Cited by 74Electronic Health Records SystemsMedical Coding and Health InformationNursing Diagnosis and Documentation

Prevalence and Sources of Duplicate Information in the Electronic Medical Record

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Steinkamp, Jackson, Kantrowitz, Jacob J., Airan-Javia, Subha·2022·JAMA Network Open

Abstract

Importance: Duplicated text is a well-documented hazard in electronic medical records (EMRs), leading to wasted clinician time, medical error, and burnout. This study hypothesizes that text duplication is prevalent and increases with time and EMR size and that duplicate information is shared across authors. Objective: To examine the prevalence and scope of duplication behavior in clinical notes from a large academic health system and the factors associated with duplication. Design, Setting, and Participants: This retrospective, cross-sectional analysis of note length and content duplication rates used a set of 10 adjacent word tokens (ie, a 10-gram) sliding-window approach to identify spans of text duplicated exactly from earlier notes in a patient’s record for all inpatient and outpatient notes written within the University of Pennsylvania Health System from January 1, 2015, through December 31, 2020. Text duplicated from a different author vs text duplicated from the same author was quantified. Furthermore, novel text and duplicated text per author for various note types and author types, as well as per patient record by number of notes in the record, were quantified. Information scatter, another documentation hazard, was defined as the inverse of novel text per note, and the association between information duplication and information scatter was graphed. Data analysis was performed from January to March 2022. Main Outcomes and Measures: Total, novel, and duplicate text by note type and note author were determined, as were the mean intra-author and inter-author duplication per note by type and author. Results: There were a total of 104 456 653 notes for 1 960 689 unique patients consisting of 32 991 489 889 words; 50.1% of the total text in the record (16 523 851 210 words) was duplicated from prior text written about the same patient. The duplication fraction increased year-over-year, from 33.0% for notes written in 2015 to 54.2% for notes written in 2020. Of the text duplicated, 54.1% came from text written by the same author, whereas 45.9% was duplicated from a different author. Records with more notes had more total duplicate text, approaching 60%. Note types with high information scatter tended to have low information overload, and vice versa, suggesting a trade-off between these 2 hazards under the current documentation paradigm. Conclusions and Relevance: Duplicate text casts doubt on the veracity of all information in the medical record, making it difficult to find and verify information in day-to-day clinical work. The findings of this cross-sectional study suggest that text duplication is a systemic hazard, requiring systemic interventions to fix, and simple solutions such as banning copy-paste may have unintended consequences, such as worsening information scatter. The note paradigm should be further examined as a major cause of duplication and scatter, and alternative paradigms should be evaluated.

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Authors
Steinkamp, J., Kantrowitz, J. J., & Airan-Javia, S.
Affiliations
  • University of Pennsylvania (US)
  • River Records, LLC, Jamaica Plain, Massachusetts
  • Department of Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia
Corresponding author
Kantrowitz, Jacob J.
Venue
JAMA Network Open
Published
2022-09-26
Volume
5
Issue
9
Pages
e2233348
ISSN
2574-3805 (ISSN-L)
OpenAlex
W4297242650
Cited by
74
References
3
Citations by year
2026: 14 · 2025: 23 · 2024: 26 · 2023: 10 · 2022: 1
FWCI
11.22
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • JAMA Network Open (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
Topics
  • Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
  • Health Sciences › Health Professions › Health Information Management › Medical Coding and Health Information
  • Health Sciences › Nursing › Issues, ethics and legal aspects › Nursing Diagnosis and Documentation
Keywords
electronic health records, information overload, medical errors, clinician burnout, academic health system
MeSH terms
Cross-Sectional Studies, Documentation, Humans, Retrospective Studies, Prevalence, Electronic Health Records

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