Identifying Electronic Health Record Contributions to Diagnostic Error in Ambulatory Settings Through Legal Claims Analysis
Open accessAbstract
This qualitative study analyzes closed legal claims data to determine whether problems with electronic health records are associated with diagnostic errors, in which part of the diagnostic process errors occur, and the specific types of errors that occur.
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EHRs potentially contribute to over 60% of diagnostic errors in ambulatory settings.
“However, EHRs potentially contribute to over 60% of diagnostic errors in ambulatory settings [165].”
From Toward Safer Diagnoses: A SEIPS-Based Narrative Review of Diagnostic Errors (2026) · cites this paper as [165]
The Results report 122 ambulatory legal claims in which an EHR was a potential contributor to diagnostic error. They do not establish that EHRs contribute to over 60% of ambulatory diagnostic errors; the Methods describe a selected set of claims already coded with diagnosis-related and EHR-related factors, not all ambulatory diagnostic errors. (LLM, conf=0.85)
Experimental — accuracy not yet measuredSignificant issues such as incomplete data during data migration, missing information in EHRs, and insufficient functionality lead to diagnostic errors.
“Significant issues such as incomplete data during data migration, missing information in EHRs, and insufficient functionality lead to diagnostic errors.”
From Toward Safer Diagnoses: A SEIPS-Based Narrative Review of Diagnostic Errors (2026) · cites this paper as [165]
The Discussion (page not provided) says EHR design and use issues have the potential to facilitate diagnostic errors, and the Results describe claims in which an EHR was a potential contributor. The copy does not identify incomplete data during migration, missing EHR information, or insufficient functionality as the specific issues responsible; the claim also states causation more firmly than the paper does. (LLM, conf=0.85)
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References 4 · Cited by 13
Research works printed but not linked: 3
- [2]Apathy NC, Howe JL, Krevat SA,. Electronic health record legal settlements in the US since the 2009 Health Information Technology for Economic and Clinical Health Act. JAMA Health Forum. 2022; 3(11): e223872. doi: 10.1001/jamahealthforum.2022.3872 36367740 PMC9652746 · DOI
- [3]Pacheco TB, Hettinger AZ, Ratwani RM. Identifying potential patient safety issues from the federal electronic health record surveillance program. JAMA. 2019; 322(23): 2339- 2340. doi: 10.1001/jama.2019.17242 31846009 PMC6990822 · DOI
- [4]Schiff GD, Hasan O, Kim S,. Diagnostic error in medicine: analysis of 583 physician-reported errors. Arch Intern Med. 2009; 169(20): 1881- 1887. doi: 10.1001/archinternmed.2009.333 19901140 · DOI · Paper page
- Authors
- Krevat, S. A., Samuel, S., Boxley, C., Mohan, V., Siegal, D., Gold, J. A., & Ratwani, R. M.
- Affiliations
- MedStar Health (US)
- Oregon Health & Science University (US)
- Controlled Risk Insurance Company (United States) (US)
- Corresponding author
- Gold, Jeffrey A.
- ORCID
- Venue
- JAMA Network Open
- Publisher
- American Medical Association (AMA)
- Published
- 2023-04-14
- Volume
- 6
- Issue
- 4
- Pages
- e238399
- ISSN
- 2574-3805 (ISSN-L)
- PMC
- PMC10105306
- OpenAlex
- W4365479347
- Cited by
- 13
- References
- 4
- Citations by year
- 2026: 7 · 2025: 5 · 2024: 1
- FWCI
- 2.92
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- JAMA Network Open (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Funders
- Agency for Healthcare Research and Quality (R18 HS027119)
- U.S. National Library of Medicine (T15LM007088)
- Topics
- Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
- Health Sciences › Health Professions › Pharmacy › Medical Malpractice and Liability Issues
- Health Sciences › Health Professions › Health Information Management › Medical Coding and Health Information
- Keywords
- electronic health records, diagnostic errors, outpatient care, malpractice claims, diagnostic process, medical record errors
- MeSH terms
- Ambulatory Care, Diagnostic Errors, Humans, Insurance Claim Review, 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.
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