Criteria for item selection for a preference-based measure for use in economic evaluation
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COMMENTARY
Criteria for item selection for a preference-based measure for use in economic evaluation Tessa Peasgood1,2 · Clara Mukuria1 · Jill Carlton1 · Janice Connell1 · John Brazier1 Accepted: 18 November 2020 © The Author(s) 2020
Abstract Preference-based measures allow patients to report their level of health, and the responses are then scored using preference weights from a representative general population sample for use in cost utility analysis. The development process of new preference-based measures should ensure that valid items are selected to reflect the constructs of interest included in the measure and that are suitable for use in preference-elicitation exercises. Existing criteria on patient-reported outcome measures (PROMs) development were reviewed, and additional considerations were taken into account in order to generate criteria to support development of new preference-based measures. Criteria covering 22 different aspects related to item selection for preference-based measures are presented. These include criteria related to how items are phrased to ensure accurate completion, the coverage of items in terms of range of domains as well as focus on current outcomes and whether items are suitable for valuation. The criteria are aimed at supporting the development of new preference-based measures with discussion to ensure that even where there is conflict between criteria, issues have been considered at the item selection stage. This would minimize problems at valuation stage by harmonizing established criteria and expanding lists to reflect the unique characteristics of preference-based measures. Keywords PROMs · Item selection · Question selection · Preference-based measures · Quality of life · Utility
Background In the context of health technology assessment (HTA), reimbursement agencies such as the UK’s National Institute of Health and Care Excellence (NICE) recommend the use of quality-adjusted life years (QALYs) as the outcome measure [1]. QALYs combine length of life with health-related quality of life (HRQoL). The HRQoL score here is based on preferences which are anchored on a scale of dead (0) to full health or full health-related quality of life (1). These quality adjustment values are based on individuals’ preferences for different health states using preference-elicitation or valuation techniques such as time trade-off (TTO) or discrete choice experiments (DCE) [2] which aim to measure how good respondents think it would be to live hypothetical * Tessa Peasgood [email protected] 1
School of Health and Related Research, University of Sheffield, Sheffield, UK
Melbourne School of Population and Global Health, University of Melbourne, Melbourne, VIC, Australia
2
lives. Although these quality adjustment values can be generated for each individual study, this would be costly and time consuming. Preference-based measures [2] have been developed to allow patients to report their level of health, and the measure is then scored using preference weights from a represe
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