The Burden of Burnout: An Assessment of Burnout Among Internal Medicine Residents After the 2011 Duty Hour Changes.
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This study sought to determine burnout prevalence and factors associated with burnout in internal medicine residents after introduction of the 2011 ACGME duty hour rules. Burnout was evaluated using an anonymized, abbreviated version of the Maslach Burnout Inventory. Surveys were collected biweekly for 48 weeks during the 2013-2014 academic year. Burnout severity was compared across subgroups and time. A score of 3 or higher signified burnout. Overall, 944 of 3936 (24%) surveys were completed. The mean burnout score across all surveys was 2.8. Categorical residents had higher burnout severity than noncategorical residents (2.9 vs 2.7, P = .005). Postgraduate year 2 residents had the highest burnout severity by year (3.1, P < .001). Residents on inpatient rotations had higher burnout severity than residents on outpatient or consultation rotations (3.1 vs 2.2 vs 2.2, P < .001). Night float rotations had the highest severity (3.8). Burnout remains a significant problem even with recent duty hour modifications.
Published Version (Please cite this version)10.1177/1062860615625802
Publication InfoBae, J; Boggan, Joel; Elmariah, H; Thomas, S; & Zaas, Aimee Kirsch (2016). The Burden of Burnout: An Assessment of Burnout Among Internal Medicine Residents After the 2011 Duty Hour Changes. Am J Med Qual. 10.1177/1062860615625802. Retrieved from http://hdl.handle.net/10161/12042.
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Assistant Professor of Medicine
My current QI and research projects include work on readmissions, clinical documentation improvement, ORYX measures, medication reconciliation, and optimization of chronic kidney disease and cardiovascular disease management and referral patterns. I also oversee QI education and projects for the Internal Medicine Residency Program at Duke as the Associate Program Director for Quality Improvement and Patient Safety and help co-lead our Residency Patient Safety and Quality Council. <br
Associate Professor of Medicine
Medical education Genomic applications for diagnosis of infectious diseases Genomic applications for prediction of infectious diseases
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