Cited by 68Electronic Health Records SystemsHospital Admissions and OutcomesMedical Coding and Health Information

Documenting or operating: where is time spent in general surgery residency?

Open access
Cox, Morgan L., Farjat, Alfredo E., Risoli, TJ, Peskoe, Sarah, Goldstein, Benjamin A., Turner, David A., Migaly, John·2018·Journal of Surgical Education

Abstract

Objective The utilization of electronic health records (EHR) has become essential in the daily activities of physicians for documentation and as an information source. However, the amount of time spent by residents utilizing the EHR has not been thoroughly evaluated, particularly within surgical specialties. This study aims to analyze EHR usage by general surgery residents and to assess the association between this use and case volume at a single academic institution.Design For general surgery residents in clinical years (CY) 1-5, de-identified login and logout time data between September 2016 and June 2017 were retrospectively extracted from the Epic EHR (Verona, WI). A binary time series was created for each resident to indicate and track over time whether he or she was utilizing the EHR system. Comparisons between categorical variables were performed with Fisher's exact test. Continuous variables were compared using Wilcoxon rank sum test. Longitudinal linear mixed-effects models were used to assess the EHR usage among the surgery residents. The association between EHR time and the number of operative cases logged was evaluated with Pearson's correlation coefficient.Setting This study was performed by the Department of Surgery in conjunction with the Office of Graduate Medical Education at Duke University Health System.Participants All active general surgery residents during the 2016-2017 academic year.Results Thirty-six general surgery residents (28 males, 8 females) spent a median of 2.4 hours per day and 23.7 hours per week using the EHR. CY2 had the highest median usage per week (28.9 hours), while CY3 had the lowest (16.7 hours) but no significant difference based on EHR usage was found among the analyzed CYs (p = 0.164). Residents spent significantly more time logged into the EHR during the week compared to weekends and during the day compared to nights (all p < 0.001). For the residency program as a whole, a median of 151.5 total work hours per day was dedicated to documentation. On average, interns on dedicated night rotations spent 7% of their login time outside regularly scheduled duty hours while interns on dedicated day rotations spent 27%. There was no overall correlation between monthly case logs and EHR usage (r = 0.06, p = 0.30); however, CY2 had a significant negative correlation (r = -0.2, p = 0.038).Conclusions In the era of a maximum 80-hour work week, general surgery residents spend a substantial portion, at least 30%, of their time utilizing the EHR. One third of EHR usage by interns occurred outside the scheduled 12-hour shift, demonstrating the difficulties of completing paperwork as part of the scheduled work day. Additionally, the lack of correlation to case logs is likely due to an underestimation of the documentation burden associated with operating, which includes preparatory effort and operative notes. Ultimately, these quantitative EHR usage results will be correlated to burnout prior to implementing programs to improve efficiency and decrease the burden of charting.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1016/j.jsurg.2018.10.010

Cites

27 of 27 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Authors
Cox, M. L., Farjat, A. E., Risoli, T., Peskoe, S., Goldstein, B. A., Turner, D. A., & Migaly, J.
Affiliations
  • Duke University (US)
  • Duke University Health System (US)
Corresponding author
Cox, Morgan L.
Venue
Journal of Surgical Education
Publisher
Elsevier BV
Published
2018-11
Volume
75
Issue
6
Pages
e97-e106
ISSN
  • 1878-7452 (ISSN-L)
  • 1931-7204
OpenAlex
W2902726648
Cited by
68
References
27
Citations by year
2026: 7 · 2025: 6 · 2024: 9 · 2023: 8 · 2022: 12 · 2021: 13 · 2020: 9 · 2019: 4
FWCI
8.20
Type
journal article
Language
en
Open access
Locations
  • Journal of surgical education (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
Funders
National Institutes of Health (T32HL069749)
Topics
  • Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
  • Health Sciences › Medicine › Emergency Medicine › Hospital Admissions and Outcomes
  • Health Sciences › Health Professions › Health Information Management › Medical Coding and Health Information
Keywords
electronic health records, general surgery residents, clinical documentation, operative case volume, resident work hours, graduate medical education, Epic EHR, documentation burden
MeSH terms
Documentation, Internship and Residency, Personnel Staffing and Scheduling, Retrospective Studies, General Surgery, Surgical Procedures, Operative, Time Factors, Electronic Health Records

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review