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. 2021 Apr 1;4(4):e215686.
doi: 10.1001/jamanetworkopen.2021.5686.

Clinician Burnout Associated With Sex, Clinician Type, Work Culture, and Use of Electronic Health Records

Eugenia McPeek-Hinz  1 , Mina Boazak  2   3 , J Bryan Sexton  2   4 , Kathryn C Adair  4 , Vivian West  5 , Benjamin A Goldstein  3 , Robert S Alphin  6 , Sherif Idris  6 , W Ed Hammond  5   7 , Shelley E Hwang  8 , Jonathan Bae  1   9
Affiliations

Clinician Burnout Associated With Sex, Clinician Type, Work Culture, and Use of Electronic Health Records

Eugenia McPeek-Hinz et al. JAMA Netw Open. .

Abstract

Importance: Electronic health records (EHRs) are considered a potentially significant contributor to clinician burnout.

Objective: To describe the association of EHR usage, sex, and work culture with burnout for 3 types of clinicians at an academic medical institution.

Design, setting, and participants: This cross-sectional study of 1310 clinicians at a large tertiary care academic medical center analyzed EHR usage metrics for the month of April 2019 with results from a well-being survey from May 2019. Participants included attending physicians, advanced practice providers (APPs), and house staff from various specialties. Data were analyzed between March 2020 and February 2021.

Exposures: Clinician demographic characteristics, EHR metadata, and an institution-wide survey.

Main outcomes and measures: Study metrics included clinician demographic data, burnout score, well-being measures, and EHR usage metadata.

Results: Of the 1310 clinicians analyzed, 542 (41.4%) were men (mean [SD] age, 47.3 [11.6] years; 448 [82.7%] White clinicians, 52 [9.6%] Asian clinicians, and 21 [3.9%] Black clinicians) and 768 (58.6%) were women (mean [SD] age, 42.6 [10.3] years; 573 [74.6%] White clinicians, 105 [13.7%] Asian clinicians, and 50 [6.5%] Black clinicians). Women reported more burnout (survey score ≥50: women, 423 [52.0%] vs men, 258 [47.6%]; P = .008) overall. No significant differences in EHR usage were found by sex for multiple metrics of time in the EHR, metrics of volume of clinical encounters, or differences in products of clinical care. Multivariate analysis of burnout revealed that work culture domains were significantly associated with self-reported results for commitment (odds ratio [OR], 0.542; 95% CI, 0.427-0.688; P < .001) and work-life balance (OR, 0.643; 95% CI, 0.559-0.739; P < .001). Clinician sex significantly contributed to burnout, with women having a greater likelihood of burnout compared with men (OR, 1.33; 95% CI, 1.01-1.75; P = .04). An increased number of days spent using the EHR system was associated with less likelihood of burnout (OR, 0.966; 95% CI, 0.937-0.996; P = .03). Overall, EHR metrics accounted for 1.3% of model variance (P = .001) compared with work culture accounting for 17.6% of variance (P < .001).

Conclusions and relevance: In this cross-sectional study, sex-based differences in EHR usage and burnout were found in clinicians. These results also suggest that local work culture factors may contribute more to burnout than metrics of EHR usage.

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Conflict of interest statement

Conflict of Interest Disclosures: Dr Sexton reported receiving grant funding from the National Institutes of Health to conduct research on health care worker well-being metrics and interventions outside the submitted work. Dr Adair reported receiving grant funding from the National Institutes of Health and occasionally give talks or workshops on the topic of healthcare worker burnout to hospitals or hospital associations outside the submitted work. No other disclosures were reported.

Figures

Figure 1.
Figure 1.. Cohort Development Flow Diagram
Figure 2.
Figure 2.. Graphical Data Visualizations of Time EHR Metrics and Interaction of Sex in Full Model
See this image and copyright information in PMC

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