Ross W Hilliard1, Jacqueline Haskell2, Rebekah L Gardner1,2. 1. Department of Medicine, Division of General Internal Medicine, Warren Alpert Medical School of Brown University, Providence, Rhode Island, USA. 2. Healthcentric Advisors, Providence, Rhode Island, USA.
Abstract
OBJECTIVE: The study sought to examine the association between clinician burnout and measures of electronic health record (EHR) workload and efficiency, using vendor-derived EHR action log data. MATERIALS AND METHODS: We combined data from a statewide clinician survey on burnout with Epic EHR data from the ambulatory sites of 2 large health systems; the combined dataset included 422 clinicians. We examined whether specific EHR workload and efficiency measures were independently associated with burnout symptoms, using multivariable logistic regression and controlling for clinician characteristics. RESULTS: Clinicians with the highest volume of patient call messages had almost 4 times the odds of burnout compared with clinicians with the fewest (adjusted odds ratio, 3.81; 95% confidence interval, 1.44-10.14; P = .007). No other workload measures were significantly associated with burnout. No efficiency variables were significantly associated with burnout in the main analysis; however, in a subset of clinicians for whom note entry data were available, clinicians in the top quartile of copy and paste use were significantly less likely to report burnout, with an adjusted odds ratio of 0.22 (95% confidence interval, 0.05-0.93; P = .039). DISCUSSION: High volumes of patient call messages were significantly associated with clinician burnout, even when accounting for other measures of workload and efficiency. In the EHR, "patient calls" encompass many of the inbox tasks occurring outside of face-to-face visits and likely represent an important target for improving clinician well-being. CONCLUSIONS: Our results suggest that increased workload is associated with burnout and that EHR efficiency tools are not likely to reduce burnout symptoms, with the exception of copy and paste.
OBJECTIVE: The study sought to examine the association between clinician burnout and measures of electronic health record (EHR) workload and efficiency, using vendor-derived EHR action log data. MATERIALS AND METHODS: We combined data from a statewide clinician survey on burnout with Epic EHR data from the ambulatory sites of 2 large health systems; the combined dataset included 422 clinicians. We examined whether specific EHR workload and efficiency measures were independently associated with burnout symptoms, using multivariable logistic regression and controlling for clinician characteristics. RESULTS: Clinicians with the highest volume of patient call messages had almost 4 times the odds of burnout compared with clinicians with the fewest (adjusted odds ratio, 3.81; 95% confidence interval, 1.44-10.14; P = .007). No other workload measures were significantly associated with burnout. No efficiency variables were significantly associated with burnout in the main analysis; however, in a subset of clinicians for whom note entry data were available, clinicians in the top quartile of copy and paste use were significantly less likely to report burnout, with an adjusted odds ratio of 0.22 (95% confidence interval, 0.05-0.93; P = .039). DISCUSSION: High volumes of patient call messages were significantly associated with clinician burnout, even when accounting for other measures of workload and efficiency. In the EHR, "patient calls" encompass many of the inbox tasks occurring outside of face-to-face visits and likely represent an important target for improving clinician well-being. CONCLUSIONS: Our results suggest that increased workload is associated with burnout and that EHR efficiency tools are not likely to reduce burnout symptoms, with the exception of copy and paste.
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