Abstract
In this paper, we propose a methodological approach to measure the relationship between hospital costs and health outcomes. We propose to investigate the relationship for each condition or disease area by using patient-level data. We examine health outcomes as a function of costs and other patient-level variables by using the following: (1) two-stage residual inclusion with Murphy-Topel adjustment to address costs being endogenous to health outcomes, (2) random-effects models in both stages to correct for correlation between observation, and (3) Cox proportional hazard models in the second stage to ensure that the available information is exploited. To demonstrate its application, data on mortality following hospital treatment for acute myocardial infarction (AMI) from a large German sickness fund were used. Provider reimbursement was used as a proxy for treatment costs. We relied on the Ontario Acute Myocardial Infarction Mortality Prediction Rules as a disease-specific risk-adjustment instrument. A total of 12,284 patients with treatment for AMI in 2004-2006 were included. The results showed a reduction in hospital costs by €100 to increase the hazard of dying, that is, mortality, by 0.43%. The negative association between costs and mortality confirms that decreased resource input leads to worse outcomes for treatment after AMI.
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