Impact of Double Counting and Transfer Bias on Estimated Rates and Outcomes of Acute Myocardial Infarction

Context. Ischemic heart disease is the leading cause of death in the United States. Recent studies report inconsistent findings on the changes in the incidence of hospitalizations for ischemic heart disease. These reports have relied primarily on hospital discharge data. Preliminary data suggest that a significant percentage of patients suffering acute myocardial infarction (MI) in rural communities are transferred to urban centers for care. Patients transferred to a second hospital may be counted twice for one episode of ischemic heart disease. Objective. To describe the impact of double counting and transfer bias on the estimation of incidence rates and outcomes of ischemic heart disease, specifically acute MI, in the United States. Design. Analysis of state hospital discharge data from Kansas, Colorado (State Inpatient Database [SID]), Nebraska, Arizona, New Jersey, Michigan, Pennsylvania, and Illinois (SID) for the years 1995 to 1997. A matching algorithm was developed for hospital discharges to determine patients counted twice for one episode of ischemic heart disease. Validation of our matching algorithm. Patients. Patients reported to have suffered ischemic heart disease (ICD9 codes 410-414, 786.5). Main Outcome Measures. Number of patients counted twice for one episode of acute MI. Results. It is estimated that double count rates range from 10% to 15% for all states and increased over the 3 years. Moderate sized rural counties had the highest estimated double count rates at 15% to 20% with a few counties having estimated double count rates a high as 35% to 50%. Older patients and females were less likely to be double counted (P