Evidence map›Paper›PMID 39042410›Full record

ArticleJAMA network open2024

Gender Differences in Electronic Health Record Usage Among Surgeons.

Karen Malacon, Gavin Touponse, Ezra Yoseph, Guan Li, Pingho Janet Wei, Kimberly Kicielinski, Lara Massie, Theresa Williamson, Summer Han, Corinna Zygourakis

Abstract read
In one paragraph

Article in JAMA network open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
–field-weighted citation impact
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

13 citing papers in PubMed.

  1. Article
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  8. Administrative burden in primary care: Critical review.Canadian family physician Medecin de famille canadien · 2025
    Review
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

Karen MalaconDepartment of Neurosurgery, Stanford University Medical Center, Stanford, California.
Gavin TouponseDepartment of Neurosurgery, Stanford University Medical Center, Stanford, California.
Ezra YosephDepartment of Neurosurgery, Stanford University Medical Center, Stanford, California.
Guan LiDepartment of Neurosurgery, Stanford University Medical Center, Stanford, California.
Pingho Janet WeiStanford Health Care, Stanford, California.
Kimberly KicielinskiDepartment of Neurosurgery, Medical University of South Carolina, Charleston.
Lara MassieDepartment of Neurosurgery, Allegheny Health Network, Monroeville, Pennsylvania.
Theresa WilliamsonDepartment of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston.
Summer HanDepartment of Neurosurgery, Stanford University Medical Center, Stanford, California.
Corinna ZygourakisDepartment of Neurosurgery, Stanford University Medical Center, Stanford, California.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Importance: Understanding gender differences in electronic health record (EHR) use among surgeons is crucial for addressing potential disparities in workload, compensation, and physician well-being. Objective: To investigate gender differences in EHR usage patterns. Design, Setting, and Participants: This cross-sectional study examined data from an EHR system (Epic Signal) at a single academic hospital from January to December 2022. Participants included 224 attending surgeons with patient encounters in the outpatient setting. Statistical analysis was performed from May 2023 to April 2024. Exposures: Surgeon's gender. Main Outcomes and Measures: The primary outcome variables were progress note length, documentation length, time spent in medical records, and time spent documenting patient encounters. Continuous variables were summarized with median and IQR and assessed via the Kruskal-Wallis test. Categorical variables were summarized using proportion and frequency and compared using the χ2 test. Multivariate linear regression was used with primary EHR usage variables as dependent variables and surgeon characteristics as independent variables. Results: This study included 222 529 patient encounters by 224 attending surgeons, of whom 68 (30%) were female and 156 (70%) were male. The median (IQR) time in practice was 14.0 (7.8-24.3) years. Male surgeons had more median (IQR) appointments per month (78.3 [39.2-130.6] vs 57.8 [25.7-89.8]; P = .005) and completed more medical records per month compared with female surgeons (43.0 [21.8-103.9] vs 29.1 [15.9-48.1]; P = .006). While there was no difference in median (IQR) time spent in the EHR system per month (664.1 [301.0-1299.1] vs 635.0 [315.6-1192.0] minutes; P = .89), female surgeons spent more time logged into the system both outside of 7am to 7pm (36.4 [7.8-67.6] vs 14.1 [5.4-52.2] min/mo; P = .05) and outside of scheduled clinic hours (134.8 [58.9-310.1] vs 105.2 [40.8-214.3] min/mo; P = .05). Female surgeons spent more median (IQR) time per note (4.8 [2.6-7.1] vs 2.5 [0.9-4.2] minutes; P < .001) compared with male surgeons. Male surgeons had a higher number of median (IQR) days logged in per month (17.7 [13.8-21.3] vs 15.7 [10.7-19.7] days; P = .03). Female surgeons wrote longer median (IQR) inpatient progress notes (6025.1 [3692.1-7786.7] vs 4307.7 [2808.9-5868.4] characters/note; P = .001) and had increased outpatient document length (6321.1 [4079.9-7825.0] vs 4445.3 [2934.7-6176.7] characters/note; P < .001). Additionally, female surgeons wrote a higher fraction of the notes manually (17% vs 12%; P = .006). After using multivariable linear regression models, male gender was associated with reduced character length for both documentations (regression coefficient, -1106.9 [95% CI, -1981.5 to -232.3]; P = .01) and progress notes (regression coefficient, -1119.0 [95% CI, -1974.1 to -263.9]; P = .01). Male gender was positively associated with total hospital medical records completed (regression coefficient, 47.3 [95% CI, 28.3-66.3]; P < .001). There was no difference associated with gender for time spent in each note, time spent outside of 7 am to 7 pm, or time spent outside scheduled clinic hours. Conclusions and Relevance: This cross-sectional study of EHR data found that female surgeons spent more time documenting patient encounters, wrote longer notes, and spent more time in the EHR system compared with male surgeons. These findings have important implications for understanding the differential burdens faced by female surgeons, including potential contributions to burnout and payment disparities.

Indexed as

Electronic Health RecordsSurgeonsAdultCross-Sectional StudiesFemaleHumansMaleMiddle AgedSex FactorsWorkload

Identifiers

PMID39042410
PMCPMC11267410

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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.