ArticleJournal of the American Medical Informatics Association : JAMIA2021
Validation of an electronic trigger to measure missed diagnosis of stroke in emergency departments.
Article in Journal of the American Medical Informatics Association : JAMIA, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04166240 (Measuring and Improving the Safety of Test Result Follow-Up), which is not on this map. Cited by 8 papers, 1 of them a synthesis that pooled it.
What it found
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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.
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.
Measuring and Improving the Safety of Test Result Follow-Up
Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it, 14 citations in OpenAlex.
- Dizziness in the emergency department and risk of stroke: A systematic review and meta-analysis.PloS one · 2026Pooled it
- Classification of Emergency Diagnosis-Sensitive Conditions Among Medicare Beneficiaries.JAMA network open · 2026Article
- Epidemiology of diagnostic errors in pediatric emergency departments using electronic triggers.Academic emergency medicine : official journal of the Society for Academic Emergency Medicine · 2025Article
- Implementation of Electronic Triggers to Identify Diagnostic Errors in Emergency Departments.JAMA internal medicine · 2025Article
- Machine Learning to Enhance Electronic Detection of Diagnostic Errors.JAMA network open · 2024Article
- Identifying stigmatizing language in clinical documentation: A scoping review of emerging literature.PloS one · 2024Article
- Article
- Inviting patients to identify diagnostic concerns through structured evaluation of their online visit notes.Journal of the American Medical Informatics Association : JAMIA · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 2 institutions in 1 country.
Funding
Abstract
objectiveDiagnostic errors are major contributors to preventable patient harm. We validated the use of an electronic health record (EHR)-based trigger (e-trigger) to measure missed opportunities in stroke diagnosis in emergency departments (EDs).
methodsUsing two frameworks, the Safer Dx Trigger Tools Framework and the Symptom-disease Pair Analysis of Diagnostic Error Framework, we applied a symptom-disease pair-based e-trigger to identify patients hospitalized for stroke who, in the preceding 30 days, were discharged from the ED with benign headache or dizziness diagnoses. The algorithm was applied to Veteran Affairs National Corporate Data Warehouse on patients seen between 1/1/2016 and 12/31/2017. Trained reviewers evaluated medical records for presence/absence of missed opportunities in stroke diagnosis and stroke-related red-flags, risk factors, neurological examination, and clinical interventions. Reviewers also estimated quality of clinical documentation at the index ED visit.
resultsWe applied the e-trigger to 7,752,326 unique patients and identified 46,931 stroke-related admissions, of which 398 records were flagged as trigger-positive and reviewed. Of these, 124 had missed opportunities (positive predictive value for "missed" = 31.2%), 93 (23.4%) had no missed opportunity (non-missed), 162 (40.7%) were miscoded, and 19 (4.7%) were inconclusive. Reviewer agreement was high (87.3%, Cohen's kappa = 0.81). Compared to the non-missed group, the missed group had more stroke risk factors (mean 3.2 vs 2.6), red flags (mean 0.5 vs 0.2), and a higher rate of inadequate documentation (66.9% vs 28.0%).
conclusionIn a large national EHR repository, a symptom-disease pair-based e-trigger identified missed diagnoses of stroke with a modest positive predictive value, underscoring the need for chart review validation procedures to identify diagnostic errors in large data sets.
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Registered trials
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