Physicians in hospitals that treat a large number of patients with a similar condition will gain experience about the most effective treatments. One would assume this expertise should be reflected in better health outcomes (practice-makes-perfect hypothesis). However, using observational data, a selection bias arises since patients prefer the perceived """"""""better"""""""" hospital, creating a spurious correlation between volume and outcomes (selective-referrals hypothesis). Gaining a comprehensive understanding of the relationship between hospital volume and health outcomes commands a high policy priority. Although the positive relationship between hospital volume and quality of care has been well documented for a large number of medical interventions, few studies have tried to control for the selectivity bias due to selective referrals. The proposed research will take advantage of two existing data bases to better understand the causes of the relationship between hospital volume and health outcomes. This project has the following two specific aims: 1) Obtain unbiased estimates of the effect of hospital volume on health outcomes. 2) Analyze the effects of time since technology adoption and accumulated experience on quality of care. Our data will come from the Cooperative Cardiovascular Project (CCP) (a sample of Medicare patients who were admitted for an acute myocardial infarction (AMI) between 1994 and 1995) and we will use the Nationwide Impatient Sample (NIS) to measure hospital volume and the year when a particular technology was adopted. The CCP data has several advantages to study the relation between hospital volume and health outcomes: 1) It is a large and nationally representative sample, 2) It contains information on post-hospital mortality and readmissions, 3) it contains very detailed information on the severity of illness at admission and the procedures performed, 4) it contains the patient's zip code which will provide us with better instruments than previous studies.
