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Estimating Costs Associated with Disease Model States Using Generalized Linear Models: A Tutorial

Author

Listed:
  • Junwen Zhou

    (University of Oxford)

  • Claire Williams

    (University of Oxford)

  • Mi Jun Keng

    (University of Oxford)

  • Runguo Wu

    (Queen Mary University of London)

  • Borislava Mihaylova

    (University of Oxford
    Queen Mary University of London)

Abstract

Estimates of costs associated with disease states are required to inform decision analytic disease models to evaluate interventions that modify disease trajectory. Increasingly, decision analytic models are developed using patient-level data with a focus on heterogeneity between patients, and there is a demand for costs informing such models to reflect individual patient costs. Statistical models of health care costs need to recognize the specific features of costs data which typically include a large number of zero observations for non-users, and a skewed and heavy right-hand tailed distribution due to a small number of heavy healthcare users. Different methods are available for modelling costs, such as generalized linear models (GLMs), extended estimating equations and latent class approaches. While there are tutorials addressing approaches to decision modelling, there is no practical guidance on the cost estimation to inform such models. Therefore, this tutorial aims to provide a general guidance on estimating healthcare costs associated with disease states in decision analytic models. Specifically, we present a step-by-step guide to how individual participant data can be used to estimate costs over discrete periods for participants with particular characteristics, based on the GLM framework. We focus on the practical aspects of cost modelling from the conceptualization of the research question to the derivation of costs for an individual in particular disease states. We provide a practical example with step-by-step R code illustrating the process of modelling the hospital costs associated with disease states for a cardiovascular disease model.

Suggested Citation

  • Junwen Zhou & Claire Williams & Mi Jun Keng & Runguo Wu & Borislava Mihaylova, 2024. "Estimating Costs Associated with Disease Model States Using Generalized Linear Models: A Tutorial," PharmacoEconomics, Springer, vol. 42(3), pages 261-273, March.
  • Handle: RePEc:spr:pharme:v:42:y:2024:i:3:d:10.1007_s40273-023-01319-x
    DOI: 10.1007/s40273-023-01319-x
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    References listed on IDEAS

    as
    1. Junwen Zhou & Runguo Wu & Claire Williams & Jonathan Emberson & Christina Reith & Anthony Keech & John Robson & Kenneth Wilkinson & Jane Armitage & Alastair Gray & John Simes & Colin Baigent & Borisla, 2023. "Prediction Models for Individual-Level Healthcare Costs Associated with Cardiovascular Events in the UK," PharmacoEconomics, Springer, vol. 41(5), pages 547-559, May.
    2. Daryl Pregibon, 1980. "Goodness of Link Tests for Generalized Linear Models," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 29(1), pages 15-24, March.
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