Studies Show Computerized Decision Tools Can Aid Acute Coronary Syndrome, Pulmonary Embolism Diagnoses

New AHRQ-funded research finds that computerized diagnostic testing can help clinicians assess whether their patients are suffering serious, acute cardiovascular events such as heart attacks. Traditionally, pretest probability assessment—in which clinicians use their experience to discern whether a patient is in danger—has played a central role in diagnosis. This clinical judgment, or “doctor’s best guess,” can help reduce unnecessary and dangerous testing. However, pretest probability assessment is imperfect for ruling out acute coronary syndrome [ACS] (which includes heart attack and unstable angina) and pulmonary embolism [PE] (a sudden blockage in the lung artery). One AHRQ-funded paper, published in Annals of Emergency Medicine, found that clinicians routinely overestimated pretest probability of both ACS and PE compared with computerized pretest methods. A second paper, based on the same study and also published in Annals of Emergency Medicine, found that patients at very low risk of ACS or PE (less than 2.5 percent) may be able to skip imaging (which is often used to test for ACS and PE) and reduce their exposure to radiation. A third paper, published in Circulation: Cardiovascular Imaging, found that computerized pretest probability screening reduces dangerous and expensive testing (including the risk of radiation exposure) in low-risk ambulatory patients with symptoms of ACS and PE. This demonstrates direct benefit of an electronic decision support to aid in diagnosis. All three papers were based on AHRQ-funded research led by Jeffrey A. Kline, M.D., from the Department of Emergency Medicine, Department of Cellular and Integrative Physiology, Indiana University School of Medicine.