Development and validation of a health policy simulation model for type 1 diabetes
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Professor Philip Clarke
Project Details
We bring together an international multi-disciplinary team of health economists, statisticians, epidemiologists and clinicians to develop and validate a health economic computer simulation model for type 1 diabetes.
The simulation model will predict rates of disease-related complications such as myocardial infarction, as well as the impact on costs and quality of life. An important strength of the project is that the team collectively has access to clinical and long-term outcomes on over 50,000 people with Type 1 diabetes from a landmark long term clinical study and two large diabetes registries in Sweden and Scotland. Where possible the model will be complemented with the use of Australian data.
The main purpose of the simulation model will be to inform health policy decisions regarding allocation of resources for people with type 1 diabetes (e.g. in helping undertake cost-effectiveness analysis of new treatments and technologies for this population). The project builds on extensive experience of members of the research team in building diabetes simulation models for people with diabetes.
Researchers
Funding
National Health and Medical Research Council Project Grant
Research Publications
- TRAN-DUY A, KNIGHT J, PALMER A, …, CLARKE PM (2020). A patient-level model to estimate lifetime health outcomes of patients with type 1 diabetes. Diabetes Care, 43, dc192249.
- LUNG WTC, PETRIE, D. Herman, WH. PALMER, AJ Svensson, AM Eliasson B. and CLARKE, PM. "Severe Hypoglycemia and Mortality After Cardiovascular Events for Type 1 Diabetic Patients in Sweden" Published online before print August 4, 2014, doi: 10.2337/dc14-0405
- LUNG TW, CLARKE PM, Hayes AJ, Stevens RJ, Farmer A. Simulating lifetime outcomes associated with complications for people with type 1 diabetes. Pharmacoeconomics. 2013 Jun;31(6):509-18. doi: 10.1007/s40273-013-0047-4
Research Group
School Research Themes
Data science, health metrics and disease modeling
Key Contact
For further information about this research, please contact the research group leader.
Department / Centre
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