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

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.

Department

Description

Provenance

Subjects

Citation

Published Version (Please cite this version)

10.1001/jamanetworkopen.2021.5686

Publication Info

McPeek-Hinz, Eugenia, Mina Boazak, J Bryan Sexton, Kathryn C Adair, Vivian West, Benjamin A Goldstein, Robert S Alphin, Sherif Idris, et al. (2021). Clinician Burnout Associated With Sex, Clinician Type, Work Culture, and Use of Electronic Health Records. JAMA network open, 4(4). p. e215686. 10.1001/jamanetworkopen.2021.5686 Retrieved from https://hdl.handle.net/10161/23676.

This is constructed from limited available data and may be imprecise. To cite this article, please review & use the official citation provided by the journal.

Scholars@Duke

Sexton

John Bryan Sexton

Associate Professor in Psychiatry and Behavioral Sciences

Bryan is the Director of the Duke Center for the Advancement of Well-being Science.  He leads the efforts around research, training and coaching, guiding quality improvement and well-being activities.  

 

A psychologist member of the Department of Psychiatry, Bryan is a psychometrician and spends time developing methods of assessing and improving safety culture, teamwork, leadership and especially work-force well-being.  Currently, he is disseminating the results from a successful NIH R01 grant that used RCTs to show that we can cause enduring improvements in healthcare worker well-being. 

 

A perpetually recovering father of four, he enjoys running, using hand tools on wood, books on Audible, and hearing particularly good explanations of extremely complicated topics.

Goldstein

Benjamin Alan Goldstein

Professor of Biostatistics & Bioinformatics

I study the meaningful use of Electronic Health Records data. My research interests sit at the intersection of biostatistics, biomedical informatics, machine learning and epidemiology. I collaborate with researchers both locally at Duke as well as nationally. I am interested in speaking with any students, methodologistis or collaborators interested in EHR data.

Please find more information at: https://sites.duke.edu/bgoldstein/

Hammond

William Edward Hammond

Professor in Family Medicine and Community Health

Main areas of interest include computer-based medical records, hospital information systems, national and international standards, artificial intelligence, networking and computerization in ambulatory care.

Bae

Jonathan Gregory Bae

Associate Professor of Medicine

Patient safety and quality improvement, hospital based performance improvement, care transitions and hospital readmissions, general internal medicine hospital care, resident and medical student education.


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