Validation of an Electronic Trigger to Measure Missed Diagnosis of Stroke in Emergency Departments

Authors

Viralkumar Vaghani
Li Wei
Umair Mushtaq
Dean F Sittig
Andrea Bradford
Hardeep Singh

Publication Date

9-18-2021

Journal

Journal of the American Medical Informatics Association

DOI

10.1093/jamia/ocab121

PMID

34279630

PMCID

PMC8449630

PubMedCentral® Posted Date

7-19-2021

PubMedCentral® Full Text Version

Post-Print

Published Open-Access

yes

Keywords

Diagnostic Errors, Electronic Health Records, Electronics, Emergency Service, Hospital, Humans, Missed Diagnosis, Retrospective Studies, Stroke, diagnostic errors; health care quality improvement; health services research; patient safety, stroke

Abstract

OBJECTIVE: Diagnostic 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).

METHODS: Using 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.

RESULTS: We 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%).

CONCLUSION: In 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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