Simulation Modelling and Risk Prediction

Overview

Our research includes the development of a range of simulation models and risk prediction tools.

Many health economic questions involve use of simulation modelling, as it can take years for intervention to have an impact particularly on chronic diseases such as diabetes. The development of these simulation models requires extensive development time and experience, as they involve exhaustive synthesis of clinical and economic data. Our Unit is involved in the development of several simulation models for use in evaluating interventions for:

• Type 1 and 2 Diabetes
• Cardiovascular disease (including for indigenous Australians)
• Osteoarthritis

Projects

Development and validation of a health policy simulation model for cardiovascular disease

Development and validation of a health policy simulation model for Type 1 diabetes

Building a simulation model to improve cardiovascular disease risk prediction and treatment for Indigenous Australians

Prediction tools:

An Android app for cardiovascular risk assessment in remote Indigenous Australia

An iOS app for cardiovascular risk assessment in remote Indigenous Australia

An interactive web app for visualizing risks of complications and death, and survival times in patients with type 1 diabetes

Selected 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.

TRAN-DUY A, McDermott R, KNIGHT J, HUA X, Barr EL, Arabena K, PALMER A and CLARKE PM (2020). Development and use of prediction models for classification of cardiovascular risk of remote indigenous Australians. Heart, Lung and Circulation 2019, 29, 374-383.

Lung, TW., CLARKE, PM., Hayes, AJ., Stevens, RJ., & Farmer, A. (2013). Simulating lifetime outcomes associated with complications for people with type 1 diabetes. Pharmacoeconomics, 31(6), 509-518.

Hayes, AJ., Leal, J., Gray, AM., Holman, RR., & CLARKE, PM. (2013). UKPDS Outcomes Model 2: a new version of a model to simulate lifetime health outcomes of patients with type 2 diabetes mellitus using data from the 30 year United Kingdom Prospective Diabetes Study: UKPDS 82.Diabetologia,1-9.

HUA, X., Lung, T. W. C., Palmer, A., Si, L., Herman, W. H., & CLARKE, P. (2017). How Consistent is the Relationship between Improved Glucose Control and Modelled Health Outcomes for People with Type 2 Diabetes Mellitus? a Systematic Review. PharmacoEconomics, 35, 319-329.

HUA, X., McDermott, R., Lung, T., Wenitong, M., TRAN-DUY, A., Li, M., & CLARKE, P. (2017). Validation and recalibration of the Framingham cardiovascular disease risk models in an Australian Indigenous cohort. Eur J Prev Cardiol, 24, 1660-1669.

SCHILLING, C., DALZIEL, K., Nunn, R., Du Plessis, K., Shi, W. Y., Celermajer, D., ... & Bullock, A. (2016). The Fontan epidemic: Population projections from the Australia and New Zealand Fontan Registry. International Journal of Cardiology, 219, 14-19.