LAUSR

OBJECTIVE To evaluate medical costs of novel therapies in complex medical settings using registry data. DATA SOURCE/STUDY SETTING Primary data, from 2008 to 2010. We used patient registry data to evaluate cost and quality performance of coronary computed tomography angiography (CCTA) in triaging chest pain patients in our tertiary care emergency department and to model financial performance under Medicare's two midnight rule. STUDY DESIGN Using generalized linear modeling, we retrospectively compared estimated expenditures for evaluation of low-to-intermediate-risk chest pain for demographic and medically risk matched samples of 894 patients each, triaged with CCTA or local standard of care (SOC) using Medicare reimbursement as a proxy. DATA COLLECTION/EXTRACTION METHODS Predefined data elements were downloaded from the hospital mainframe into the CCTA registry, where they were validated and maintained electronically. PRINCIPLE FINDINGS We found that predicted standard of care costs were 2.5 times higher on the initial visit and 1.98 times higher over 30 days (p < .001) than those using CCTA. Predicted cost was 1.6 times higher when we applied our two midnight rule model (p < .001). CONCLUSION Rapid assessment of treatment using registry data is a promising means of analyzing cost performance in complex health care environments.