Enhancing the Australian national health survey data for use in a microsimulation model of pharmaceutical drug usage and cost

Annie Abello, Sharyn Lymer, Laurie Brown, Ann Harding, Ben Phillips

    Research output: Contribution to journalArticle

    6 Citations (Scopus)

    Abstract

    While static microsimulation models of the tax-transfer system are now available throughout the developed world, health microsimulation models are much rarer. This is, at least in part, due to the difficulties in creating adequate base micro-datasets upon which the microsimulation models can be constructed. In sharp contrast to tax-transfer modelling, no readily available microdata set typically contains all the health status, health service usage and socio-demographic information required for a sophisticated health microsimulation model. This paper describes three new techniques developed to overcome survey data limitations when constructing 'MediSirn', a microsimulation model of the Australian Pharmaceutical Benefits Scheme. Comparable statistical matching and data imputation techniques may be of relevance to other modellers, as they attempt to overcome similar data deficiencies. The 2001 national health survey (NHS) was the main data source for MediSim. However, the NHS has a number of limitations for use in a microsimulation model. To compensate for this, we statistically matched the NHS with another national survey to create synthetic families and get a complete record for every individual within each family. Further, we used complementary datasets to impute short term health conditions and prescribed drug usage for both short- and long-term health conditions. The application of statistical matching methods and use of complementary data sets significantly improved the usefulness of the NHS as a base dataset for MediSim.

    Original languageEnglish
    Pages (from-to)1-26
    Number of pages26
    JournalJASSS
    Volume11
    Issue number3
    Publication statusPublished - 1 Jun 2008

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    pharmaceutical
    Drug products
    Health
    drug
    costs
    health
    Costs
    Taxation
    taxes
    Health Surveys
    health status
    health service

    Cite this

    Abello, Annie ; Lymer, Sharyn ; Brown, Laurie ; Harding, Ann ; Phillips, Ben. / Enhancing the Australian national health survey data for use in a microsimulation model of pharmaceutical drug usage and cost. In: JASSS. 2008 ; Vol. 11, No. 3. pp. 1-26.
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    abstract = "While static microsimulation models of the tax-transfer system are now available throughout the developed world, health microsimulation models are much rarer. This is, at least in part, due to the difficulties in creating adequate base micro-datasets upon which the microsimulation models can be constructed. In sharp contrast to tax-transfer modelling, no readily available microdata set typically contains all the health status, health service usage and socio-demographic information required for a sophisticated health microsimulation model. This paper describes three new techniques developed to overcome survey data limitations when constructing 'MediSirn', a microsimulation model of the Australian Pharmaceutical Benefits Scheme. Comparable statistical matching and data imputation techniques may be of relevance to other modellers, as they attempt to overcome similar data deficiencies. The 2001 national health survey (NHS) was the main data source for MediSim. However, the NHS has a number of limitations for use in a microsimulation model. To compensate for this, we statistically matched the NHS with another national survey to create synthetic families and get a complete record for every individual within each family. Further, we used complementary datasets to impute short term health conditions and prescribed drug usage for both short- and long-term health conditions. The application of statistical matching methods and use of complementary data sets significantly improved the usefulness of the NHS as a base dataset for MediSim.",
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    Enhancing the Australian national health survey data for use in a microsimulation model of pharmaceutical drug usage and cost. / Abello, Annie; Lymer, Sharyn; Brown, Laurie; Harding, Ann; Phillips, Ben.

    In: JASSS, Vol. 11, No. 3, 01.06.2008, p. 1-26.

    Research output: Contribution to journalArticle

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