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Seminar Series 2008 |
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The Seminar Series presents local and international researchers discussing recent health economics projects, including those undertaken by the CHERE team. Follow this link if you would like to receive email notification about the 2008 CHERE Seminar Series. Thursday 29 May, 2008 at 4pm Paul Brown, PhD (Wisconsin), Senior Health Economist in the School of Population Health at the University of Auckland. He is also the Director of the Centre for Health Services Research and Policy Interest and willingness to pay for genetic risk information Abstract: Genetic tests vary in their prediction of disease occurrence, with some mutations conferring relatively low risk and others indicating near certainty. The current study assessed how increments in disease risk influence individual’s willingness to pay for a genetic test, and how willingness to pay varied with risk perceptions, interest, and expected consequences of genetic tests for diseases of varying severity. Adults (N=752), recruited from New Zealand, Australia, and the UK for an online analogue study, were randomly assigned to receive information about a test of genetic risk for diabetes, heart disease, colon cancer or lung cancer. The risk varied across conditions by 10% increments, from 20% to 100%. Participants completed measures of perceived likelihood of disease for individuals with mutations, risk-related affect, interest, and testing consequences. Analyses revealed two increment clusters yielding differences in likelihood perceptions: A “moderate risk” cluster (20% to 70 %), and a “high risk” cluster (80% to 100%). Risk increment influenced willingness to pay for the test as well as expectations of worry, feelings of risk, testing-induced distress, and family obligations, with nonlinear patterns including disproportionately high responses for the 50% increment. Risk increment did not alter interest in testing or perceived benefits. These patterns of effects held across the four diseases. The results suggest that magnitudes of risk from genetic testing have a nonlinear influence on willingness to pay for genetic tests. Room: 5D.01.12 located in the UTS Business Faculty, Quay St, Haymarket. For more information contact: stephen.goodall@chere.uts.edu.au Thursday 1 May, 2008 at 4pm Peter Sivey, MSc (Health Economics) and BSc (Economics/Econometrics), both from The University of York, Research Fellow at the Melbourne Institute of Applied Economic and Social Research Including quality in a model of hospital choice for NHS CABG patients Abstract: We measure hospital quality using mortality rates and model hospital choice for NHS Coronary Artery Bypass Graft (CABG) patients. Hospital quality has the expected positive effect on hospital choice, but this result is sensitive to methodology. We also estimate how distance and hospital waiting times determine hospital choice. Including census data linked to patient postcodes, we interact patient characteristics with hospital attributes to capture observable heterogeneity. Room: 5D.01.12 located in the UTS Business Faculty, Quay St, Haymarket. Tuesday 4 March, 2008 at 12pm Clare Emmett, BSc, MSc, CPsychol: Research Associate & Chartered Health Psychologist. Academic Unit of Primary Health Care, University of Bristol, UK Decision aids for mode of delivery after previous caesarean section Background: Pregnant women with one previous caesarean section (CS) must decide their preferred mode of delivery. For most this is a preference-sensitive decision involving a choice between attempted vaginal birth after caesarean (VBAC) and elective CS. Decision aids are interventions designed to assist patients to make treatment choices and have been shown to be beneficial in a variety of health settings. Aim: To design and evaluate two computer-based decision aids to assist pregnant women with one previous CS with decision making about preferred mode of delivery. Methods: The research project has four components 1) A qualitative interview study involving 21 postnatal women, which explored women’s experiences of decision making. 2) Development of two computer-based decision aids by a multidisciplinary team and a piloting study involving 15 postnatal and 11 antenatal women. 3) A randomised controlled trial (RCT) to evaluate the two decision aids (Information Program or Decision Analysis Program) compared to usual care. 742 women with one previous CS participated in the RCT. The primary outcomes were decisional conflict at 37 weeks’ gestation and actual mode of delivery. 4) A focus group study involving 28 health professionals to explore barriers and facilitators to implementation in routine practice. Results: The interview study established a need for the decision aids by highlighting potential inadequacies in the provision of information in routine care. The piloting study showed that the proposed decision aids were acceptable, usable and comprehensive. The RCT demonstrated that both decision aids reduced decisional conflict compared with usual care. There was also a suggestion that the VBAC rate was higher amongst women in the Decision Analysis Program group, in comparison to the other groups. Discussion: Pregnant women with one previous CS were found to benefit from access to either of the decision aids as an adjunct to routine clinical care. Further investigation is required to confirm whether the Decision Analysis Program could help to reduce the discrepancy between women’s preferred and actual mode of delivery. Issues relating to the implementation of the decision aids must also be considered. Room: 5D.01.12 . Located in the UTS Business Faculty, Quay St, Haymarket. See map http://www.uts.edu.au/about/mapsdirections/citymap.html Room 112 is located on the ground floor. Enter building 5 via entrance D. Follow the corridor to the right. The seminar is free and open to visitors. Light refreshments will be served afterwards. RSVP by Thursday Feb 28, 2008, to gretchen.togle@chere.uts.edu.au For more info Contact: stephen.goodall@chere.uts.edu.au
Dr Katherine Payne: RCUK Academic Fellow in Health Economics, Health Economics Research at Manchester, School of Community Based Medicine, The University of Manchester Outcome measures for clinical genetics services: do QALYs have a role? Abstract: There has been, and will continue to be, a rapid expansion in genetics knowledge about the basis of disease and associated developments in new genetic tests and clinical genetics services. Clinical genetics services compete with other healthcare services for scarce resources and it is therefore important to evaluate the impact of clinical genetics services on patients and their families. Current evidence suggests that appropriate measures to value the health and social outcomes of clinical genetics services are not readily available. There is little comparative evidence of the effectiveness, benefits and value of clinical genetics services. This seminar will describe a programme of research carried by a team of researchers based at Nowgen – A Centre for Genetics in Healthcare that aimed to develop a set of outcome measures appropriate to value the patient benefits from using a clinical genetics service. The programme combined data from three studies: (1) a systematic review to identify existing validated outcome measures; (2) a Delphi survey to identify the degree of consensus about the relevance of existing outcome measures and (3) qualitative research (focus groups and semi-structured interviews) to explore the outcomes valued by patients, patient representatives and service providers. Triangulation (methods, investigators, disciplines and data) was used as an approach to achieve completeness rather than to seek confirmation of findings using different methods. Results will be discussed in the context of whether the QALY, currently preferred as the outcome of choice by national decision-makers in the UK, does (or should) have a role in the evaluation of clinical genetics services and associated genetic tests.
Room 112 is located on the ground floor. Enter building 5 via entrance D. Follow the corridor to the right. RSVP by Monday Feb 4, 2008, to gretchen.togle@chere.uts.edu.au Francesco Paolucci: Research Fellow, Australian Centre for Economic Research on Health (ACERH), Australian National University (ANU) Subsidising Private Health Insurance in Australia: Why, How and How to proceed? Abstract: Australia’s health care system relies upon a mix of public-private financing and public-private provision of health services. These health financing arrangements lead to duplication in insurance coverage for those who purchase private health insurance. Duplication arises because the Medicare coverage for public hospital services cannot be used for private hospital services. Those who purchase private health insurance therefore have to pay a premium that covers the full cost of private hospital services and not just the additional cost of the private hospital services. A large part of private health insurance coverage is therefore duplicate coverage while only a small part is supplementary coverage. There are two broad policy options to remove this duplication in coverage. One is to reduce Medicare coverage for those who purchase private health insurance, making private health insurance fully substitutable for public health insurance. The other is to expand the coverage available under the public scheme to include private hospital services, thereby confining the role of private health insurance to supplementary coverage only. This paper is concerned with the first of these options. If this option is pursued, then from an efficiency perspective it is argued that: (a) purchase of private health insurance should be substitutive of Medicare coverage (i.e. allow opting out); (b) community-rating regulations should be replaced by premium bands that constrain the variation in premiums that can be charged for any product; and (c) the current 30% ad valorem subsidy for private health insurance should be replaced by risk-adjusted subsidies that are positively correlated with an individual’s risk. Date: Thursday 17 January, 2008 RSVP by Monday Jan 14, 2008, to gretchen.togle@chere.uts.edu.au
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