Economic evaluation in health care: what is it good for?
Presented by Professor Jon Karnon, from Flinders University.
When: Monday 6th May, 4.30pm
Where: Macquarie University, MGSM Seminar Room 101
Afternoon tea will be available from 4.15pm
This seminar is free, just register by 3rd May 2019. Please register at: https://www.eventbrite.com.au/e/prof-jon-karnon-on-economic-evaluation-in-health-care-what-is-it-good-for-tickets-60383481619
Abstract
Economic evaluations are used to inform government decisions to fund new health technologies, but without being able to observe the best alternative use of the resources required to fund new technologies, it is not clear that economic evaluation is informing the efficient allocation of resources. Elsewhere, economic evaluation is an almost expected component of comparative studies of health service interventions and other economic evaluations are undertaken using published data, but are these economic evaluations being used to inform funding decisions? in a systematic manner?
This seminar will explore the notion of local economic evaluation, discussing the feasibility and value of cost-effectiveness analyses of investment options that reflect the local context, including local processes of care, local resource constraints and local preferences.
Biography
Professor Karnon has undertaken applied evaluation research in a wide range of clinical areas. Analyses he has undertaken or led have informed decisions around the funding of new pharmaceuticals for heart disease, breast cancer, and thalassaemia, patient safety programs, and screening programs for cervical and colorectal cancer and various antenatal and neonatal conditions. More recently, an NHMRC funded simulation model of glaucoma services led to practice change to address increasing demand and won best Australian Health Services Research paper of 2014.
He is currently leading NHMRC research projects estimating the cost-effectiveness threshold to inform funding decisions and developing methods for the appropriate extrapolation of survival data.