Though risk adjustment is necessary in order to make equitable comparisons of resource utilization in the treatment of acute myocardial infarction patients, there is little in the literature that can be practically applied without access to clinical records or specialized registries. The aim of this study is to show that effective models of resource utilization can be developed based on administrative data, and to demonstrate a practical application of the same models by comparing the risk-adjusted performance of the hospitals in our dataset. The study sample included 1748 AMI cases discharged from 10 large, private teaching hospitals in Japan, between 10 April 2001 and 30 June 2004. Explanatory variables included procedures (CABG and PCI), length of stay, outcome, patient demographics, diagnosis and comorbidity status. Multiple linear regression models constructed for the study were able to account for 66.5, 27.7, and 58.4% of observed variation in total charges, length of stay and charges per day, respectively. The performance of models constructed for this study was comparable to or better than performance reported by other studies that made use of explanatory variables extracted from clinical data. The use of administrative data in risk adjustment makes broad scale application of risk adjustment feasible.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.