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Enhancing the Australian National Health Survey Data for Use in a Microsimulation Model of Pharmaceutical Drug Usage and Cost

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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 'MediSim', 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.

Suggested Citation

  • Annie Abello & Sharyn Lymer & Laurie Brown & Ann Harding & Ben Phillips, 2008. "Enhancing the Australian National Health Survey Data for Use in a Microsimulation Model of Pharmaceutical Drug Usage and Cost," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 11(3), pages 1-2.
  • Handle: RePEc:jas:jasssj:2007-76-2
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    File URL: http://jasss.soc.surrey.ac.uk/11/3/2/2.pdf
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    1. Laurie Brown & Ann Harding, 2002. "Social Modelling and Public Policy: Application of Microsimulation Modelling in Australia," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 5(4), pages 1-6.
    2. Creedy, John, 2001. "Tax Modelling," The Economic Record, The Economic Society of Australia, vol. 77(237), pages 189-202, June.
    3. Rodgers, Willard L, 1984. "An Evaluation of Statistical Matching," Journal of Business & Economic Statistics, American Statistical Association, vol. 2(1), pages 91-102, January.
    4. Sutherland, Holly & Taylor, Rebecca & Gomulka, Joanna, 2002. "Combining Household Income and Expenditure Data in Policy Simulations," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 48(4), pages 517-536, December.
    5. Ann Harding & Richard Percival & Deborah Schofield & Agnes Walker, 2002. "The Lifetime Distributional Impact of Government Health Outlays," Australian Economic Review, The University of Melbourne, Melbourne Institute of Applied Economic and Social Research, vol. 35(4), pages 363-379.
    6. Ann Harding & Annie Abello & Laurie Brown & Ben Phillips, 2004. "Distributional Impact of Government Outlays on the Australian Pharmaceutical Benefits Scheme in 2001-02," The Economic Record, The Economic Society of Australia, vol. 80(s1), pages 83-96, September.
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    Cited by:

    1. Sharyn Lymer & Laurie Brown & Ann Harding & Alicia Payne, 2011. "Challenges and Solutions in Constructing a Microsimulation Model of the Use and Costs of Medical Services in Australia," International Journal of Microsimulation, International Microsimulation Association, vol. 4(3), pages 17-31.
    2. Zucchelli, E & Jones, A.M & Rice, N, 2010. "The evaluation of health policies through microsimulation methods," Health, Econometrics and Data Group (HEDG) Working Papers 10/03, HEDG, c/o Department of Economics, University of York.
    3. Eugenio Zucchelli & Andrew M Jones & Nigel Rice, 2012. "The evaluation of health policies through dynamic microsimulation methods," International Journal of Microsimulation, International Microsimulation Association, vol. 5(1), pages 2-20.

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