A new approach to surveillance of myocardial infarction, the major cardiovascular endpoint is described using an algorithm which depends primarily on enzyme data, using evidence of chest pain and positive electrocardiogram findings as supplemental information only. This approach is evaluated with respect to reproducibility by minimally trained abstractors, cost, and robustness with respect to different hospital systems as well as changes in diagnostic techniques and/or labelling over time. Two pilot studies demonstrate that, in comparison to more traditional approaches, the new surveillance system provides at least a 50% reduction in cost, is highly reproducible over different hospital systems, and potentially, is resilient to changes in diagnostic procedures or coding. The more general applicability of such an innovative surveillance approach to other disease endpoints, in which one reliable procedure contains most of the diagnostic information, is discussed with particular reference to cancer.