Development and validation of the Ontario acute myocardial infarction mortality prediction rules

OBJECTIVES To develop and validate simple statistical models that can be us ed with hospital discharge administrative databases to predict 30-day and o ne-year mortality after an acute myocardial infarction (AMI). BACKGROUND There is increasing interest in developing AMI "report cards" us ing population-based hospital discharge databases. However, there is a lack of simple statistical models that can be used to adjust for regional and i nterinstitutional differences in patient case-mix. METHODS We used linked administrative databases on 52,616 patients having a n AMI in Ontario, Canada, between 1994 and 1997 to develop logistic regress ion statistical models to predict 30-day and one-year mortality after an AM I. These models were subsequently validated in two external cohorts of AMI patients derived from administrative datasets from Manitoba, Canada, and Ca lifornia, U.S. RESULTS The 11-variable Ontario AMI mortality prediction rules accurately p redicted mortality with an area under the receiver operating characteristic (ROC) curve of 0.78 for 30-day mortality and 0.79 for one-year mortality i n the Ontario dataset from which they were derived. In an independent valid ation dataset of 4,836 AMI patients from Manitoba, the ROC areas were 0.77 and 0.78, respectively. In a second validation dataset of 112,234 AMI patie nts from California, the ROC areas were 0.77 and 0.78 respectively. CONCLUSIONS The Ontario AMI mortality prediction rules predict quite accura tely 30-day and one-year mortality after an AMI in linked hospital discharg e databases of AMI patients from Ontario, Manitoba and California. These mo dels may also be useful to outcomes and quality measurement researchers in other jurisdictions. (J Am Coll Cardiol 2001;37:992-7) (C) 2001 by the Amer ican College of Cardiology.