ||||||
Aasland, 1997 [54]b | Norway | Modified MBI (22 items; scale, 15) | 582 | EE, 2.39 (0.80); DP, 1.81 (0.65); PA, 3.51 (0.46) | 298 | EE, 2.65 (0.80); DP, 1.90 (0.59); PA, 3.45 (0.40) |
Grassi, 2000 [58] | Italy | MBI | 146 | EE, 16.17 (9.64); DP, 5.32 (4.76); PA, 38.71 (7.28) | 182 | EE, 18.49 (11.49); DP, 6.11 (5.86); PA, 38.52 (7.60) |
Gandini, 2006 [65]b | Argentina | MBI | 290 | EE, 25.0 (12.7);DP, 7.9 (6.2); PA, 40.1 (7.0) | 67 | EE, 31.0 (13.8); DP, 10.2 (6.6); PA, 38.4 (6.8) |
Dunwoodie, 2007 [68]b | Australia | MBI | 14 | EE, 18.29 (14.24); DP, 5.29 (5.89); PA, 38.86 (3.42) | 21 | EE, 14.95 (9.14); DP, 3.95 (3.40); PA, 38.90 (2.88) |
Srgaard, 2007 [69]b | 5 European nations | MBI | 18 | EE, 18.56 (9.32); DP, 5.50 (3.79); PA, 39.08 (5.39) | 22 | EE, 19.41 (8.08); DP, 6.68 (4.93); PA, 39.00 (4.40) |
Sosa Oberlin, 2007 [56]b | Argentina | Author‐designed instrument | 3 | 3 (100%) had 4 burnout symptoms, 8.67 symptoms per physician | 33 | 26 (78.8%) had 4 burnout symptoms, 6.15 symptoms per physician |
Voltmer, 2007 [57]b | Germany | AVEM | 271 | 77 (28.4%) exhibited burnout (type B) pattern | 46 | 11 (23.9%) exhibited burnout (type B) pattern |
dm, 2008 [70]b | Hungary | MBI | 194 | EE, 19.23 (10.79); DP, 4.88 (4.61); PA, 35.26 (8.42) | 163 | EE, 17.45 (11.12); DP, 4.86 (4.91); PA, 36.56 (7.03) |
Di Iorio, 2008 [71]b | Italy | Author‐designed instrument | 62 | Work: 3.1 (1.4); material: 3.3 (1.5); climate: 2.9 (1.1); objectives: 2.5 (1.5); quality: 3.0 (1.1); justification: 3.1 (2.1) | 54 | Work: 2.6 (1.5); material: 3.1 (2.1); climate: 3.0 (1.1); objectives: 3.4 (1.6); quality: 2.2 (1.5); justification: 3.2 (2.0) |
Bressi, 2009 [76]b | Italy | MBI | 28 | EE, 17.89 (14.46); DP, 5.32 (7.01); PA, 34.57 (11.27) | 53 | EE, 23.15 (11.99); DP, 7.02 (6.29); PA, 36.41 (7.54) |
Lasalvia, 2009[55]b | Italy | Modified MBI (16 items; scale, 06) | 21 | EE, 1.95 (1.04); DP, 1.35 (0.85); PA, 4.46 (1.04) | 38 | EE, 2.37 (1.27); DP, 1.51 (1.15); PA, 4.46 (0.87) |
Peisah, 2009 [79]b | Australia | MBI | 62 | EE, 20.09 (9.91); DP, 6.34 (4.90); PA, 35.06 (7.33) | 28 | EE, 13.92 (9.24); DP, 3.66 (3.95); PA, 39.34 (8.55) |
Shanafelt, 2009 [80]b | United States | MBI | 19 | EE, 25.2 (11.59); DP, 4.4 (3.79); PA, 38.5 (8.04) | 408 | EE, 20.5 (11.10); DP, 4.3 (4.74); PA, 40.8 (6.26) |
Lucas, 2011 [84]b | United States | MBI (EE only) | 26 | EE, 19.54 (12.85) | 30 | EE, 24.37 (14.95) |
Shanafelt, 2012 [87]b | United States | MBI | 130 | EE, 24.7 (12.5); DP, 9.1 (6.9); PA, 39.0 (7.6) | 447 | EE, 25.4 (14.0); DP, 7.5 (6.3); PA, 41.4 (6.0) |
Figure 2 shows that no significant difference existed between the groups regarding emotional exhaustion (mean difference, 0.11 points on a 54‐point scale; 95% confidence interval [CI], 2.40 to 2.61; P=0.94). In addition, there was no significant difference between the groups regarding depersonalization (Figure 3; mean difference, 0.00 points on a 30‐point scale; 95% CI, 1.03 to 1.02; P=0.99) and personal accomplishment (Figure 4; mean difference, 0.93 points on a 48‐point scale; 95% CI, 0.23 to 2.09; P=0.11).



We used meta‐regression to allow the incorporation of single‐armed MBI studies. Whether single‐armed studies were analyzed separately (15 outpatient studies comprising 3927 physicians, 4 inpatient studies comprising 300 physicians) or analyzed with double‐armed studies (24 outpatient arms comprising 5318 physicians, 13 inpatient arms comprising 1301 physicians), the lack of a significant difference between the groups persisted for the depersonalization and personal accomplishment scales (Figure 5). Emotional exhaustion was significantly higher in outpatient physicians when single‐armed studies were considered separately (mean difference, 6.36 points; 95% CI, 2.24 to 10.48; P=0.002), and this difference persisted when all studies were combined (mean difference, 3.00 points; 95% CI, 0.05 to 5.94, P=0.046).

Subgroup analysis by geographic location showed US outpatient physicians had a significantly higher personal accomplishment score than US inpatient physicians (mean difference, 2.38 points; 95% CI, 1.22 to 3.55; P<0.001) in double‐armed studies. This difference did not persist when single‐armed studies were included through meta‐regression (mean difference, 0.55 points, 95% CI, 4.30 to 5.40, P=0.83).
Table 4 demonstrates that methodological quality was generally good from the standpoint of the reporting and bias subsections of the Downs and Black tool. External validity was scored lower for many studies due to the use of convenience samples and lack of information about physicians who declined to participate.
Lead Author, Publication Year | Reporting | External Validity | Internal Validity: Bias | Internal Validity: Confounding | Power |
---|---|---|---|---|---|
Schweitzer, 1994 [12] | 5 of 6 points | 1 of 2 points | 3 of 4 points | 0 of 1 point | 0 of 1 point |
Varga, 1996 [88] | 5 of 6 points | 1 of 2 points | 3 of 4 points | 1 of 1 point | 0 of 1 point |
Aasland, 1997 [54] | 3 of 6 points | 2 of 2 points | 3 of 4 points | 1 of 1 point | 0 of 1 point |
Bargellini, 2000 [89] | 5 of 6 points | 0 of 2 points | 4 of 4 points | 1 of 1 point | 0 of 1 point |
Grassi, 2000 [58] | 6 of 6 points | 0 of 2 points | 3 of 4 points | 0 of 1 point | 0 of 1 point |
McManus, 2000 [59] | 5 of 6 points | 2 of 2 points | 4 of 4 points | 1 of 1 point | 0 of 1 point |
Hoff, 2001 [33] | 6 of 6 points | 2 of 2 points | 2 of 4 points | 1 of 1 point | 0 of 1 point |
Yaman, 2002 [60] | 5 of 6 points | 0 of 2 points | 4 of 4 points | 0 of 1 point | 0 of 1 point |
Cathbras, 2004 [61] | 6 of 6 points | 0 of 2 points | 4 of 4 points | 0 of 1 point | 0 of 1 point |
Kushnir, 2004 [62] | 5 of 6 points | 0 of 2 points | 3 of 4 points | 0 of 1 point | 0 of 1 point |
Goehring, 2005 [63] | 6 of 6 points | 1 of 2 points | 3 of 4 points | 1 of 1 point | 0 of 1 point |
Trichard, 2005 [90] | 3 of 6 points | 1 of 2 points | 3 of 4 points | 0 of 1 point | 0 of 1 point |
Esteva, 2006 [64] | 6 of 6 points | 2 of 2 points | 4 of 4 points | 1 of 1 point | 0 of 1 point |
Gandini, 2006 [65] | 6 of 6 points | 1 of 2 points | 3 of 4 points | 1 of 1 point | 0 of 1 point |
Ozyurt, 2006 [66] | 6 of 6 points | 2 of 2 points | 4 of 4 points | 1 of 1 point | 0 of 1 point |
Deighton, 2007 [67] | 5 of 6 points | 0 of 2 points | 4 of 4 points | 0 of 1 point | 0 of 1 point |
Dunwoodie, 2007 [68] | 5 of 6 points | 2 of 2 points | 4 of 4 points | 0 of 1 point | 0 of 1 point |
Srgaard, 2007 [69] | 6 of 6 points | 0 of 2 points | 3 of 4 points | 1 of 1 point | 1 of 1 point |
Sosa Oberlin, 2007 [56] | 4 of 6 points | 0 of 2 points | 3 of 4 points | 0 of 1 point | 0 of 1 point |
Voltmer, 2007 [57] | 4 of 6 points | 0 of 2 points | 4 of 4 points | 0 of 1 point | 0 of 1 point |
dm, 2008 [70] | 5 of 6 points | 2 of 2 points | 3 of 4 points | 1 of 1 point | 0 of 1 point |
Di Iorio, 2008 [71] | 6 of 6 points | 0 of 2 points | 2 of 4 points | 0 of 1 point | 0 of 1 point |
Fuss, 2008 [91] | 6 of 6 points | 0 of 2 points | 3 of 4 points | 0 of 1 point | 0 of 1 point |
Lee, 2008 [49] | 4 of 6 points | 2 of 2 points | 4 of 4 points | 0 of 1 point | 1 of 1 point |
Marner, 2008 [92] | 6 of 6 points | 0 of 2 points | 4 of 4 points | 0 of 1 point | 0 of 1 point |
Shehabi, 2008 [93] | 3 of 6 points | 1 of 2 points | 3 of 4 points | 0 of 1 point | 0 of 1 point |
Truchot, 2008 [72] | 5 of 6 points | 1 of 2 points | 3 of 4 points | 0 of 1 point | 0 of 1 point |
Twellaar, 2008 [73] | 6 of 6 points | 2 of 2 points | 3 of 4 points | 0 of 1 point | 0 of 1 point |
Vela‐Bueno, 2008 [74] | 5 of 6 points | 2 of 2 points | 4 of 4 points | 1 of 1 point | 0 of 1 point |
Arigoni, 2009 [17] | 6 of 6 points | 2 of 2 points | 4 of 4 points | 1 of 1 point | 0 of 1 point |
Bernhardt, 2009 [75] | 6 of 6 points | 2 of 2 points | 4 of 4 points | 1 of 1 point | 0 of 1 point |
Bressi, 2009 [76] | 6 of 6 points | 0 of 2 points | 3 of 4 points | 1 of 1 point | 0 of 1 point |
Brown, 2009 [94] | 6 of 6 points | 0 of 2 points | 4 of 4 points | 0 of 1 point | 0 of 1 point |
Krasner, 2009 [77] | 9 of 11 points | 0 of 3 points | 6 of 7 points | 1 of 2 points | 1 of 1 point |
Lasalvia, 2009 [55] | 6 of 6 points | 2 of 2 points | 4 of 4 points | 1 of 1 point | 0 of 1 point |
Lesic, 2009 [78] | 5 of 6 points | 0 of 2 points | 4 of 4 points | 0 of 1 point | 0 of 1 point |
Peisah, 2009 [79] | 6 of 6 points | 2 of 2 points | 3 of 4 points | 1 of 1 point | 0 of 1 point |
Shanafelt, 2009 [80] | 6 of 6 points | 2 of 2 points | 4 of 4 points | 1 of 1 point | 0 of 1 point |
Tunc, 2009 [95] | 6 of 6 points | 2 of 2 points | 4 of 4 points | 1 of 1 point | 0 of 1 point |
Zantinge, 2009 [81] | 5 of 6 points | 0 of 2 points | 3 of 4 points | 1 of 1 point | 0 of 1 point |
Cocco, 2010 [96] | 4 of 6 points | 0 of 2 points | 4 of 4 points | 0 of 1 point | 0 of 1 point |
Demirci, 2010 [82] | 6 of 6 points | 0 of 2 points | 4 of 4 points | 0 of 1 point | 0 of 1 point |
Voltmer, 2010 [83] | 6 of 6 points | 2 of 2 points | 4 of 4 points | 1 of 1 point | 0 of 1 point |
Doppia, 2011 [97] | 5 of 6 points | 2 of 2 points | 4 of 4 points | 1 of 1 point | 0 of 1 point |
Glasheen, 2011 [98] | 5 of 6 points | 0 of 2 points | 4 of 4 points | 1 of 1 point | 0 of 1 point |
Lucas, 2011 [84] | 10 of 11 points | 2 of 3 points | 7 of 7 points | 5 of 6 points | 1 of 1 point |
Maccacaro, 2011 [85] | 5 of 6 points | 0 of 2 points | 4 of 4 points | 1 of 1 point | 0 of 1 point |
Putnik, 2011 [86] | 6 of 6 points | 1 of 2 points | 4 of 4 points | 0 of 1 point | 0 of 1 point |
Thorsen, 2011 [99] | 6 of 6 points | 0 of 2 points | 4 of 4 points | 0 of 1 point | 0 of 1 point |
Hinami, 2012 [50] | 6 of 6 points | 2 of 2 points | 4 of 4 points | 1 of 1 point | 1 of 1 point |
Quenot, 2012 [100] | 8 of 11 points | 1 of 3 points | 6 of 7 points | 1 of 2 points | 0 of 1 point |
Ruitenburg, 2012 [101] | 6 of 6 points | 2 of 2 points | 4 of 4 points | 0 of 1 point | 0 of 1 point |
Seibt, 2012 [102] | 6 of 6 points | 0 of 2 points | 4 of 4 points | 1 of 1 point | 0 of 1 point |
Shanafelt, 2012 [87] | 6 of 6 points | 2 of 2 points | 4 of 4 points | 1 of 1 point | 0 of 1 point |
Funnel plots were used to evaluate for publication bias in the meta‐analysis of the 8 double‐armed studies (Figure 6). We found no significant evidence of bias, which was supported by Begg's test P values of 0.90 for emotional exhaustion, >0.99 for depersonalization, and 0.54 for personal accomplishment. A trim‐and‐fill analysis determined that no adjustment was necessary.

DISCUSSION
There appears to be no support for the long‐held belief that inpatient physicians are particularly prone to burnout. Among studies for which practice location was stated explicitly or could be obtained from the authors, and who used the MBI, no differences were found among inpatient and outpatient physicians with regard to depersonalization or personal accomplishment. This finding persisted whether double‐armed studies were compared directly, single‐armed studies were incorporated into this analysis, or single‐armed studies were analyzed separately. Outpatient physicians had a higher degree of emotional exhaustion when all studies were considered.
There are several reasons why outpatient physicians may be more prone to emotional exhaustion than their inpatient colleagues. Although it is by no means true that all inpatient physicians work in shifts, the increased availability of shift work may allow some inpatient physicians to better balance their professional and personal lives, a factor of work with which some outpatient physicians have struggled.[47] Inpatient practice may also afford more opportunity for teamwork, a factor that has been shown to correlate with reduced burnout.[48] When surveyed about burnout, outpatient physicians have cited patient volumes, paperwork, medicolegal concerns, and lack of community support as factors.[49] Inpatient physicians are not immune to these forces, but they arguably experience them to different degrees.
The absence of a higher rate of depersonalization among inpatient physicians is particularly reassuring in light of concerns expressed with the advent of US hospital medicinethat some hospitalists would be prone to viewing patients as an impediment to the efficient running of the hospital,[2] the very definition of depersonalization.
Although the difference in the whole sample was not statistically significant, the consistent tendency toward a greater sense of personal accomplishment among outpatient physicians is also noteworthy, particularly because post hoc subgroup analysis of US physicians did show statistical significance in both 2‐armed studies. Without detailed age data for the physicians in each study, we could not separate the possible impact of age on personal accomplishment; hospital medicine is a newer specialty staffed by generally younger physicians, and hospitalists may not have had time to develop a sense of accomplishment. When surveyed about job satisfaction, hospitalists have also reported the feeling that they were treated as glorified residents,[50] a factor that, if shared by other inpatient physicians, must surely affect their sense of personal accomplishment. The lack of longitudinal care for patients and the substantial provision of end‐of‐life care also may diminish the sense of personal accomplishment among inpatient physicians.
Another important finding from this systematic review is the marked heterogeneity of the instruments used to measure physician burnout. Many of the identified studies could not be subjected to meta‐analysis because of their use of differing burnout measures. Drawing more substantial conclusions about burnout and practice location is limited by the fact that, although the majority of studies used the full MBI, the largest study of European hospital doctors used the Copenhagen Burnout Inventory, and the studies thus far of US hospitalists have used single‐item surveys or portions of the MBI. Not reflected in this review is the fact that a large study of US burnout and job satisfaction[51] did not formally address practice location (M. Linzer, personal communication, August 2012). Similarly, a large study of British hospital doctors[52] is not included herein because many of the physicians involved had substantial outpatient duties (C. Taylor, personal communication, July 2012). Varying burnout measures have complicated a previous systematic review of burnout in oncologists.[53] Two studies that directly compared inpatient and outpatient physicians but that were excluded from our statistical analysis because of their modified versions of the MBI,[54, 55] showed higher burnout scores in outpatient physicians. Two other studies that provided direct inpatient versus outpatient comparisons but that used alternative burnout measures[56, 57] showed a greater frequency of burnout in inpatient physicians, but of these, 1 study[56] involved only 3 inpatient physicians.
Several limitations of our study should be considered. Although we endeavored to obtain information from authors (with some success) about specific local practice patterns and eliminated many studies because of incomplete data or mixed practice patterns (eg, general practitioners who take frequent hospital calls, hospital physicians with extensive outpatient duties in a clinic attached to their hospital), it remains likely that many physicians identified as outpatient provided some inpatient care (attending a few weeks per year on a teaching service, for example) and that some physicians identified as inpatient have minimal outpatient duties.
More importantly, the dataset analyzed is heterogeneous. Studies of the incidence of burnout are naturally observational and therefore not randomized. Inclusion of international studies is necessary to answer the research question (because published data on US hospitalists are sparse) but naturally introduces differences in practice settings, local factors, and other factors for which we cannot possibly account fully.
Our meta‐analysis therefore addressed a broad question about burnout among inpatient and outpatient physicians in various diverse settings. Applying it to any 1 population (including US hospitalists) is, by necessity, imprecise.
Post hoc analysis should be viewed with caution. For example, the finding of a statistical difference between US inpatient and outpatient physicians with regard to personal accomplishment score is compelling from the standpoint of hypothesis generation. However, it is worth bearing in mind that this analysis contained only 2 studies, both by the same primary author, and compared 855 outpatient physicians to only 149 hospitalists. This difference was no longer significant when 2 outpatient studies were added through meta‐regression.
Finally, the specific focus of this study on practice location precluded comparison with emergency physicians and anesthesiologists, 2 specialist types that have been the subject of particularly robust burnout literature. As the literature on hospitalist burnout becomes more extensive, comparative studies with these groups and with intensivists might prove instructive.
In summary, analysis of 24 studies comprising data on 5318 outpatient physicians and 1301 inpatient physicians provides no support for the commonly held belief that hospital‐based physicians are particularly prone to burnout. Outpatient physicians reported higher emotional exhaustion. Further studies of the incidence and severity of burnout according to practice location are indicated. We propose that in future studies, to avoid the difficulties with statistical analysis summarized herein, investigators ask about and explicitly report practice location (inpatient vs outpatient vs both) and report mean MBI subset data and standard deviations. Such information about US hospitalists would allow comparison with a robust (if heterogeneous) international literature on burnout.
Acknowledgments
The authors gratefully acknowledge all of the study authors who contributed clarification and guidance for this project, particularly the following authors who provided unpublished data for further analysis: Olaf Aasland, MD; Szilvia dm, PhD; Annalisa Bargellini, PhD; Cinzia Bressi, MD, PhD; Darrell Campbell Jr, MD; Ennio Cocco, MD; Russell Deighton, PhD; Senem Demirci Alanyali, MD; Biagio Di Iorio, MD, PhD; David Dunwoodie, MBBS; Sharon Einav, MD; Madeleine Estryn‐Behar, PhD; Bernardo Gandini, MD; Keiki Hinami, MD; Antonio Lasalvia, MD, PhD; Joseph Lee, MD; Guido Maccacaro, MD; Swati Marner, EdD; Chris McManus, MD, PhD; Carmelle Peisah, MBBS, MD; Katarina Putnik, MSc; Alfredo Rodrguez‐Muoz, PhD; Yahya Shehabi, MD; Evelyn Sosa Oberlin, MD; Jean Karl Soler, MD, MSc; Knut Srgaard, PhD; Cath Taylor; Viva Thorsen, MPH; Mascha Twellaar, MD; Edgar Voltmer, MD; Colin West, MD, PhD; and Deborah Whippen. The authors also thank the following colleagues for their help with translation: Dusanka Anastasijevic (Norwegian); Joyce Cheung‐Flynn, PhD (simplified Chinese); Ales Hlubocky, MD (Czech); Lena Jungheim, RN (Swedish); Erez Kessler (Hebrew); Kanae Mukai, MD (Japanese); Eliane Purchase (French); Aaron Shmookler, MD (Russian); Jan Stepanek, MD (German); Fernando Tondato, MD (Portuguese); Laszlo Vaszar, MD (Hungarian); and Joseph Verheidje, PhD (Dutch). Finally, the authors thank Cynthia Heltne and Diana Rogers for their expert and tireless library assistance, Bonnie Schimek for her help with figures, and Cindy Laureano and Elizabeth Jones for their help with author contact.
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- The occupational hazards of emergency physicians. Am J Emerg Med. 2000;18(3):300–311. , .
- Physician burnout in pediatric critical care medicine. Crit Care Med. 1995;23(8):1425–1429. , , , et al.
- The hospitalist: new boon for internal medicine or retreat from primary care? Ann Intern Med. 1999;130(4 pt 2): 382–387. , .
- Enquete sur les horaires et la charge de travail des medecins dans un establissement de l'Assitance Publique‐Hopitaux de Paris. Arch Mal Prof. 1996;57:438–444. , , , et al.
- Burn‐out of urologists in the county of Schleswig‐Holstein, Germany: a comparison of hospital and private practice urologists. J Urol. 2001;165(4): 1158–1161. , , , , .
- Satisfaction and worklife of academic hospitalist and non‐hospitalist attendings on general medical inpatient rotations. J Gen Internal Med. 2006;21(S4):128. , , , et al.
- SGIM Career Satisfaction Group. What effect does increasing inpatient time have on outpatient‐oriented internist satisfaction? J Gen Intern Med. 2003;18(9):725–729. , , , , , ;
- Burnout and career‐choice regret among family practice physicians in early practice. Fam Pract Res J. 1994;14(3):213–222. , , .
- Job stress and satisfaction among palliative physicians. Palliat Med. 1996; 10(3):185–194. , , , , , .
- Stress and burnout in junior doctors. S Afr Med J. 1994; 84(6):352–354. .
- Work stress, satisfaction and burnout in New Zealand radiologists: comparison of public hospital and private practice in New Zealand. J Med Imaging Radiat Oncol. 2009;53(2):194–199. , .
- Measurement of hypothetical burnout in cystic fibrosis caregivers. Acta Paediatr Scand. 1981; 70(6):935–939. , , .
- Personality characteristics and proneness to burnout: a study among internists. Stress Med. 1987;3(4):307–315. , .
- Thriving and surviving in a new medical career: the case of hospitalist physicians. J Health Soc Behav. 2002;43(1):72–91. , , .
- Prevalence of burnout among Swiss cancer clinicians, paediatricians and general practitioners: who are most at risk? Support Care Cancer. 2009;17(1): 75–81. , , , , .
- Preparing for “diastole”: advanced training opportunities for academic hospitalists. J Hosp Med. 2006;1(6):368–377. , , , .
- Mental health, “burnout” and job satisfaction among hospital and community‐based mental health staff. Br J Psychiatry. 1996;169(3):334–337. , , , , , .
- Role of a pediatric department chair: factors leading to satisfaction and burnout. J Pediatr. 2007;151(4):425–430. , , , .
- Staff burn‐out. J Soc Iss. 1974;30(1):159–165. .
- Burned‐out. Hum Behav. 1976;5(9):16–22. .
- Underpaid women, stressed out men, satisfied emergency physicians. Ann Emerg Med. 2008;51(6):729–731. .
- U.S. physician satisfaction: a systematic review. J Hosp Med. 2009;4(9):560–568. , , , .
- Professional burnout among head and neck surgeons: results of a survey. Head Neck. 1993;15(6):557–560. , , , .
- The measurement of experienced burnout. J Occup Behav. 1981;2(2):99–113. , .
- The Copenhagen Burnout Inventory: a new tool for the assessment of burnout. Work Stress. 2005;19(3):192–207. , , , .
- Handleiding van de Utrechtse Burnout Schaal (UBOS). Lisse, the Netherlands: Swets Test Services; 2000. , .
- Alberta Physician Burnout [master's thesis]. Alberta, Canada: The University of Lethbridge; 2003. .
- Arbeitsbezogenes Verhaltensund Erlebensmuster AVEM. Frankfurt, Germany: Swets Test Services; 2003. , .
- Internal construct validity of the Shirom‐Melamed Burnout Questionnaire (SMBQ). BMC Public Health. 2012;12:1. , , , .
- Validation of a single‐item measure of burnout against the Maslach Burnout Inventory among physicians. Stress Health. 2004;20(2):75–79. , , .
- Characteristics and work experiences of hospitalists in the United States. Arch Intern Med. 2001;161(6):851–858. , , , , .
- The feasibility of creating a checklist for the assessment of the methodological quality both of randomised and non‐randomised studies of health care interventions. J Epidemiol Community Health. 1998;52(6):377–384. , .
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- The PRISMA statement for reporting systematic reviews and meta‐analyses of studies that evaluate healthcare interventions: explanation and elaboration. BMJ. 2009; 339:b2700. , , , et al.
- Job satisfaction and burnout in general practitioners [in Spanish]. Aten Primaria. 2003;31(4):227–233. , , , , , .
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- Differences in psychological effects in hospital doctors with and without post‐traumatic stress disorder. Br J Psychiatry. 2008;193(2):165–166. , , , , , .
- Crossing boundaries: family physicians' struggles to protect their private lives. Can Fam Physician. 2009;55(3):286–287.e5. , , , , .
- Emergency physicians accumulate more stress factors than other physicians: results from the French SESMAT study. Emerg Med J. 2011 May;28(5):397–410. Epub 2010 Dec 1. , , , , , , et al.
- Stress, burnout, and strategies for reducing them: what's the situation among Canadian family physicians? Can Fam Physician. 2008;54(2):234–235. , , .
- Worklife and satisfaction of hospitalists: toward flourishing careers. J Gen Intern Med. 2012;27(1):28–36. , , , , .
- MEMO (Minimizing Error, Maximizing Outcome) Investigators. Working conditions in primary care: physician reactions and care quality. Ann Intern Med. 2009 Jul 7;151(1):28–36. , , , , , , et al;
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- Influence of perceived organisational factors on job burnout: survey of community mental health staff. Br J Psychiatry. 2009;195(6):537–544. , , , et al.
- Frecuencia de los sintomas del syndrome de burnout en profesionales medicos. Rev Med Rosario. 2007;73:12–20. .
- Work‐related behaviour and experience patterns of physicians compared to other professions. Swiss Med Wkly. 2007;137(31‐32):448–453. , , .
- Psychiatric morbidity and burnout in the medical profession: an Italian study of general practitioners and hospital physicians. Psychother Psychosom. 2000;69(6):329–334. , .
- Duties of a doctor: UK doctors and good medical practice. Qual Health Care. 2000;9(1):14–22. , , .
- The job related burnout questionnaire: a multinational pilot study. Aust Fam Physician. 2002;31(11):1055–1056. , .
- Burn out among French general practitioners [in French]. Presse Med. 2004;33(22): 1569–1574. , , , , .
- Are burnout levels increasing? The experience of Israeli primary care physicians. Isr Med Assoc J. 2004; 6(8):451–455. , , .
- Psychosocial and professional characteristics of burnout in Swiss primary care practitioners: a cross‐sectional survey. Swiss Med Wkly. 2005;135(7‐8):101–108. , , , .
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- Burnout in Belgrade orthopaedic surgeons and general practitioners, a preliminary report. Acta Chir Iugosl. 2009; 56(2):53–59. , , , , , .
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- Career fit and burnout among academic faculty. Arch Intern Med. 2009;169(10):990–995. , , , et al.
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- Emotional exhaustion, life stress, and perceived control among medicine ward attending physicians: a randomized trial of 2‐ versus 4‐week ward rotations [abstract]. J Hosp Med. 2011; 6(4 suppl 2):S43–S44. , , , et al.
- The effort of being male: a survey on gender and burnout [in Italian]. Med Lav. 2011;102(3):286–296. , , , , , .
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- Burnout and satisfaction with work‐life balance among US physicians relative to the general US population. Arch Intern Med. 2012;172(18):1377–1385. , , , et al.
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- Epuisement professionnel et consummation de psychotropes chez les medecins hospitaliers. Alcoologie et Addictologie. 2005;27(4):303–308. , , .
- Working conditions and Work‐Family Conflict in German hospital physicians: psychosocial and organisational predictors and consequences. BMC Public Health. 2008;8:353. , , , , .
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- Effort‐reward‐ratio and burnout risk among female teachers and hospital‐employed female physicians: a comparison between professions [in German]. Arbeitsmed Sozialmed Umweltmed. 2012;47:396–406. , , , .
On heart failure and beta-blocker dosages
Getting the right therapeutic dose of any drug is not always easy. Using antibiotics to treat infection or antihypertensive drugs to lower blood pressure can be measured easily by simple physiologic measurements.
The treatment of heart failure with beta-blockers or ACE inhibitors, however, has been largely defined by clinical trials, which by their nature use one dosage and usually provide the clinician with limited information about the range of the best and most effective dosages. The rigor of choosing the correct dosage in clinical trials is often limited to small, underpowered phase II studies carried out well before the major phase III trials, which are designed to support efficacy and safety, usually at that one dosage. And still, physicians usually pick the lowest dose, following Hippocrates’ dictum to "do no harm." This dilemma has particular importance in picking the best dose of a beta-blocker in heart failure.
A recent presentation at the annual congress of the European Society of Cardiology by Dr. L. Brent Mitchell ("Full-dose beta-blockers still show benefit," October 2013, p. 26) sheds some important light on the benefit of maximum dosing with beta-blockers in heart failure patients treated with cardiac resynchronization therapy (CRT) or implantable cardiac defibrillators (ICDs) in whom bradycardia escape pacing was present.
Although all patients received standard drug therapy, patients receiving less than 50% of the full recommended dose of beta-blocker had a worse outcome in regard to mortality and rehospitalization when compared with patients receiving the full recommended dose, regardless of the beta-blocker used. Roughly one-half of these heart failure ICD/CRT patients were receiving less than half of the recommended dose for heart failure therapy. Older patients and those with more advance heart failure tended to receive the lower dose. In this patient population with pacemaker-controlled low heart rate, the issue of beta-blocker–induced bradycardia is no longer an issue: the higher the better.
In patients with atrial-controlled heart rates with sinus rhythm or atrial fibrillation, however, the induction of bradycardia has been an issue as physicians up-titrate dosages. The effect on morbidity and mortality of varying doses of metoprolol succinate (Toprol) was examined in the MERIT-HF trial (J. Am. Coll. Cardiol. 2002;40:491-8), in which physicians were encouraged to up-titrate to the highest dose. The limitation of up-titration was bradycardia. The high-dose (greater than 100 mg/day) and low-dose (100 mg/day or less) patients received 192 mg and 76 mg/day, respectively. Despite the different maximal doses, the final heart rate achieved with the up-titration was 68 beats/min. Patients receiving the high dose and low dose achieved the same relative benefit of therapy. The low-dose patient group was older and had a higher New York Heart Association functional class.
These observations suggest that there was a significant variability in the patient’s sensitivity to beta-blocker therapy, but the achievement of a low heart rate, regardless of dose, was effective in achieving the best therapeutic benefit. In a small dose-ranging study, patients were randomized to receive 50 or 200 mg/day of Toprol. The patients receiving 200 mg demonstrated an increase in ejection fraction and a decrease in end systolic volume, compared with the 50 mg–dose patients, who failed to evidence any hemodynamic improvement (Circulation 2007;116:49-56).
These observations emphasize the uncertainties of drug dosing in heart failure with our standard therapy. The benefit of high doses of beta-blockers in the ICD/CRT trial in patients whose heart rate was controlled with bradycardia pacing provides important support for the use of high doses in these individuals. In patients whose heart rate was controlled by atrial rhythms in the MERIT-HF trial, heart rate became the major limitation of drug therapy. In these patients, up-titration to maximal heart rate expressed the presence of a variable sensitivity to beta-blockade. The achievement of a slow heart rate, regardless of dose, appeared to achieve a similar benefit on heart failure outcomes.
Dr. Goldstein, medical editor of Cardiology News, is professor of medicine at Wayne State University and division head emeritus of cardiovascular medicine at Henry Ford Hospital, both in Detroit. He is on data safety monitoring committees for the National Institutes of Health and several pharmaceutical companies, and was the co-principal investigator of the MERIT-HF trial.
Getting the right therapeutic dose of any drug is not always easy. Using antibiotics to treat infection or antihypertensive drugs to lower blood pressure can be measured easily by simple physiologic measurements.
The treatment of heart failure with beta-blockers or ACE inhibitors, however, has been largely defined by clinical trials, which by their nature use one dosage and usually provide the clinician with limited information about the range of the best and most effective dosages. The rigor of choosing the correct dosage in clinical trials is often limited to small, underpowered phase II studies carried out well before the major phase III trials, which are designed to support efficacy and safety, usually at that one dosage. And still, physicians usually pick the lowest dose, following Hippocrates’ dictum to "do no harm." This dilemma has particular importance in picking the best dose of a beta-blocker in heart failure.
A recent presentation at the annual congress of the European Society of Cardiology by Dr. L. Brent Mitchell ("Full-dose beta-blockers still show benefit," October 2013, p. 26) sheds some important light on the benefit of maximum dosing with beta-blockers in heart failure patients treated with cardiac resynchronization therapy (CRT) or implantable cardiac defibrillators (ICDs) in whom bradycardia escape pacing was present.
Although all patients received standard drug therapy, patients receiving less than 50% of the full recommended dose of beta-blocker had a worse outcome in regard to mortality and rehospitalization when compared with patients receiving the full recommended dose, regardless of the beta-blocker used. Roughly one-half of these heart failure ICD/CRT patients were receiving less than half of the recommended dose for heart failure therapy. Older patients and those with more advance heart failure tended to receive the lower dose. In this patient population with pacemaker-controlled low heart rate, the issue of beta-blocker–induced bradycardia is no longer an issue: the higher the better.
In patients with atrial-controlled heart rates with sinus rhythm or atrial fibrillation, however, the induction of bradycardia has been an issue as physicians up-titrate dosages. The effect on morbidity and mortality of varying doses of metoprolol succinate (Toprol) was examined in the MERIT-HF trial (J. Am. Coll. Cardiol. 2002;40:491-8), in which physicians were encouraged to up-titrate to the highest dose. The limitation of up-titration was bradycardia. The high-dose (greater than 100 mg/day) and low-dose (100 mg/day or less) patients received 192 mg and 76 mg/day, respectively. Despite the different maximal doses, the final heart rate achieved with the up-titration was 68 beats/min. Patients receiving the high dose and low dose achieved the same relative benefit of therapy. The low-dose patient group was older and had a higher New York Heart Association functional class.
These observations suggest that there was a significant variability in the patient’s sensitivity to beta-blocker therapy, but the achievement of a low heart rate, regardless of dose, was effective in achieving the best therapeutic benefit. In a small dose-ranging study, patients were randomized to receive 50 or 200 mg/day of Toprol. The patients receiving 200 mg demonstrated an increase in ejection fraction and a decrease in end systolic volume, compared with the 50 mg–dose patients, who failed to evidence any hemodynamic improvement (Circulation 2007;116:49-56).
These observations emphasize the uncertainties of drug dosing in heart failure with our standard therapy. The benefit of high doses of beta-blockers in the ICD/CRT trial in patients whose heart rate was controlled with bradycardia pacing provides important support for the use of high doses in these individuals. In patients whose heart rate was controlled by atrial rhythms in the MERIT-HF trial, heart rate became the major limitation of drug therapy. In these patients, up-titration to maximal heart rate expressed the presence of a variable sensitivity to beta-blockade. The achievement of a slow heart rate, regardless of dose, appeared to achieve a similar benefit on heart failure outcomes.
Dr. Goldstein, medical editor of Cardiology News, is professor of medicine at Wayne State University and division head emeritus of cardiovascular medicine at Henry Ford Hospital, both in Detroit. He is on data safety monitoring committees for the National Institutes of Health and several pharmaceutical companies, and was the co-principal investigator of the MERIT-HF trial.
Getting the right therapeutic dose of any drug is not always easy. Using antibiotics to treat infection or antihypertensive drugs to lower blood pressure can be measured easily by simple physiologic measurements.
The treatment of heart failure with beta-blockers or ACE inhibitors, however, has been largely defined by clinical trials, which by their nature use one dosage and usually provide the clinician with limited information about the range of the best and most effective dosages. The rigor of choosing the correct dosage in clinical trials is often limited to small, underpowered phase II studies carried out well before the major phase III trials, which are designed to support efficacy and safety, usually at that one dosage. And still, physicians usually pick the lowest dose, following Hippocrates’ dictum to "do no harm." This dilemma has particular importance in picking the best dose of a beta-blocker in heart failure.
A recent presentation at the annual congress of the European Society of Cardiology by Dr. L. Brent Mitchell ("Full-dose beta-blockers still show benefit," October 2013, p. 26) sheds some important light on the benefit of maximum dosing with beta-blockers in heart failure patients treated with cardiac resynchronization therapy (CRT) or implantable cardiac defibrillators (ICDs) in whom bradycardia escape pacing was present.
Although all patients received standard drug therapy, patients receiving less than 50% of the full recommended dose of beta-blocker had a worse outcome in regard to mortality and rehospitalization when compared with patients receiving the full recommended dose, regardless of the beta-blocker used. Roughly one-half of these heart failure ICD/CRT patients were receiving less than half of the recommended dose for heart failure therapy. Older patients and those with more advance heart failure tended to receive the lower dose. In this patient population with pacemaker-controlled low heart rate, the issue of beta-blocker–induced bradycardia is no longer an issue: the higher the better.
In patients with atrial-controlled heart rates with sinus rhythm or atrial fibrillation, however, the induction of bradycardia has been an issue as physicians up-titrate dosages. The effect on morbidity and mortality of varying doses of metoprolol succinate (Toprol) was examined in the MERIT-HF trial (J. Am. Coll. Cardiol. 2002;40:491-8), in which physicians were encouraged to up-titrate to the highest dose. The limitation of up-titration was bradycardia. The high-dose (greater than 100 mg/day) and low-dose (100 mg/day or less) patients received 192 mg and 76 mg/day, respectively. Despite the different maximal doses, the final heart rate achieved with the up-titration was 68 beats/min. Patients receiving the high dose and low dose achieved the same relative benefit of therapy. The low-dose patient group was older and had a higher New York Heart Association functional class.
These observations suggest that there was a significant variability in the patient’s sensitivity to beta-blocker therapy, but the achievement of a low heart rate, regardless of dose, was effective in achieving the best therapeutic benefit. In a small dose-ranging study, patients were randomized to receive 50 or 200 mg/day of Toprol. The patients receiving 200 mg demonstrated an increase in ejection fraction and a decrease in end systolic volume, compared with the 50 mg–dose patients, who failed to evidence any hemodynamic improvement (Circulation 2007;116:49-56).
These observations emphasize the uncertainties of drug dosing in heart failure with our standard therapy. The benefit of high doses of beta-blockers in the ICD/CRT trial in patients whose heart rate was controlled with bradycardia pacing provides important support for the use of high doses in these individuals. In patients whose heart rate was controlled by atrial rhythms in the MERIT-HF trial, heart rate became the major limitation of drug therapy. In these patients, up-titration to maximal heart rate expressed the presence of a variable sensitivity to beta-blockade. The achievement of a slow heart rate, regardless of dose, appeared to achieve a similar benefit on heart failure outcomes.
Dr. Goldstein, medical editor of Cardiology News, is professor of medicine at Wayne State University and division head emeritus of cardiovascular medicine at Henry Ford Hospital, both in Detroit. He is on data safety monitoring committees for the National Institutes of Health and several pharmaceutical companies, and was the co-principal investigator of the MERIT-HF trial.
Agency Funding for Healthcare Research Could Benefit Hospital Medicine
David O. Meltzer, MD, PhD, MHM, wants hospitalists to take advantage of the recent announcement by the Patient-Centered Outcomes Research Institute (PCORI) that it intends to award $300 million by the end of this year, and more in the future. And if that means calling him directly, go for it.
Dr. Meltzer, chief of the section of hospital medicine at the University of Chicago, is a member of PCORI's methodology committee. He says in a question-and-answer session with The Hospitalist that PCORI could be a valuable resource and funding source for hospitalist researchers.
Question: What should hospitalists know about PCORI?
Answer: PCORI is focused on figuring out how to improve the effectiveness of healthcare, and it is placing a strong emphasis on the importance of engaging patients and other stakeholders in that process. Also, PCORI is trying to ensure that research recognizes the potential differences between patient subgroups, and even individual patients, to the maximum degree possible.
Q: Given PCORI's focus on outcomes, how can HM researchers pitch the type of projects that would be eligible for funding?
A: They should focus on questions that matter to patients, and engage diverse stakeholders and patients in identifying those questions.
Q: How helpful for the specialty is it to have a leading member involved with the institute?
A: PCORI is becoming an important funder of research in the United States, and I think all specialties need to know about it. PCORI is working hard to get the word out to all specialties, but I hope my colleagues in hospital medicine will feel free to call if I can help them interpret PCORI's guidance about how they can best engage with it. TH
Visit our website for more information on patient-centered care.
David O. Meltzer, MD, PhD, MHM, wants hospitalists to take advantage of the recent announcement by the Patient-Centered Outcomes Research Institute (PCORI) that it intends to award $300 million by the end of this year, and more in the future. And if that means calling him directly, go for it.
Dr. Meltzer, chief of the section of hospital medicine at the University of Chicago, is a member of PCORI's methodology committee. He says in a question-and-answer session with The Hospitalist that PCORI could be a valuable resource and funding source for hospitalist researchers.
Question: What should hospitalists know about PCORI?
Answer: PCORI is focused on figuring out how to improve the effectiveness of healthcare, and it is placing a strong emphasis on the importance of engaging patients and other stakeholders in that process. Also, PCORI is trying to ensure that research recognizes the potential differences between patient subgroups, and even individual patients, to the maximum degree possible.
Q: Given PCORI's focus on outcomes, how can HM researchers pitch the type of projects that would be eligible for funding?
A: They should focus on questions that matter to patients, and engage diverse stakeholders and patients in identifying those questions.
Q: How helpful for the specialty is it to have a leading member involved with the institute?
A: PCORI is becoming an important funder of research in the United States, and I think all specialties need to know about it. PCORI is working hard to get the word out to all specialties, but I hope my colleagues in hospital medicine will feel free to call if I can help them interpret PCORI's guidance about how they can best engage with it. TH
Visit our website for more information on patient-centered care.
David O. Meltzer, MD, PhD, MHM, wants hospitalists to take advantage of the recent announcement by the Patient-Centered Outcomes Research Institute (PCORI) that it intends to award $300 million by the end of this year, and more in the future. And if that means calling him directly, go for it.
Dr. Meltzer, chief of the section of hospital medicine at the University of Chicago, is a member of PCORI's methodology committee. He says in a question-and-answer session with The Hospitalist that PCORI could be a valuable resource and funding source for hospitalist researchers.
Question: What should hospitalists know about PCORI?
Answer: PCORI is focused on figuring out how to improve the effectiveness of healthcare, and it is placing a strong emphasis on the importance of engaging patients and other stakeholders in that process. Also, PCORI is trying to ensure that research recognizes the potential differences between patient subgroups, and even individual patients, to the maximum degree possible.
Q: Given PCORI's focus on outcomes, how can HM researchers pitch the type of projects that would be eligible for funding?
A: They should focus on questions that matter to patients, and engage diverse stakeholders and patients in identifying those questions.
Q: How helpful for the specialty is it to have a leading member involved with the institute?
A: PCORI is becoming an important funder of research in the United States, and I think all specialties need to know about it. PCORI is working hard to get the word out to all specialties, but I hope my colleagues in hospital medicine will feel free to call if I can help them interpret PCORI's guidance about how they can best engage with it. TH
Visit our website for more information on patient-centered care.
Readmission Rates Not Effective Quality Measure of Pediatric Patient Care
A new study in Pediatrics finds limited use for hospital readmission rates as a meaningful quality measure when it comes to pediatric patient care.
By examining 30- and 60-day readmission rates for 958 hospitals that admit children for seven common inpatient conditions, researchers found very few that could be considered either high or low performers. In addition, pediatric 30-day readmission rates overall were low, at less than 10% for all conditions.
Naomi Bardach, MD, MAS, department of pediatrics at the University of California at San Francisco and the report's lead author, emphasizes that her study was a statistical analysis of readmission rates without assessing whether they should be a focus for quality improvement. "They might be useful for larger efforts, such as multi-institution collaboratives to improve care for a given condition," Dr. Bardach says. "But it is clear that readmission rates are not useful for comparing individual hospital performance."
An accompanying editorial noted that delaying hospital discharges even by four hours in an attempt to forestall readmissions could prove more costly in the end.
Although much of the national focus on 30-day hospital readmissions has been on the Medicare-age population, the pediatric realm is getting more attention, Dr. Bardach says. For example, the Children's Health Insurance Program Reauthorization Act of 2009 funded seven research cooperatives to develop core measures for assessing the state of children’s healthcare quality. TH
Visit our website for more information about pediatric readmissions rates.
A new study in Pediatrics finds limited use for hospital readmission rates as a meaningful quality measure when it comes to pediatric patient care.
By examining 30- and 60-day readmission rates for 958 hospitals that admit children for seven common inpatient conditions, researchers found very few that could be considered either high or low performers. In addition, pediatric 30-day readmission rates overall were low, at less than 10% for all conditions.
Naomi Bardach, MD, MAS, department of pediatrics at the University of California at San Francisco and the report's lead author, emphasizes that her study was a statistical analysis of readmission rates without assessing whether they should be a focus for quality improvement. "They might be useful for larger efforts, such as multi-institution collaboratives to improve care for a given condition," Dr. Bardach says. "But it is clear that readmission rates are not useful for comparing individual hospital performance."
An accompanying editorial noted that delaying hospital discharges even by four hours in an attempt to forestall readmissions could prove more costly in the end.
Although much of the national focus on 30-day hospital readmissions has been on the Medicare-age population, the pediatric realm is getting more attention, Dr. Bardach says. For example, the Children's Health Insurance Program Reauthorization Act of 2009 funded seven research cooperatives to develop core measures for assessing the state of children’s healthcare quality. TH
Visit our website for more information about pediatric readmissions rates.
A new study in Pediatrics finds limited use for hospital readmission rates as a meaningful quality measure when it comes to pediatric patient care.
By examining 30- and 60-day readmission rates for 958 hospitals that admit children for seven common inpatient conditions, researchers found very few that could be considered either high or low performers. In addition, pediatric 30-day readmission rates overall were low, at less than 10% for all conditions.
Naomi Bardach, MD, MAS, department of pediatrics at the University of California at San Francisco and the report's lead author, emphasizes that her study was a statistical analysis of readmission rates without assessing whether they should be a focus for quality improvement. "They might be useful for larger efforts, such as multi-institution collaboratives to improve care for a given condition," Dr. Bardach says. "But it is clear that readmission rates are not useful for comparing individual hospital performance."
An accompanying editorial noted that delaying hospital discharges even by four hours in an attempt to forestall readmissions could prove more costly in the end.
Although much of the national focus on 30-day hospital readmissions has been on the Medicare-age population, the pediatric realm is getting more attention, Dr. Bardach says. For example, the Children's Health Insurance Program Reauthorization Act of 2009 funded seven research cooperatives to develop core measures for assessing the state of children’s healthcare quality. TH
Visit our website for more information about pediatric readmissions rates.
Pay disparities and gender
As we all know, a healthy work-life balance can be very difficult to achieve, let alone maintain. That is why many of us got into hospital medicine in the first place.
When studies show that in America, male hospitalists make more on average than their female counterparts, it is assumed that there is a strong correlation between hours worked and pay. But could there be other factors as well? In Canada, at least, that seems to be the case. A research team at the University of Montreal reviewed the billing information of 870 Quebec practitioners with a focus on procedures in elderly diabetic patients. Male and female practitioners were equally represented. The results: Female doctors were far more compliant with the Canadian Diabetes Association practice guidelines, but males were more productive when it came to procedures.
Specifically, male physicians reported close to 1,000 more procedures annually compared with female physicians. So, the question comes to mind: Who is more profitable for hospitals, physicians who perform more procedures that can be billed at a higher rate, or those who seem to focus more attention on the bread and butter of care, so to speak? After all, if patients understand their condition and get the appropriate care, aren't they less likely to require rehospitalization? No definitive answers yet, but this study does make you want to go, "Hmm."
While the U.S. health care system certainly differs from Canada's, this article does bring up intriguing issues, some which just may be worth considering as we assess and improve the practice styles and compensation models for hospitalists. A 2012 Today's Hospitalist survey cited in an article titled, "Why do women hospitalists make less money?" sheds additional light on the subject. Yes, there is still a gender gap between male and female physicians. There are numerous hypotheses, as well as some hard data to explain some of these differences, though many still believe part of the issue is a persistent gender bias.
The article noted that males work a few more shifts than females, 16.68 vs 15.96, but this is only a 5% difference in work hours. Other data support a compensation difference based on the different payment models. Slightly more men are in a payment model that is 100% productivity-based or a combination of salary and productivity, and these models tend to pay more than do positions that are straight salary. Still, for a variety of reasons, some clear and others obscure, female hospitalists earn an average of $35,000 less than do their male counterparts.
Acknowledging a disparity exists is not enough. The reasons for this disparity should be further evaluated and addressed. Perhaps they are strongly the result of lifestyle choices, types of positions females prefer, and other nongender-related issues, but we owe it ourselves to gain further clarity on this very real issue.
Dr. Hester is a hospitalist with Baltimore-Washington Medical Center who has a passion for empowering patients to partner in their health care. She is the creator of the Patient Whiz, a patient-engagement app for iOS.
As we all know, a healthy work-life balance can be very difficult to achieve, let alone maintain. That is why many of us got into hospital medicine in the first place.
When studies show that in America, male hospitalists make more on average than their female counterparts, it is assumed that there is a strong correlation between hours worked and pay. But could there be other factors as well? In Canada, at least, that seems to be the case. A research team at the University of Montreal reviewed the billing information of 870 Quebec practitioners with a focus on procedures in elderly diabetic patients. Male and female practitioners were equally represented. The results: Female doctors were far more compliant with the Canadian Diabetes Association practice guidelines, but males were more productive when it came to procedures.
Specifically, male physicians reported close to 1,000 more procedures annually compared with female physicians. So, the question comes to mind: Who is more profitable for hospitals, physicians who perform more procedures that can be billed at a higher rate, or those who seem to focus more attention on the bread and butter of care, so to speak? After all, if patients understand their condition and get the appropriate care, aren't they less likely to require rehospitalization? No definitive answers yet, but this study does make you want to go, "Hmm."
While the U.S. health care system certainly differs from Canada's, this article does bring up intriguing issues, some which just may be worth considering as we assess and improve the practice styles and compensation models for hospitalists. A 2012 Today's Hospitalist survey cited in an article titled, "Why do women hospitalists make less money?" sheds additional light on the subject. Yes, there is still a gender gap between male and female physicians. There are numerous hypotheses, as well as some hard data to explain some of these differences, though many still believe part of the issue is a persistent gender bias.
The article noted that males work a few more shifts than females, 16.68 vs 15.96, but this is only a 5% difference in work hours. Other data support a compensation difference based on the different payment models. Slightly more men are in a payment model that is 100% productivity-based or a combination of salary and productivity, and these models tend to pay more than do positions that are straight salary. Still, for a variety of reasons, some clear and others obscure, female hospitalists earn an average of $35,000 less than do their male counterparts.
Acknowledging a disparity exists is not enough. The reasons for this disparity should be further evaluated and addressed. Perhaps they are strongly the result of lifestyle choices, types of positions females prefer, and other nongender-related issues, but we owe it ourselves to gain further clarity on this very real issue.
Dr. Hester is a hospitalist with Baltimore-Washington Medical Center who has a passion for empowering patients to partner in their health care. She is the creator of the Patient Whiz, a patient-engagement app for iOS.
As we all know, a healthy work-life balance can be very difficult to achieve, let alone maintain. That is why many of us got into hospital medicine in the first place.
When studies show that in America, male hospitalists make more on average than their female counterparts, it is assumed that there is a strong correlation between hours worked and pay. But could there be other factors as well? In Canada, at least, that seems to be the case. A research team at the University of Montreal reviewed the billing information of 870 Quebec practitioners with a focus on procedures in elderly diabetic patients. Male and female practitioners were equally represented. The results: Female doctors were far more compliant with the Canadian Diabetes Association practice guidelines, but males were more productive when it came to procedures.
Specifically, male physicians reported close to 1,000 more procedures annually compared with female physicians. So, the question comes to mind: Who is more profitable for hospitals, physicians who perform more procedures that can be billed at a higher rate, or those who seem to focus more attention on the bread and butter of care, so to speak? After all, if patients understand their condition and get the appropriate care, aren't they less likely to require rehospitalization? No definitive answers yet, but this study does make you want to go, "Hmm."
While the U.S. health care system certainly differs from Canada's, this article does bring up intriguing issues, some which just may be worth considering as we assess and improve the practice styles and compensation models for hospitalists. A 2012 Today's Hospitalist survey cited in an article titled, "Why do women hospitalists make less money?" sheds additional light on the subject. Yes, there is still a gender gap between male and female physicians. There are numerous hypotheses, as well as some hard data to explain some of these differences, though many still believe part of the issue is a persistent gender bias.
The article noted that males work a few more shifts than females, 16.68 vs 15.96, but this is only a 5% difference in work hours. Other data support a compensation difference based on the different payment models. Slightly more men are in a payment model that is 100% productivity-based or a combination of salary and productivity, and these models tend to pay more than do positions that are straight salary. Still, for a variety of reasons, some clear and others obscure, female hospitalists earn an average of $35,000 less than do their male counterparts.
Acknowledging a disparity exists is not enough. The reasons for this disparity should be further evaluated and addressed. Perhaps they are strongly the result of lifestyle choices, types of positions females prefer, and other nongender-related issues, but we owe it ourselves to gain further clarity on this very real issue.
Dr. Hester is a hospitalist with Baltimore-Washington Medical Center who has a passion for empowering patients to partner in their health care. She is the creator of the Patient Whiz, a patient-engagement app for iOS.
Self-administration of romiplostim in patients with chronic immune thrombocytopenia
Background Romiplostim increases platelet counts in ITP and is typically injected at clinic visits.
Objective To estimate the efficacy and safety of romiplostim self-administration, we evaluated data from an open-label extension study in a post hoc analysis.
Methods Patients received weekly romiplostim with dose adjustments to target platelet counts of 50-200 x 109/L. Patients with a stable dose and platelet counts of 50-200 x 109/L for 3 or more weeks could begin self-administration if investigators deemed it appropriate, returning to study sites every 4 weeks.
Results Of 292 patients, 239 (82%) initiated self-administration for a median of 74 (Q1-Q3:56-164) weeks. Twenty-eight of the 239 (12%) discontinued self-administration (investigator or sponsor decision: 19, patient request: 6, noncompliance: 3). The median average weekly dose for patients self-administering romiplostim was 4.1 g/kg. The romiplostim dose was adjusted in 40 (17%) of the 239 patients in the first 8 weeks of self-administration; 84 (35%) in the first 6 months. Patients had a platelet response (more than 50 x 109/L) for a mean of 75.1% of weeks. The adverse event (AE) rate was 18.3/100 patient-weeks, with 0.8 serious AEs/100 patient-weeks. Fourteen AEs led to withdrawal; none related to self-administration.
Limitations The analysis was post hoc. Lack of a randomized comparator group may have resulted in differences between patient populations. No distinctions could be made between constant and intermittent self-administration or between adverse events occurring during self-administration or administration at the study site.
Conclusions Patients were able to maintain platelet responses for a mean of 75% of the time without new safety issues while self-administering romiplostim.
To read the full article, click on the PDF icon at the top of this introduction.
Background Romiplostim increases platelet counts in ITP and is typically injected at clinic visits.
Objective To estimate the efficacy and safety of romiplostim self-administration, we evaluated data from an open-label extension study in a post hoc analysis.
Methods Patients received weekly romiplostim with dose adjustments to target platelet counts of 50-200 x 109/L. Patients with a stable dose and platelet counts of 50-200 x 109/L for 3 or more weeks could begin self-administration if investigators deemed it appropriate, returning to study sites every 4 weeks.
Results Of 292 patients, 239 (82%) initiated self-administration for a median of 74 (Q1-Q3:56-164) weeks. Twenty-eight of the 239 (12%) discontinued self-administration (investigator or sponsor decision: 19, patient request: 6, noncompliance: 3). The median average weekly dose for patients self-administering romiplostim was 4.1 g/kg. The romiplostim dose was adjusted in 40 (17%) of the 239 patients in the first 8 weeks of self-administration; 84 (35%) in the first 6 months. Patients had a platelet response (more than 50 x 109/L) for a mean of 75.1% of weeks. The adverse event (AE) rate was 18.3/100 patient-weeks, with 0.8 serious AEs/100 patient-weeks. Fourteen AEs led to withdrawal; none related to self-administration.
Limitations The analysis was post hoc. Lack of a randomized comparator group may have resulted in differences between patient populations. No distinctions could be made between constant and intermittent self-administration or between adverse events occurring during self-administration or administration at the study site.
Conclusions Patients were able to maintain platelet responses for a mean of 75% of the time without new safety issues while self-administering romiplostim.
To read the full article, click on the PDF icon at the top of this introduction.
Background Romiplostim increases platelet counts in ITP and is typically injected at clinic visits.
Objective To estimate the efficacy and safety of romiplostim self-administration, we evaluated data from an open-label extension study in a post hoc analysis.
Methods Patients received weekly romiplostim with dose adjustments to target platelet counts of 50-200 x 109/L. Patients with a stable dose and platelet counts of 50-200 x 109/L for 3 or more weeks could begin self-administration if investigators deemed it appropriate, returning to study sites every 4 weeks.
Results Of 292 patients, 239 (82%) initiated self-administration for a median of 74 (Q1-Q3:56-164) weeks. Twenty-eight of the 239 (12%) discontinued self-administration (investigator or sponsor decision: 19, patient request: 6, noncompliance: 3). The median average weekly dose for patients self-administering romiplostim was 4.1 g/kg. The romiplostim dose was adjusted in 40 (17%) of the 239 patients in the first 8 weeks of self-administration; 84 (35%) in the first 6 months. Patients had a platelet response (more than 50 x 109/L) for a mean of 75.1% of weeks. The adverse event (AE) rate was 18.3/100 patient-weeks, with 0.8 serious AEs/100 patient-weeks. Fourteen AEs led to withdrawal; none related to self-administration.
Limitations The analysis was post hoc. Lack of a randomized comparator group may have resulted in differences between patient populations. No distinctions could be made between constant and intermittent self-administration or between adverse events occurring during self-administration or administration at the study site.
Conclusions Patients were able to maintain platelet responses for a mean of 75% of the time without new safety issues while self-administering romiplostim.
To read the full article, click on the PDF icon at the top of this introduction.