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Evaluating Acute Stroke Diagnosis Using Simulation Scenarios - 09/04/25

Doi : 10.1016/j.annemergmed.2025.03.004 
Ava L. Liberman, MD a, Daniel Apley, PhD b, Jingyu Zhu, PhD b, Elida Romo, BS c, Jane L. Holl, MD, MPH c, Rebeca Khorzad, MEM d, Matthew Maas, MD, MS e, Scott J. Mendelson, MD, PhD f, Christopher T. Richards, MD, MS g, Sarah Song, MD, MPH h, Shyam Prabhakaran, MD, MS c,
a Department of Neurology, Clinical and Translational Neuroscience Unit, Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY 
b Department of Industrial Engineering & Management Sciences, Northwestern University, Chicago, IL 
c Department of Neurology, University of Chicago, Chicago, IL 
d Arvin LLC, Healthcare Quality Improvement, Lake Forest, IL 
e Department of Neurology, Department of, Northwestern University, Chicago, IL 
f Access TeleCare, Dallas, TX 
g Department of Emergency Medicine, University of Cincinnati, Cincinnati, OH 
h Department of Neurology, Rush University, Chicago, IL 

Corresponding author.
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Abstract

Study objective

This study sought to explore the clinical and process factors that, alone or in combination, influence the accuracy of stroke diagnosis in the emergency department (ED) by applying a novel design of experiments methodology.

Methods

We used design of experiments, a branch of applied statistics, to create a screening experiment comprised of patient simulation scenarios in which purposeful changes are made to prespecified factors thought to potentially influence the outcome of interest. We used 4 base case scenarios (typical and atypical acute ischemic stroke, intracerebral hemorrhage, and complex migraine [a stroke mimic]) and 12 prespecified clinical factors thought to influence stroke diagnosis (eg, patient age, history of seizure, and interruption occurring during patient assessment that the physician must attend to [distraction]) based on literature review and expert opinion. Experimental runs were designed using a modified fractional factorial design approach. Physicians, including postgraduate trainees from 3 health systems, were invited to participate. After each run, participants were asked to provide a diagnosis and their confidence in that diagnosis; both inperson and virtual assessments were conducted. We used multivariate regression to explore factor(s) influencing physician confidence in stroke diagnosis. Confidence was signed, with positive confidence corresponding to a stroke diagnosis and negative confidence to a nonstroke diagnosis, allowing confidence levels from the regression model to be translated to misdiagnosis.

Results

A total of 27 physicians (12 neurology and 15 emergency medicine) completed 100 experimental runs. The typical ischemic stroke base case presentation was accurately diagnosed in every run, whereas the other 3 base cases were less accurately diagnosed. Stroke overdiagnosis occurred in the complex migraine case (83% false positive) and stroke underdiagnosis in the intracerebral hemorrhage case (36% false negative). Distraction during patient evaluation and the availability of a witness from whom relevant information could be obtained exhibited significant, independent effects on diagnostic confidence. Distractions of the physician had an even stronger influence on stroke diagnostic confidence when no witness was present.

Conclusions

Applying the design of experiments methods to simulated scenarios, we found that distraction and presence of a witness significantly influenced diagnostic confidence and thus, stroke diagnostic accuracy. These findings should inform future studies to understand the underlying mechanisms of ED misdiagnosis and in the design of future interventions to improve stroke diagnostic formulation.

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Keywords : Diagnostic Error, Stroke, Emergency Medicine, Patient Safety, Design of Experiments, Simulation


Plan


 Please see page XX for the Editor’s Capsule Summary of this article.
 Supervising editor: William J. Meurer, MD, MS. Specific detailed information about possible conflicts of interest for individual editors is available at editors .
 Author contributions: ALL analyzed the data and wrote the manuscript. DA and JZ helped design the study, analyzed the data, and reviewed the manuscript. JLH and RK conceived and helped design the study, collected data, and reviewed the manuscript. MM, SJM, CTR, and SS helped design the study and reviewed the manuscript. SP takes responsibility for the paper as a whole.
 Data sharing statement: Anonymized data not published within this article will be made available by request from any qualified investigator.
  All authors attest to meeting the four ICMJE.org authorship criteria: (1) Substantial contributions to the conception or design of the work; or the acquisition, analysis, or interpretation of data for the work; AND (2) Drafting the work or revising it critically for important intellectual content; AND (3) Final approval of the version to be published; AND (4) Agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.
 Funding and support: By Annals ’ policy, all authors are required to disclose any and all commercial, financial, and other relationships in any way related to the subject of this article as per ICMJE conflict of interest guidelines (see www.icmje.org ). Drs. Holl and Prabhakaran are supported by R18 HS025359, R18 HS027264, and U01 NS131797. Dr. Prabhakaran is also supported by U24 NS107233. The other authors have stated that no such relationships exist.


© 2025  American College of Emergency Physicians. Publié par Elsevier Masson SAS. Tous droits réservés.
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