Jeroen Luyten1, Roselinde Kessels2, Peter Goos3, Philippe Beutels4. 1. Centre for Health Economics Research & Modelling Infectious Diseases, Vaccine & Infectious Disease Institute, Faculty of Medicine & Health Sciences, University of Antwerp, Antwerpen, Belgium; Centre for Economics and Ethics, Institute of Philosophy, University of Leuven, Leuven, Belgium; Department of Social Policy, London School of Economics and Political Science, London, UK. Electronic address: jeroen.luyten@uantwerpen.be. 2. Faculty of Applied Economics, Department of Economics, University of Antwerp, Antwerpen, Belgium; StatUa Center for Statistics, University of Antwerp, Antwerpen, Belgium. 3. Faculty of Applied Economics, Department of Economics, University of Antwerp, Antwerpen, Belgium; StatUa Center for Statistics, University of Antwerp, Antwerpen, Belgium; Department of Econometrics, Erasmus School of Economics, Erasmus University Rotterdam, Rotterdam, The Netherlands; Faculty of Bioscience Engineering, Department of Biosystems, University of Leuven, Leuven, Belgium. 4. Centre for Health Economics Research & Modelling Infectious Diseases, Vaccine & Infectious Disease Institute, Faculty of Medicine & Health Sciences, University of Antwerp, Antwerpen, Belgium; School of Public Health and Community Medicine, The University of New South Wales, Sydney, Australia.
Abstract
BACKGROUND: Setting fair health care priorities counts among the most difficult ethical challenges our societies are facing. OBJECTIVE: To elicit through a discrete choice experiment the Belgian adult population's (18-75 years; N = 750) preferences for prioritizing health care and investigate whether these preferences are different for prevention versus cure. METHODS: We used a Bayesian D-efficient design with partial profiles, which enables considering a large number of attributes and interaction effects. We included the following attributes: 1) type of intervention (cure vs. prevention), 2) effectiveness, 3) risk of adverse effects, 4) severity of illness, 5) link between the illness and patient's health-related lifestyle, 6) time span between intervention and effect, and 7) patient's age group. RESULTS: All attributes were statistically significant contributors to the social value of a health care program, with patient's lifestyle and age being the most influential ones. Interaction effects were found, showing that prevention was preferred to cure for disease in young adults, as well as for severe and lethal disease in people of any age. However, substantial differences were found in the preferences of respondents from different age groups, with different lifestyles and different health states. CONCLUSIONS: Our study suggests that according to the Belgian public, contextual factors of health gains such as patient's age and health-related lifestyle should be considered in priority setting decisions. The studies, however, revealed substantial disagreement in opinion between different population subgroups.
BACKGROUND: Setting fair health care priorities counts among the most difficult ethical challenges our societies are facing. OBJECTIVE: To elicit through a discrete choice experiment the Belgian adult population's (18-75 years; N = 750) preferences for prioritizing health care and investigate whether these preferences are different for prevention versus cure. METHODS: We used a Bayesian D-efficient design with partial profiles, which enables considering a large number of attributes and interaction effects. We included the following attributes: 1) type of intervention (cure vs. prevention), 2) effectiveness, 3) risk of adverse effects, 4) severity of illness, 5) link between the illness and patient's health-related lifestyle, 6) time span between intervention and effect, and 7) patient's age group. RESULTS: All attributes were statistically significant contributors to the social value of a health care program, with patient's lifestyle and age being the most influential ones. Interaction effects were found, showing that prevention was preferred to cure for disease in young adults, as well as for severe and lethal disease in people of any age. However, substantial differences were found in the preferences of respondents from different age groups, with different lifestyles and different health states. CONCLUSIONS: Our study suggests that according to the Belgian public, contextual factors of health gains such as patient's age and health-related lifestyle should be considered in priority setting decisions. The studies, however, revealed substantial disagreement in opinion between different population subgroups.
Authors: Suzana Karim; Benjamin M Craig; Caroline Vass; Catharina G M Groothuis-Oudshoorn Journal: Pharmacoeconomics Date: 2022-08-12 Impact factor: 4.558
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Authors: Bing Wang; Gang Chen; Julie Ratcliffe; Hossein Haji Ali Afzali; Lynne Giles; Helen Marshall Journal: PLoS One Date: 2017-07-26 Impact factor: 3.240
Authors: Hannah Christensen; Hareth Al-Janabi; Pierre Levy; Maarten J Postma; David E Bloom; Paolo Landa; Oliver Damm; David M Salisbury; Javier Diez-Domingo; Adrian K Towse; Paula K Lorgelly; Koonal K Shah; Karla Hernandez-Villafuerte; Vinny Smith; Linda Glennie; Claire Wright; Laura York; Raymond Farkouh Journal: Eur J Health Econ Date: 2019-11-21