Ruth Schwarzer1,2, Ursula Rochau1,2, Kim Saverno1,3, Beate Jahn1,2, Bernhard Bornschein1, Nikolai Muehlberger1, Magdalena Flatscher-Thoeni4, Petra Schnell-Inderst1,2, Gaby Sroczynski1,2, Martina Lackner1, Imke Schall1, Ansgar Hebborn5, Karl Pugner6, Andras Fehervary7, Diana Brixner1,2,3,8, Uwe Siebert1,2,9,10. 1. Department of Public Health, Health Services Research & Health Technology Assessment, Institute of Public Health, Medical Decision Making & Health Technology Assessment, UMIT - University for Health Sciences, Medical Informatics & Technology, Eduard Wallnoefer Center I, 6060 Hall i.T., Austria. 2. Division of Public Health Decision Modelling, Health Technology Assessment & Health Economics, ONCOTYROL - Center for Personalized Cancer Medicine, Innrain 66a, 6020 Innsbruck, Austria. 3. Department of Pharmacotherapy, University of Utah, 30 South 2000, Salt Lake City, UT 84112, USA. 4. Program on Health Policy, Administration, Economics & Law, Department of Public Health & Health Technology Assessment, UMIT - University for Health Sciences, Medical Informatics & Technology, Eduard Wallnoefer Center I, 6060 Hall i.T., Austria. 5. F Hoffmann-La Roche AG, Market Access Policy, Grenzacher Str. 124, 4070 Basel, Switzerland. 6. Amgen, Department of Health Economics & Reimbursement, Dammstrasse 23, 6301 Zug, Switzerland. 7. Novartis International AG, Government Affairs Europe, Novartis Campus, Fabrikstrasse 1, 4002 Basel, Switzerland. 8. Program in Personalized Health Care, Outcomes Research Center, Department of Pharmacotherapy, University of Utah, 30 South 2000, Salt Lake City, UT 84112, USA. 9. Department of Health Policy & Management, Center for Health Decision Science, Harvard T.H. Chan School of Public Health, 718 Huntington Ave., Boston, MA 02115, USA. 10. Institute for Technology Assessment & Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 101 Merrimac Street, Boston, MA 02114-4724, USA.
Abstract
AIM: To provide an overview of thresholds for incremental cost-effectiveness ratios (ICERs) representing willingness-to-pay (WTP) across multiple countries and insights into exemptions pertaining to the ICER (e.g., cancer). To compare ICER thresholds to individual country's estimated ability-to-pay. MATERIALS & METHODS: We included AHRQ/USA, BIQG-GOEG/Austria, CADTH/Canada, DAHTA@DIMDI/Germany, DECIT-CGATS/Brazil, HAS/France, HITAP/Thailand, IQWiG/Germany, LBI-HTA/Austria, MSAC/Australia, NICE/England/Wales and SBU/Sweden. ICER thresholds were derived from systematic literature/website search/expert surveys. WTP was compared with ATP using Spearman's rank correlation. RESULTS: Two general and explicitly acknowledged thresholds (England/Wales, Thailand), implicit thresholds in six countries and different ICER thresholds/decision-making rules in oncology were identified. Correlation between WTP and ability-to-pay was moderate. DISCUSSION: Our overview supports country-specific discussions on WTP and on how to define value(s) within societies.
AIM: To provide an overview of thresholds for incremental cost-effectiveness ratios (ICERs) representing willingness-to-pay (WTP) across multiple countries and insights into exemptions pertaining to the ICER (e.g., cancer). To compare ICER thresholds to individual country's estimated ability-to-pay. MATERIALS & METHODS: We included AHRQ/USA, BIQG-GOEG/Austria, CADTH/Canada, DAHTA@DIMDI/Germany, DECIT-CGATS/Brazil, HAS/France, HITAP/Thailand, IQWiG/Germany, LBI-HTA/Austria, MSAC/Australia, NICE/England/Wales and SBU/Sweden. ICER thresholds were derived from systematic literature/website search/expert surveys. WTP was compared with ATP using Spearman's rank correlation. RESULTS: Two general and explicitly acknowledged thresholds (England/Wales, Thailand), implicit thresholds in six countries and different ICER thresholds/decision-making rules in oncology were identified. Correlation between WTP and ability-to-pay was moderate. DISCUSSION: Our overview supports country-specific discussions on WTP and on how to define value(s) within societies.
Entities:
Keywords:
cost–effectiveness thresholds; decision-making; health policy; reimbursement; technology assessment; willingness-to-pay
Authors: Ann-Kathrin Richter; Ludger Klimek; Hans F Merk; Norbert Mülleneisen; Harald Renz; Wolfgang Wehrmann; Thomas Werfel; Eckard Hamelmann; Uwe Siebert; Gaby Sroczynski; Jürgen Wasem; Janine Biermann-Stallwitz Journal: Eur J Health Econ Date: 2018-03-24
Authors: B Jahn; U Rochau; C Kurzthaler; M Hubalek; R Miksad; G Sroczynski; M Paulden; M Kluibenschädl; M Krahn; U Siebert Journal: Springerplus Date: 2015-12-01