Abstract
Whether health care provider burnout contributes to lower quality of patient care is unclear. To estimate the overall relationship between burnout and quality of care and to evaluate whether published studies provide exaggerated estimates of this relationship. MEDLINE, PsycINFO, Health and Psychosocial Instruments (EBSCO), Mental Measurements Yearbook (EBSCO), EMBASE (Elsevier), and Web of Science (Clarivate Analytics), with no language restrictions, from inception through 28 May 2019. Peer-reviewed publications, in any language, quantifying health care provider burnout in relation to quality of patient care. 2 reviewers independently selected studies, extracted measures of association of burnout and quality of care, and assessed potential bias by using the Ioannidis (excess significance) and Egger (small-study effect) tests. A total of 11703 citations were identified, from which 123 publications with 142 study populations encompassing 241553 health care providers were selected. Quality-of-care outcomes were grouped into 5 categories: best practices (n= 14), communication (n= 5), medical errors (n= 32), patient outcomes (n= 17), and quality and safety (n= 74). Relations between burnout and quality of care were highly heterogeneous (I2= 93.4% to 98.8%). Of 114 unique burnout-quality combinations, 58 indicated burnout related to poor-quality care, 6 indicated burnout related to high-quality care, and 50 showed no significant effect. Excess significance was apparent (73% of studies observed vs. 62% predicted to have statistically significant results; P= 0.011). This indicator of potential bias was most prominent for the least-rigorous quality measures of best practices and quality and safety. Studies were primarily observational; neither causality nor directionality could be determined. Burnout in health care professionals frequently is associated with poor-quality care in the published literature. The true effect size may be smaller than reported. Future studies should prespecify outcomes to reduce the risk for exaggerated effect size estimates. Stanford Maternal and Child Health Research Institute.
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