Inger M Janssen1,2, Ansgar Gerhardus3, Milly A Schröer-Günther4, Fülöp Scheibler4. 1. Department of Epidemiology & International Public Health, University of Bielefeld, Bielefeld, Germany. 2. Department of Health Information, Institute for Quality and Efficiency in Healthcare (IQWiG), Köln, Germany. 3. Department of Health Services Research, Institute for Public Health and Nursing Science, University of Bremen, Bremen, Germany. 4. Department of Non-Drug Interventions, Institute for Quality and Efficiency in Healthcare (IQWiG), Köln, Germany.
Abstract
BACKGROUND: Evidence synthesis has seen major methodological advances in reducing uncertainty and estimating the sizes of the effects. Much less is known about how to assess the relative value of different outcomes. OBJECTIVE: To identify studies that assessed preferences for outcomes in health conditions. SEARCH STRATEGY: we searched MEDLINE, EMBASE, PsycINFO and the Cochrane Library in February 2014. INCLUSION CRITERIA: eligible studies investigated preferences of patients, family members, the general population or healthcare professionals for health outcomes. The intention of this review was to include studies which focus on theoretical alternatives; studies which assessed preferences for distinct treatments were excluded. DATA EXTRACTION: study characteristics as study objective, health condition, participants, elicitation method, and outcomes assessed in the study were extracted. MAIN RESULTS: One hundred and twenty-four studies were identified and categorized into four groups: (1) multi criteria decision analysis (MCDA) (n = 71), (2) rating or ranking (n = 25), (3) utility eliciting (n = 5) and (4) studies comparing different methods (n = 23). The number of outcomes assessed by method group varied. The comparison of different methods or subgroups within one study often resulted in different hierarchies of outcomes. CONCLUSIONS: A dominant method most suitable for application in evidence syntheses was not identified. As preferences of patients differ from those of other stakeholders (especially medical professionals), the choice of the group to be questioned is consequential. Further research needs to focus on validity and applicability of the identified methods.
BACKGROUND: Evidence synthesis has seen major methodological advances in reducing uncertainty and estimating the sizes of the effects. Much less is known about how to assess the relative value of different outcomes. OBJECTIVE: To identify studies that assessed preferences for outcomes in health conditions. SEARCH STRATEGY: we searched MEDLINE, EMBASE, PsycINFO and the Cochrane Library in February 2014. INCLUSION CRITERIA: eligible studies investigated preferences of patients, family members, the general population or healthcare professionals for health outcomes. The intention of this review was to include studies which focus on theoretical alternatives; studies which assessed preferences for distinct treatments were excluded. DATA EXTRACTION: study characteristics as study objective, health condition, participants, elicitation method, and outcomes assessed in the study were extracted. MAIN RESULTS: One hundred and twenty-four studies were identified and categorized into four groups: (1) multi criteria decision analysis (MCDA) (n = 71), (2) rating or ranking (n = 25), (3) utility eliciting (n = 5) and (4) studies comparing different methods (n = 23). The number of outcomes assessed by method group varied. The comparison of different methods or subgroups within one study often resulted in different hierarchies of outcomes. CONCLUSIONS: A dominant method most suitable for application in evidence syntheses was not identified. As preferences of patients differ from those of other stakeholders (especially medical professionals), the choice of the group to be questioned is consequential. Further research needs to focus on validity and applicability of the identified methods.
Authors: L A Merlino; I Bagchi; T N Taylor; P Utrie; E Chrischilles; W Sumner; A Mudano; K G Saag Journal: Med Decis Making Date: 2001 Mar-Apr Impact factor: 2.583
Authors: A F Mohamed; J Zhang; F R Johnson; I Duprat Lomon; E Malvolti; R Townsend; C J Ostgren; K G Parhofer Journal: Diabetes Metab Date: 2013-07-20 Impact factor: 6.041
Authors: Marjan J M Hummel; Fabian Volz; Jeannette G van Manen; Marion Danner; Charalabos-Markos Dintsios; Maarten J Ijzerman; Andreas Gerber Journal: Patient Date: 2012 Impact factor: 3.883
Authors: Robert J Volk; Scott B Cantor; Alvah R Cass; Stephen J Spann; Susan C Weller; Murray D Krahn Journal: J Gen Intern Med Date: 2004-04 Impact factor: 5.128
Authors: Arwen H Pieterse; Frank Berkers; Monique C M Baas-Thijssen; Corrie A M Marijnen; Anne M Stiggelbout Journal: Patient Educ Couns Date: 2009-07-05
Authors: John Fp Bridges; Norah L Crossnohere; Anne L Schuster; Judith A Miller; Carolyn Pastorini; Rebecca A Aslakson Journal: Patient Prefer Adherence Date: 2018-02-08 Impact factor: 2.711