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michelle picture.jpgAbstract: Standard approaches to modelling outcomes commonly include a range of predictors such as age, sex and co-morbidities. However, there is growing evidence that quality-of-life (QoL) is also an important predictor of mortality.

Whilst the effects of standard risk factors have been adequately captured to describe mortality in most models, the omission of QoL indicates the assumption of full independence between QoL and life expectancy (LE). This omission could give rise to systematic bias when measuring quality-adjusted life years (QALYs).

Using data from a registry cohort of patients undergoing total knee replacement (TKR), potential correlations between baseline utility, change in utility and survival are explored using parametric survival models. Outcomes such as LE, QALYs, and incremental cost-effectiveness ratios (ICERs) were calculated and compared.

Biography: Michelle Tew is a Research Assistant at the Centre for Health Policy, Melbourne School of Population and Global Health. She completed her postgraduate training in Public Health specialising in Health Economics and Economic Evaluation at the University of Melbourne (MPH; Australia) and in Pharmacy at the University of Nottingham (MPharm; UK). Since 2015, she has worked on a number of costing studies including analysing costs associated with Caesarean section for overweight women and in the implementation of a sepsis protocol pathway. She has worked with large datasets, in particular with BreastScreen Victoria data, and contributed to a return on investment study for the Victorian Department of Health. She is also part of the team providing economic evaluation for the Medical Services Advisory Committee (MSAC) at the Department of Health to inform decisions about listing of new Medicare 

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Forthcoming events

Quality of Life Trajectories in Total Knee Replacement Patients: What can they tell us?

Thursday, 27 June 2019, 1pm to 2pm @ Big Data Institute (BDI) LG 0 Seminar Room