Association of Electronic Health Record Inbasket Message Characteristics With Physician Burnout

Author:

Baxter Sally L.12,Saseendrakumar Bharanidharan Radha1,Cheung Michael3,Savides Thomas J.2,Longhurst Christopher A.24,Sinsky Christine A.5,Millen Marlene2,Tai-Seale Ming23

Affiliation:

1. Division of Ophthalmology Informatics and Data Science, Viterbi Family Department of Ophthalmology and Shiley Eye Institute, University of California, San Diego, La Jolla

2. Department of Medicine, University of California, San Diego, La Jolla

3. Department of Family Medicine, University of California, San Diego, La Jolla

4. Department of Pediatrics, University of California, San Diego, La Jolla

5. American Medical Association, Chicago, Illinois

Abstract

ImportancePhysician burnout is an ongoing epidemic; electronic health record (EHR) use has been associated with burnout, and the burden of EHR inbasket messages has grown in the context of the COVID-19 pandemic. Understanding how EHR inbasket messages are associated with physician burnout may uncover new insights for intervention strategies.ObjectiveTo evaluate associations between EHR inbasket message characteristics and physician burnout.Design, Setting, and ParticipantsCross-sectional study in a single academic medical center involving physicians from multiple specialties. Data collection took place April to September 2020, and data were analyzed September to December 2020.ExposuresPhysicians responded to a survey including the validated Mini-Z 5-point burnout scale.Main Outcomes and MeasuresPhysician burnout according to the self-reported burnout scale. A sentiment analysis model was used to calculate sentiment scores for EHR inbasket messages extracted for participating physicians. Multivariable modeling was used to model risk of physician burnout using factors such as message characteristics, physician demographics, and clinical practice characteristics.ResultsOf 609 physicians who responded to the survey, 297 (48.8%) were women, 343 (56.3%) were White, 391 (64.2%) practiced in outpatient settings, and 428 (70.28%) had been in medical practice for 15 years or less. Half (307 [50.4%]) reported burnout (score of 3 or higher). A total of 1 453 245 inbasket messages were extracted, of which 630 828 (43.4%) were patient messages. Among negative messages, common words included medical conditions, expletives and/or profanity, and words related to violence. There were no significant associations between message characteristics (including sentiment scores) and burnout. Odds of burnout were significantly higher among Hispanic/Latino physicians (odds ratio [OR], 3.44; 95% CI, 1.18-10.61; P = .03) and women (OR, 1.60; 95% CI, 1.13-2.27; P = .01), and significantly lower among physicians in clinical practice for more than 15 years (OR, 0.46; 95% CI, 0.30-0.68; P < .001).Conclusions and RelevanceIn this cross-sectional study, message characteristics were not associated with physician burnout, but the presence of expletives and violent words represents an opportunity for improving patient engagement, EHR portal design, or filters. Natural language processing represents a novel approach to understanding potential associations between EHR inbasket messages and physician burnout and may also help inform quality improvement initiatives aimed at improving patient experience.

Publisher

American Medical Association (AMA)

Subject

General Medicine

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