Background/Aims: Study populations are commonly identified using a single data source. However, the inclusion criteria may result in an unacceptable level of false positives/negatives. The utilization of multiple sources may allow for more complex inclusion criteria, therefore improving the accuracy of identification of cases and controls for use in research. For this study, Geisinger’s electronic health record (EHR) was combined with clinical databases to identify a population of patients with suspected Acute Myocardial Infarction (AMI)
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