Matthew H R Little1, Peter Reitmeir2, Annette Peters3, Reiner Leidl4. 1. Institute of Health and Society, Newcastle University, The Baddiley-Clark Building, Newcastle upon Tyne, UK; Institute for Health Economics and Health Care Management, Helmholtz Zentrum München, Neuherberg, Germany. Electronic address: mhrlittle@gmail.com. 2. Institute for Health Economics and Health Care Management, Helmholtz Zentrum München, Neuherberg, Germany. 3. Institute for Epidemiology II, Helmholtz Zentrum München, Neuherberg, Germany. 4. Institute for Health Economics and Health Care Management, Helmholtz Zentrum München, Neuherberg, Germany; Munich Center of Health Sciences, Ludwig-Maximilians-University, Munich, Germany.
Abstract
BACKGROUND: Health states can be valued by those who currently experience a health state (experienced health states [EHS]) or by the general public, who value a set of given health states (GHS) described to them. There has been debate over which method is more appropriate when making resource allocation decisions. OBJECTIVE: This article informs this debate by assessing whether differences between these methods have an effect on the mean EQ-5D-3L tariff scores of different patient groups. METHODS: The European tariff based on GHS valuations was compared with a German EHS tariff. Comparison was made in the context of EQ-5D-3L health states describing a number of diagnosed chronic diseases (stroke, diabetes, myocardial infarction, and cancer) taken from the Cooperative Health Research in the Augsburg Region population surveys. Comparison was made of both the difference in weighting of the dimensions of the EQ-5D-3L and differences in mean tariff scores for patient groups. RESULTS: Weighting of the dimensions of the EQ-5D-3L were found to be systematically different. The EHS tariff gave significantly lower mean scores for most, but not all, patient groups despite tariff scores being lower for 213 of 243 EQ-5D-3L health states using the GHS tariff. Differences were found to vary between groups, with the largest change in difference being 5.45 in the multiple stoke group. CONCLUSIONS: The two tariffs have systematic differences that in certain patient groups could drive the results of an economic evaluation. Therefore, the choice as to which is used may be critical when making resource allocation decisions.
BACKGROUND: Health states can be valued by those who currently experience a health state (experienced health states [EHS]) or by the general public, who value a set of given health states (GHS) described to them. There has been debate over which method is more appropriate when making resource allocation decisions. OBJECTIVE: This article informs this debate by assessing whether differences between these methods have an effect on the mean EQ-5D-3L tariff scores of different patient groups. METHODS: The European tariff based on GHS valuations was compared with a German EHS tariff. Comparison was made in the context of EQ-5D-3L health states describing a number of diagnosed chronic diseases (stroke, diabetes, myocardial infarction, and cancer) taken from the Cooperative Health Research in the Augsburg Region population surveys. Comparison was made of both the difference in weighting of the dimensions of the EQ-5D-3L and differences in mean tariff scores for patient groups. RESULTS: Weighting of the dimensions of the EQ-5D-3L were found to be systematically different. The EHS tariff gave significantly lower mean scores for most, but not all, patient groups despite tariff scores being lower for 213 of 243 EQ-5D-3L health states using the GHS tariff. Differences were found to vary between groups, with the largest change in difference being 5.45 in the multiple stoke group. CONCLUSIONS: The two tariffs have systematic differences that in certain patient groups could drive the results of an economic evaluation. Therefore, the choice as to which is used may be critical when making resource allocation decisions.
Authors: Fatima Al Sayah; Nick Bansback; Stirling Bryan; Arto Ohinmaa; Lise Poissant; Eleanor Pullenayegum; Feng Xie; Jeffrey A Johnson Journal: Qual Life Res Date: 2015-12-10 Impact factor: 4.147
Authors: Szilárd Nemes; Kristina Burström; Niklas Zethraeus; Ted Eneqvist; Göran Garellick; Ola Rolfson Journal: Qual Life Res Date: 2015-06-03 Impact factor: 4.147
Authors: Y Jo; I Gomes; H Shin; A Tucker; L G Ngwira; R E Chaisson; E L Corbett; D W Dowdy Journal: Int J Tuberc Lung Dis Date: 2020-11-01 Impact factor: 2.373
Authors: Reiner Leidl; Bernd Schweikert; Harry Hahmann; Juergen M Steinacker; Peter Reitmeir Journal: Health Qual Life Outcomes Date: 2016-03-22 Impact factor: 3.186