Location: Dinwoodie Lecture Theatre, Cicely Saunders Institute, Denmark Hill Campus
Better informing decision-making with multiple outcomes cost-effectiveness analysis in palliative care
Speaker: Dr Nikki McCaffrey BSc(Hons) PGDip(ClinPharm) PGDip(HEc) MSc PhD, Department Palliative & Supportive Services, Repatriation General Hospital, Daw Park, Australia
Abstract: Health and social costs globally are escalating. Funders, clinicians and policy makers need to make difficult decisions about where best to invest limited public funds. Economic evaluations systematically compare the costs and benefits of different strategies and help inform decision-makers about how best to maximise benefits for patients from public spending. However, capturing and comparing a range of benefits is important, yet challenging in areas like palliative care. In this seminar, Nikki will highlight the limitations of traditional approaches to multiple outcomes cost-effectiveness analysis in palliative care and present a new approach, multiple outcomes cost-effectiveness analysis under uncertainty in cost-disutility space. She will illustrate the new method with two palliative care case studies and discuss the relative merits of the new approach for informing funders, clinicians and policy makers.
About the speaker: Dr Nikki McCaffrey is a health economist with Flinders Health Economics Group, Flinders University, South Australia and the Australian Palliative Care Clinical Studies Collaborative (PaCCSC), a national collaboration of researchers engaged in Phase III studies in palliative care. She is an investigator on competitive research grants totalling more than AU$4.3 million. Her original research includes: comparison in cost-disutility space when comparing more than two strategies with multiple outcomes in health technology assessment; outcome measurement in palliative care economic evaluations, including the development of disease specific preference based economic measures; evaluation of community models of palliative care; and development of discrete choice attributes from qualitative data.
View presentation slides (PDF, 24 MB)
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