Development of a Dynamic Microsimulation Model to Investigate How Best to Compress Morbidity in Older Australians and Optimise Ageing

This paper reports the development of a dynamic microsimulation model being built as part of the DYNOPTA (Dynamic Analyses to Optimize Ageing) Project. The model aims to establish a demographic modelling infrastructure that can be used to simulate the health and social outcomes of Australia's baby boomer and aged cohorts and examine the impacts of possible social and medical interventions to compress morbidity and optimise ageing in Australia over the next 20 years. The DYNOPTA microsimulation model is founded on a pooled dataset which combines data from nine Australian Longitudinal Studies of Ageing. The pooled dataset is being used to inform the base file, identify key incidence and prevalence rates, risk and protective factors for health outcomes, and disease pathways and transition rates. The modelling focuses on four conditions that contribute to burden of disease and quality of life in the aged - cognitive decline and dementia, sensory impairment, impairment in mobility, and depression. The microsimulation modelling is underpinned by a life course approach to development and ageing that recognises interdependencies among demographic, social, economic and health factors. The base population are those aged 45 years and over. The number of individuals in various states of disability, and the length of time spent in these states prior to death, will be modelled over the 30 year simulation period - and associated health costs estimated for both base case and scenario projections. Once built, the model will provide a new and innovative means of directly informing health and social policy on the aged in Australia.