Key result
Model-augmented screening yields ~20-point higher sensitivity for acute coronary syndrome than routine practice.
Why the study?
Does model-augmented human screening improve sensitivity and equity for detecting acute coronary syndrome in emergency department patients?
Cohort (n=279,132)
No
Does model-augmented human screening improve sensitivity and equity for detecting acute coronary syndrome in emergency department patients?
Combining predictive models with human clinical practice significantly improves the sensitivity and demographic equity of emergency department screening for acute coronary syndrome.
Model-augmented screening may raise ED ACS detection sensitivity; hypothesis-generating for equity gains and requires prospective validation.
We compared four methods to screen emergency department (ED) patients for an early electrocardiogram (ECG) to diagnose ST-elevation myocardial infarction (STEMI) in a 5-year retrospective cohort through observed practice, objective application of screening protocol criteria, a predictive model, and a model augmenting human practice. We measured screening performance by sensitivity, missed acute coronary syndrome (ACS) and STEMI, and the number of ECGs required. Our cohort of 279,132 ED visits included 1397 patients who had a diagnosis of ACS. We found that screening by observed practice augmented with the model delivered the highest sensitivity for detecting ACS (92.9%, 95%CI: 91.4-94.2%) and showed little variation across sex, race, ethnicity, language, and age, demonstrating equity. Although it missed a few cases of ACS (7.6%) and STEMI (4.4%), it did require ECGs on an additional 11.1% of patients compared to current practice. Screening by protocol performed the worst, underdiagnosing young, Black, Native American, Alaskan or Hawaiian/Pacific Islander, and Hispanic patients. Thus, adding a predictive model to augment human practice improved the detection of ACS and STEMI and did so most equitably across the groups. Hence, combining human and model screening--rather than relying on either alone--may maximize ACS screening performance and equity.
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Bunney et al. (2023) conducted a cohort in Acute Coronary Syndrome (n=279,132). Model-augmented human screening vs. Observed human practice was evaluated on Sensitivity for detecting acute coronary syndrome (95% CI 91.4-94.2). Model-augmented human screening achieved the highest sensitivity for detecting acute coronary syndrome (92.9%) compared to observed practice (73%), while requiring ECGs for an additional 11.1% of patients.
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