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

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.Base Data, Drug Usage, Microsimulation, Pharmaceutical Benefits, Scripts, Statistical Matching

Challenges and Solutions in Constructing a Microsimulation Model of the Use and Costs of Medical Services in Australia

This paper describes the development of a microsimulation model =HealthMod‘ which simulates the use and costs of medical and related services by Australian families. Australia has a universal social insurance scheme known as =Medicare‘ which provides all Australians with access to free or low-cost essential medical services. These services are provided primarily by general practitioners as well as specialist doctors but also include diagnostic and imaging services. Individuals may pay a direct out-of pocket contribution if fees charged for services are higher than the reimbursement schedule set by government. HealthMod is based on the Australian 2001 National Health Survey. This survey had a number of deficiencies in terms of modelling the national medical benefits scheme. The article outlines three major methodological steps that had to be taken in the model construction: the imputation of synthetic families, the imputation of short-term health conditions, and the annualisation of doctor visits and costs. Some preliminary results on the use of doctor services subsidised through Australia‘s Medicare are presented.Economic microsimulation modelling, medical services, use and costs, Australia

Application of statistical and decision-analytic models for evidence synthesis for decision-making in public health and the healthcare sector

With the awareness that healthcare is a limited resource, decision-makers are challenged to allocate it rationally and efficiently. Health economic methods of evidence synthesis for decision-making are useful to quantify healthcare resource utilisation, critically evaluate different interventions and ensure the implementation of the most effective or cost-effective strategy. The nine studies included in the present cumulative doctoral thesis aim to demonstrate the capability of statistical and decision-analytic modelling techniques to inform and support rational healthcare decision-making in Germany. Five studies apply statistical modelling in analyses of public health and health economic data. They show that the developed models are valuable instruments for examining patterns in the data and generating knowledge from observable data which can further be used in devising disease management and care programs as well as economic evaluations. Further, two health economic evaluations, which adopt the decision-analytic-modelling approach, show that decision-analytic modelling is a powerful tool to represent the epidemiology of infectious and non-infectious diseases on a population level, quantify the burden of the diseases, generalise the outcomes of clinical trials, and predict how the interventions can change the impact of the diseases on the health of the population. Additionally, two literature reviews examine the application of decision-analytic modelling in health economic evaluations. The first study reviews and empirically analyses health technology assessments by the German Institute for Medical Documentation and Information and demonstrates that the application of decision-analytic models improves the evidence produced for policy-making in the healthcare sector in Germany. The second systematic review focuses on methodological choices made in constructing decision-analytic models and explains how critically the structural and parametrical assumptions can influence the final message of the economic evaluations and shows that building a validated, reliable model as well as the transparent reporting is of high priority in facilitating the communication and implementation of the most cost-effective course of action. Overall, the present thesis shows the relevance and advantage of the application of models in synthesising evidence for decision-making. The included studies contribute to the current and future development of the methods used to address the problems of health economic efficiency. Further advances in the computational modelling techniques and data collection, from one side, will ease the decision-making process, but, from another side, will require increasing competence and understanding within the decision-making bodies

Gesundheitsökonomische Aspekte zur Gesundheitsförderung und Prävention von chronischen Lungenerkrankungen

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A consensus approach to building diabetes capabilities in the healthcare workforce

This study investigated the different health professional practice levels that signified a change in the breadth of knowledge and skills required to deliver diabetes education and care in Australia. Further, it identified the capabilities needed by health professionals to deliver quality, safe diabetes education and care to increase the health workforce’s capacity to manage diabetes. It resulted in the development of a capability framework to guide training and practice