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Risk adjusted resource utilization for AMI patients treated in Japanese hospitals

Author

Listed:
  • Edward Evans
  • Yuichi Imanaka
  • Miho Sekimoto
  • Tatsuro Ishizaki
  • Kenshi Hayashida
  • Haruhisa Fukuda
  • Eun‐Hwan Oh

Abstract

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. Copyright © 2006 John Wiley & Sons, Ltd.

Suggested Citation

  • Edward Evans & Yuichi Imanaka & Miho Sekimoto & Tatsuro Ishizaki & Kenshi Hayashida & Haruhisa Fukuda & Eun‐Hwan Oh, 2007. "Risk adjusted resource utilization for AMI patients treated in Japanese hospitals," Health Economics, John Wiley & Sons, Ltd., vol. 16(4), pages 347-359, April.
    • Handle: RePEc:wly:hlthec:v:16:y:2007:i:4:p:347-359
    DOI: 10.1002/hec.1177
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    Cited by:

    1. Galina Besstremyannaya, 2011. "Managerial performance and cost efficiency of Japanese local public hospitals: A latent class stochastic frontier model," Health Economics, John Wiley & Sons, Ltd., vol. 20(S1), pages 19-34, September.
    2. Oliver Tiemann, 2008. "Variations in hospitalisation costs for acute myocardial infarction – a comparison across Europe," Health Economics, John Wiley & Sons, Ltd., vol. 17(S1), pages 33-45, January.
    3. Jonas Schreyögg, 2008. "A micro‐costing approach to estimating hospital costs for appendectomy in a Cross‐European context," Health Economics, John Wiley & Sons, Ltd., vol. 17(S1), pages 59-69, January.
    4. Siok Tan & Leona Hakkaart-van Roijen & B. Ineveld & W. Redekop, 2013. "Explaining length of stay variation of episodes of care in the Netherlands," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 14(6), pages 919-927, December.
    5. Tom Stargardt & Jonas Schreyögg & Ivan Kondofersky, 2014. "Measuring The Relationship Between Costs And Outcomes: The Example Of Acute Myocardial Infarction In German Hospitals," Health Economics, John Wiley & Sons, Ltd., vol. 23(6), pages 653-669, June.
    6. Cohen, Deborah & Manuel, Douglas G. & Tugwell, Peter & Sanmartin, Claudia & Ramsay, Tim, 2014. "Direct healthcare costs of acute myocardial infarction in Canada’s elderly across the continuum of care," The Journal of the Economics of Ageing, Elsevier, vol. 3(C), pages 44-49.
    7. Park, Sungchul & Lee, Jason & Ikai, Hiroshi & Otsubo, Tetsuya & Imanaka, Yuichi, 2013. "Decentralization and centralization of healthcare resources: Investigating the associations of hospital competition and number of cardiologists per hospital with mortality and resource utilization in ," Health Policy, Elsevier, vol. 113(1), pages 100-109.
    8. Ishizaki, Tatsuro & Imanaka, Yuichi & Oh, Eun-Hwan & Sekimoto, Miho & Hayashida, Kenshi & Kobuse, Hiroe, 2008. "Association between patient age and hospitalization resource use in a teaching hospital in Japan," Health Policy, Elsevier, vol. 87(1), pages 20-30, July.
    9. Jonas Schreyögg & Tom Stargardt & Oliver Tiemann, 2011. "Costs and quality of hospitals in different health care systems: a multi‐level approach with propensity score matching," Health Economics, John Wiley & Sons, Ltd., vol. 20(1), pages 85-100, January.

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