A Systematic Review to Identify the Use of Preference Elicitation Methods in Healthcare Decision Making

Abstract

Introduction Preference elicitation methods help to increase patient-centred medical decision making (MDM) by measuring benefit and value. Preferences can be applied in decisions regarding reimbursement, including health technology assessment (HTA); market access, including benefit-risk assessment (BRA); and clinical care. These three decision contexts have different requirements for use and elicitation of preferences. Objectives This systematic review identified studies using preference elicitation methods and summarized methodological and practical characteristics within the requirements of the three contexts. Methods The search terms included those related to MDM and patient preferences. Only articles with original data from quantitative preference elicitation methods were included. Results The selected articles (n = 322) included 379 preference elicitation methods, comprising matching methods [MM] (n = 71, 18.7 %), discrete choice experiments [DCEs] (n = 96, 25.3 %), multi-criteria decision analysis (n = 12, 3.2 %) and other methods (n = 200, 52.8 %; i.e. rating scales, which provide estimates inconsistent with utility theory). Most publications of preference elicitation methods had an intended use in clinical decisions (n = 134, 40 %). Fewer preference studies had an intended use in HTA (n = 68, 20 %) or BRA (n = 12, 4 %). In clinical decisions, rating, ranking, visual analogue scales and direct choice are used most often. In HTA, DCEs and MM are both used frequently, and elicitation of preferences in BRA was limited to DCEs. Conclusion Relatively simple preference methods are often adequate in clinical decisions because they are easy to administer and have a low cognitive burden. MM and DCE fulfil the requirements of HTA and BRA but are complex for respondents. No preference elicitation methods with a low cognitive burden could adequately inform HTA and BRA decisions. Key PointsPreference elicitation methods can be used to quantify relative benefits and to value various aspects of a drug or health states.Most studies found in the current literature identify preferences for guiding clinical decisions.Fewer preference studies directly support reimbursement (health technology assessment [HTA]) or market access (benefit-risk assessment [BRA]) decisions.Clinical decisions require more patient-friendly and straightforward preference methods.Matching methods and discrete choice experiments fulfil almost all of the contexts' requirements of BRA and HTA. However, those methods can be cognitively complex for the respondents if the number of attributes is large or the attributes are difficult to understand. Marieke G. M. Weernink and Sarah I. M. Janus contributed equally to this work. Electronic supplementary material The online version of this article (

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