Evidence map›Paper›PMID 32016375›Full record

ArticleJournal of the American Medical Informatics Association : JAMIA2020

Electronic health records and burnout: Time spent on the electronic health record after hours and message volume associated with exhaustion but not with cynicism among primary care clinicians.

Julia Adler-Milstein, Wendi Zhao, Rachel Willard-Grace, Margae Knox, Kevin Grumbach

Open access · bronzeAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of the American Medical Informatics Association : JAMIA, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 197 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
197citing papers in PubMed, 4 pooled it
40.1field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

197 citing papers in PubMed, 4 syntheses or guidelines pooled it, 329 citations in OpenAlex.

  1. Pooled it
  2. Measuring Documentation Burden in Healthcare.Journal of general internal medicine · 2024
    Pooled it
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  4. Exploring the relationship between electronic health records and provider burnout: A systematic review.Journal of the American Medical Informatics Association : JAMIA · 2021
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137 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 1 institution in 1 country.

Julia Adler-MilsteinCenter for Clinical Informatics and Improvement Research, University of California, San Francisco, San Francisco, California, USA.
Wendi ZhaoCenter for Clinical Informatics and Improvement Research, University of California, San Francisco, San Francisco, California, USA.
Rachel Willard-GraceDepartment of Family and Community Medicine, University of California, San Francisco, San Francisco, California, USA.
Margae KnoxDepartment of Family and Community Medicine, University of California, San Francisco, San Francisco, California, USA.
Kevin GrumbachDepartment of Family and Community Medicine, University of California, San Francisco, San Francisco, California, USA.
University of California, San Francisco · US

Funding

UC Berkeley-UCSF Health Services Research Training ProgramT32HS022241 · AHRQ · UNIVERSITY OF CALIFORNIA BERKELEY · PI RODRIGUEZ, HECTOR P. · 2013 to 2024
$3.2M
AHRQ HHS T32 HS022241
6 · The paper itself

Abstract

objectivesThe study sought to determine whether objective measures of electronic health record (EHR) use-related to time, volume of work, and proficiency-are associated with either or both components of clinician burnout: exhaustion and cynicism. MATERIALS AND

methodsWe combined Maslach Burnout Inventory survey measures (94% response rate; 122 of 130 clinicians) with objective, vendor-defined EHR use measures from log files (time after hours on clinic days; time on nonclinic days; message volume; composite measures of efficiency and proficiency). Data were collected in early 2018 from all primary care clinics of a large, urban, academic medical center. Multivariate regression models measured the association between each burnout component and each EHR use measure.

resultsOne-third (34%) of clinicians had high cynicism and 51% had high emotional exhaustion. Clinicians in the top 2 quartiles of EHR time after hours on scheduled clinic days (those above the sample median of 68 minutes per clinical full-time equivalent per week) had 4.78 (95% confidence interval [CI], 1.1-20.1; P = .04) and 12.52 (95% CI, 2.6-61; P = .002) greater odds of high exhaustion. Clinicians in the top quartile of message volume (>307 messages per clinical full-time equivalent per week) had 6.17 greater odds of high exhaustion (95% CI, 1.1-41; P = .04). No measures were associated with high cynicism. DISCUSSION: EHRs have been cited as a contributor to clinician burnout, and self-reported data suggest a relationship between EHR use and burnout. As organizations increasingly rely on objective, vendor-defined EHR measures to design and evaluate interventions to reduce burnout, our findings point to the measures that should be targeted.

conclusionsTwo specific EHR use measures were associated with exhaustion.

Indexed as

Academic Medical CentersAttitude of Health PersonnelBurnout, ProfessionalElectronic Health RecordsFatigueFemaleHumansMalePhysicians, Primary CareSan FranciscoSurveys and QuestionnairesWorkloadclinician burnoutEHR optimizationEHR use

Identifiers

PMID32016375
PMCPMC7647261
OpenAlexW3005890082

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.