Objective: To determine the ability of administrative data in predicting in-hospital mortality for patients undergoing coronary artery bypass graft surgery.
Methods: Patient data were obtained from the administrative databases on hospital discharge abstracts of the Italian region Emilia Romagna for the years 2000-2001. We used a multivariate logistic regression analysis to compare an ICD-9-CM risk adjustment approach based on administrative variables (such as age, gender, principal diagnosis, combined operation, previous cardiac surgery, emergency admission, and Charlson comorbidity index) with a risk adjustment approach based on the clinical European System for Cardiac Operative Risk Evaluation (EuroSCORE) to predict in-hospital mortality and to assess hospital performance. In order to distinguish complications of care from comorbidities, we linked hospital data across multiple episodes of care up to 1 year before the admission for coronary artery bypass graft (CABG).
Results: The risk adjustment approach based on ICD-9-CM data provides good explanatory ability in models assessing in-hospital mortality (the c statistics obtained are very close: c = 0.76 in 2000 and c = 0.80 in 2001 for the administrative model versus 0.78 in 2000 and 0.77 in 2001 for the clinical one) and in those ranking the centres (c = 0.78 in 2000 in both approaches, and c = 0.82 for the administrative model versus c = 0.78 for the clinical one in 2001).
Conclusions: Adding some administrative variables considered proxy for clinical complexity to the administrative model and linking hospital data across patients' multiple episodes of care eliminated much of the difference in effectiveness between the clinical and administrative risk adjustment approach. Focusing on the health policy context of measuring CABG death rates, our study strengthened the thesis that, with the growing improvement in accurate coding practice, administrative databases could provide a valuable and economical source for health planning and research.