Whether health care provider burnout contributes to lower quality of patient care is unclear

Study Purpose: To estimate the overall relationship between burnout and quality of care and to evaluate whether published studies provide exaggerated estimates of this relationship.

Data Sources: 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.

Study Selection: Peer-reviewed publications, in any language, quantifying health care provider burnout in relation to quality of patient care.

Data Extraction: 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.

Data Synthesis: A total of 11 703 citations were identified, from which 123 publications with 142 study populations encompassing 241 553 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.

Limitation: Studies were primarily observational; neither causality nor directionality could be determined.

Conclusion: 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.