Automated Retrospective Calculation of the EDACS and HEART Scores in a Multicenter Prospective Cohort of Emergency Department Chest Pain Patients
- PMID: 32596953
- DOI: 10.1111/acem.14068
Automated Retrospective Calculation of the EDACS and HEART Scores in a Multicenter Prospective Cohort of Emergency Department Chest Pain Patients
Abstract
Objectives: Coronary risk scores are commonly applied to emergency department patients with undifferentiated chest pain. Two prominent risk score-based protocols are the Emergency Department Assessment of Chest pain Score Accelerated Diagnostic Protocol (EDACS-ADP) and the History, ECG, Age, Risk factors, and Troponin (HEART) pathway. Since prospective documentation of these risk determinations can be challenging to obtain, quality improvement projects could benefit from automated retrospective risk score classification methodologies.
Methods: EDACS-ADP and HEART pathway data elements were prospectively collected using a Web-based electronic clinical decision support (eCDS) tool over a 24-month period (2018-2019) among patients presenting with chest pain to 13 EDs within an integrated health system. Data elements were also extracted and processed electronically (retrospectively) from the electronic health record (EHR) for the same patients. The primary outcome was agreement between the prospective/eCDS and retrospective/EHR data sets on dichotomous risk protocol classification, as assessed by kappa statistics (ĸ).
Results: There were 12,110 eligible eCDS uses during the study period, of which 66 and 47% were low-risk encounters by EDACS-ADP and HEART pathway, respectively. Agreement on low-risk status was acceptable for EDACS-ADP (ĸ = 0.73, 95% confidence interval [CI] = 0.72 to 0.75) and HEART pathway (ĸ = 0.69, 95% CI = 0.68 to 0.70) and for the continuous scores (interclass correlation coefficients = 0.87 and 0.84 for EDACS and HEART, respectively).
Conclusions: Automated retrospective determination of low risk status by either the EDACS-ADP or the HEART pathway provides acceptable agreement compared to prospective score calculations, providing a feasible risk adjustment option for use in large data set analyses.
© 2020 by the Society for Academic Emergency Medicine.
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