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Using multilevel models for assessing the variability of multinational resource use and cost data

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  • Richard Grieve
  • Richard Nixon
  • Simon G. Thompson
  • Charles Normand

Abstract

Multinational economic evaluations often calculate a single measure of cost‐effectiveness using cost data pooled across several countries. To assess the validity of pooling international cost data the reasons for cost variation across countries need to be assessed. Previously, ordinary least‐squares (OLS) regression models have been used to identify factors associated with variability in resource use and total costs. However, multilevel models (MLMs), which accommodate the hierarchical structure of the data, may be more appropriate. This paper compares these different techniques using a multinational dataset comprising case‐mix, resource use and cost data on 1300 stroke admissions from 13 centres in 11 European countries. OLS and MLMs were used to estimate the effect of patient and centre‐level covariates on the total length of hospital stay (LOS) and total cost. MLMs with normal and gamma distributions for the data within centres were compared. The results from the OLS model showed that both patient and centre‐level covariates were associated with LOS and total cost. The estimates from the MLMs showed that none of the centre‐level characteristics were associated with LOS, and the level of spending on health was the centre‐level variable most highly associated with total cost. We conclude that using OLS models for assessing international variation can lead to incorrect inferences, and that MLMs are more appropriate for assessing why resource use and costs vary across centres. Copyright © 2004 John Wiley & Sons, Ltd.

Suggested Citation

  • Richard Grieve & Richard Nixon & Simon G. Thompson & Charles Normand, 2005. "Using multilevel models for assessing the variability of multinational resource use and cost data," Health Economics, John Wiley & Sons, Ltd., vol. 14(2), pages 185-196, February.
  • Handle: RePEc:wly:hlthec:v:14:y:2005:i:2:p:185-196
    DOI: 10.1002/hec.916
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Thompson, Simon G. & Nixon, Richard M. & Grieve, Richard, 2006. "Addressing the issues that arise in analysing multicentre cost data, with application to a multinational study," Journal of Health Economics, Elsevier, vol. 25(6), pages 1015-1028, November.
    2. 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.
    3. Tom Stargardt, 2008. "Health service costs in Europe: cost and reimbursement of primary hip replacement in nine countries," Health Economics, John Wiley & Sons, Ltd., vol. 17(S1), pages 9-20.
    4. 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.
    5. Mark J. Sculpher & Karl Claxton & Mike Drummond & Chris McCabe, 2006. "Whither trial‐based economic evaluation for health care decision making?," Health Economics, John Wiley & Sons, Ltd., vol. 15(7), pages 677-687, July.
    6. 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.
    7. Aline Gauthier & Andrea Manca & Susan Anton, 2009. "Bayesian Modelling of Healthcare Resource Use in Multinational Randomized Clinical Trials," PharmacoEconomics, Springer, vol. 27(12), pages 1017-1029, December.
    8. Moreno, Elías & Girón, F.J. & Vázquez-Polo, F.J. & Negrín, M.A., 2012. "Optimal healthcare decisions: The importance of the covariates in cost–effectiveness analysis," European Journal of Operational Research, Elsevier, vol. 218(2), pages 512-522.
    9. Ileana Baldi & Eva Pagano & Paola Berchialla & Alessandro Desideri & Alberto Ferrando & Franco Merletti & Dario Gregori, 2013. "Modeling healthcare costs in simultaneous presence of asymmetry, heteroscedasticity and correlation," Journal of Applied Statistics, Taylor & Francis Journals, vol. 40(2), pages 298-310, February.
    10. David Epstein & Anne Mason & Andrea Manca, 2008. "The hospital costs of care for stroke in nine European countries," Health Economics, John Wiley & Sons, Ltd., vol. 17(S1), pages 21-31.
    11. Jonas Schreyögg & Oliver Tiemann & Tom Stargardt & Reinhard Busse, 2008. "Cross-country comparisons of costs: the use of episode-specific transitive purchasing power parities with standardised cost categories," Health Economics, John Wiley & Sons, Ltd., vol. 17(S1), pages 95-103.
    12. Andrew R. Willan & Matthew E. Kowgier, 2008. "Cost-effectiveness analysis of a multinational RCT with a binary measure of effectiveness and an interacting covariate," Health Economics, John Wiley & Sons, Ltd., vol. 17(7), pages 777-791.
    13. Anna Vassall & Lindsay Mangham‐Jefferies & Gabriela B. Gomez & Catherine Pitt & Nicola Foster, 2016. "Incorporating Demand and Supply Constraints into Economic Evaluations in Low‐Income and Middle‐Income Countries," Health Economics, John Wiley & Sons, Ltd., vol. 25(S1), pages 95-115, February.
    14. Richard M. Nixon & Simon G. Thompson, 2005. "Methods for incorporating covariate adjustment, subgroup analysis and between‐centre differences into cost‐effectiveness evaluations," Health Economics, John Wiley & Sons, Ltd., vol. 14(12), pages 1217-1229, December.
    15. 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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