Development of a Computerized, Evidence-Based Decision Support System for Computed Tomography Assessment in Acute Aortic Syndrome in the Emergency Department

Abstract

Purpose: To develop a computerized algorithm, or Clinical Decision Support System (CDSS), for managing and requesting imaging in the emergency department, specifically Computerized Tomography Angiography (CTA) of the aorta, when there is suspicion of AAS, and to determine the effect of implementing this system. To determine the factors associated with a positive radiological diagnosis that improve the predictive capacity of CTA findings. Methods: After developing and implementing an evidence-based algorithm, we studied suspected cases of AAS. Chi-squared test was used to analyze the association between the variables included in the algorithm and radiological diagnosis, with three categories: no relevant findings, positive for AAS, and alternative diagnoses. Results: 130 requests were identified; 19 (14.6%) had AAS and 34 (26.2%) had a different acute pathology. Of the 19 with AAS, 15 had been stratified as high risk and 4 as intermediate risk. The probability of AAS was 3.4 times higher in patients with known AA (p = 0.021, 95% CI 1.2-9.6) and 5.1 times higher in patients with a new aortic regurgitation murmur (p = 0.019, 95% CI 1.3-20.1). The probability of having an alternative severe acute pathology was 3.2 times higher in patients with hypotension or shock (p = 0.02, 95% CI 1.2-8.5). Conclusion: The use of a CDSS in the emergency department can help optimize AAS diagnosis. In our hospital it improved AAS management and the diagnostic yield of CTA.