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Estimating mean hospital cost as a function of length of stay and patient characteristics

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  • Elena Polverejan
  • Joseph C. Gardiner
  • Cathy J. Bradley
  • Margaret Holmes‐Rovner
  • David Rovner

Abstract

Statistical models have been used to assess the influence of clinical and demographic factors on hospital charge and length of stay (LOS). Hospital costs constitute a significant proportion of overall expenditure in health care. With escalating costs, knowing the correlates of LOS and in‐hospital cost is important for decisions on allocating resources. However, hospital charge and LOS are correlated. We describe two regression models that permit estimation of mean charges as a function of patient hospital stay and adjust for the influence of patient characteristics and treatment procedures on LOS and charge. In the first model, the mean charge over a specified duration is a weighted average of the expected cumulative charge, with weighting determined by the distribution of LOS. The second model for LOS and charge explicitly accounts for their correlation and yields estimates of the average charge per average LOS. The methods are applied to assess mean charges and mean charge per day by cardiac procedure in a cohort of patients hospitalized for acute myocardial infarction, while adjusting for the impact of patient demographic and clinical factors on LOS and charge. For relatively short hospital stays, and when only total hospital charges are available, these models provide a flexible approach to estimating summary measures on resource use while controlling for the effects of covariates on LOS and charge. Copyright © 2002 John Wiley & Sons, Ltd.

Suggested Citation

  • Elena Polverejan & Joseph C. Gardiner & Cathy J. Bradley & Margaret Holmes‐Rovner & David Rovner, 2003. "Estimating mean hospital cost as a function of length of stay and patient characteristics," Health Economics, John Wiley & Sons, Ltd., vol. 12(11), pages 935-947, November.
    • Handle: RePEc:wly:hlthec:v:12:y:2003:i:11:p:935-947
    DOI: 10.1002/hec.774
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    Cited by:

    1. Unto Häkkinen & Pietro Chiarello & Francesc Cots & Mikko Peltola & Hanna Rättö & ON BEHALF OF THE EURODRG GROUP, 2012. "Patient Classification And Hospital Costs Of Care For Acute Myocardial Infarction In Nine European Countries," Health Economics, John Wiley & Sons, Ltd., vol. 21(S2), pages 19-29, August.
    2. Zhao, Xiaobing & Zhou, Xian, 2012. "Estimation of medical costs by copula models with dynamic change of health status," Insurance: Mathematics and Economics, Elsevier, vol. 51(2), pages 480-491.
    3. Donald J Wright, 2004. "Specialist payment schemes and patient selection in private and public hospitals, CHERE Discussion Paper No 54," Discussion Papers 54, CHERE, University of Technology, Sydney.
    4. Anne Mason & Zeynep Or & Thomas Renaud & Andrew Street & Josselin Thuilliez & Padraic Ward & ON BEHALF OF THE EURODRG GROUP, 2012. "How Well Do Diagnosis‐Related Groups For Appendectomy Explain Variations In Resource Use? An Analysis Of Patient‐Level Data From 10 European Countries," Health Economics, John Wiley & Sons, Ltd., vol. 21(S2), pages 30-40, August.
    5. Xiao Zhao & Xian Zhou, 2015. "Estimation of copula-based models for lifetime medical costs," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 67(5), pages 897-915, October.
    6. Wright, Donald J., 2007. "Specialist payment schemes and patient selection in private and public hospitals," Journal of Health Economics, Elsevier, vol. 26(5), pages 1014-1026, September.
    7. Kuwabara, Hiroyo & Fushimi, Kiyohide, 2009. "The impact of a new payment system with case-mix measurement on hospital practices for breast cancer patients in Japan," Health Policy, Elsevier, vol. 92(1), pages 65-72, September.
    8. Emi Sato & Kiyohide Fushimi, 2009. "What has influenced patient health‐care expenditures in Japan?: variables of age, death, length of stay, and medical care," Health Economics, John Wiley & Sons, Ltd., vol. 18(7), pages 843-853, July.
    9. Malgorzata Cyganska & Piotr Cyganski & Chris Pyke, 2019. "Development of clinical value unit method for calculating patient costs," Health Economics, John Wiley & Sons, Ltd., vol. 28(8), pages 971-983, August.
    10. Jason Sutherland & Colin Preyra, 2006. "A mixture model approach to updating payment weights with an application to ICD-10 implementation," Health Care Management Science, Springer, vol. 9(4), pages 349-357, November.

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