Axel C Mühlbacher1,2, John F P Bridges3, Susanne Bethge4, Ch-Markos Dintsios5,6, Anja Schwalm7, Andreas Gerber-Grote7, Matthias Nübling8. 1. Institute for Health Economics and Health Care Management (IGM), University of Applied Sciences Neubrandenburg, Brodaer Straße 2, 17033, Neubrandenburg, Germany. muehlbacher@hs-nb.de. 2. Center for Health Policy and Inequalities Research, Duke Global Health Institute, Duke University, Durham, NC, USA. muehlbacher@hs-nb.de. 3. Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA. 4. Institute for Health Economics and Health Care Management (IGM), University of Applied Sciences Neubrandenburg, Brodaer Straße 2, 17033, Neubrandenburg, Germany. 5. Strategic Market Access Intelligence, Bayer Health Care, Leverkusen, Germany. 6. Department of Public Health, Faculty of Medicine, Heinrich-Heine University, Düsseldorf, Germany. 7. Institute for Quality and Efficiency in Health Care (IQWiG), Cologne, Germany. 8. Empirical Consulting mbH (GEB mbH), Freiburg, Germany.
Abstract
BACKGROUND: The German Institute for Quality and Efficiency in Health Care (IQWiG) uses patient-relevant outcomes to inform decision-makers. OBJECTIVE: IQWiG conducted a pilot study to examine whether discrete choice experiments (DCEs) can be applied in health economic evaluations in Germany to identify, weight, and prioritize multiple patient-relevant outcomes, using the example of antiviral therapy for chronic hepatitis C (HCV). A further objective was to contribute to a more structured approach towards eliciting and comparing preferences across key stakeholders. METHODS: In autumn 2010, a DCE questionnaire was sent to patients with chronic HCV to estimate preferences across seven outcomes ("attributes"), including treatment efficacy [sustained viral response (SVR) at 6 months], adverse effects (flu-like symptoms, gastrointestinal symptoms, psychiatric symptoms, and skin symptoms/alopecia), and measures of treatment burden (duration of therapy, frequency of injections). A linear model and an effects coded full model were applied to assess the relative importance of the attributes. RESULTS: In total N = 326 patients were included. A clear preference for SVR was shown; frequency of injections and duration of therapy shared the second rank, while psychiatric symptoms ranked third. The duration of flu-like symptoms was the least important attribute. CONCLUSION: Our findings indicate that it is possible to perform a DCE at the national level in a health technology assessment agency. The weighting of multiple outcomes allows an indication-specific and evidence-based measure to be used in health economic evaluations. In decision-making in health care, the approach generally allows for consideration of patient-relevant trade-offs regarding the benefits and harms of medical interventions.
BACKGROUND: The German Institute for Quality and Efficiency in Health Care (IQWiG) uses patient-relevant outcomes to inform decision-makers. OBJECTIVE: IQWiG conducted a pilot study to examine whether discrete choice experiments (DCEs) can be applied in health economic evaluations in Germany to identify, weight, and prioritize multiple patient-relevant outcomes, using the example of antiviral therapy for chronic hepatitis C (HCV). A further objective was to contribute to a more structured approach towards eliciting and comparing preferences across key stakeholders. METHODS: In autumn 2010, a DCE questionnaire was sent to patients with chronic HCV to estimate preferences across seven outcomes ("attributes"), including treatment efficacy [sustained viral response (SVR) at 6 months], adverse effects (flu-like symptoms, gastrointestinal symptoms, psychiatric symptoms, and skin symptoms/alopecia), and measures of treatment burden (duration of therapy, frequency of injections). A linear model and an effects coded full model were applied to assess the relative importance of the attributes. RESULTS: In total N = 326 patients were included. A clear preference for SVR was shown; frequency of injections and duration of therapy shared the second rank, while psychiatric symptoms ranked third. The duration of flu-like symptoms was the least important attribute. CONCLUSION: Our findings indicate that it is possible to perform a DCE at the national level in a health technology assessment agency. The weighting of multiple outcomes allows an indication-specific and evidence-based measure to be used in health economic evaluations. In decision-making in health care, the approach generally allows for consideration of patient-relevant trade-offs regarding the benefits and harms of medical interventions.
Entities:
Keywords:
Conjoint analysis (CA); Discrete choice experiment (DCE); Health technology assessment (HTA); Hepatitis C virus (HCV); Patient preferences; Priority setting
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