Valuation of EQ-5D Health States for Adults in Low-, Lower-Middle, and Upper-Middle-Income Countries: A Systematic Review

Abstract

Objectives

Preference-based measurement of health-related quality of life is crucial for informing resource allocation decisions, with the EQ-5D instrument widely used as a measure of health-related quality of life. Although country-specific value sets are well established in many high-income countries, current summarized evidence from valuation studies in low- and middle-income countries (LMICs) remains limited. This review systematically identified EQ-5D valuation studies in LMICs, summarized methodologies and scoring algorithms by country type, and highlighted key challenges.

Methods

A systematic search was undertaken across 7 academic databases and the EuroQol website. Two independent reviewers screened titles and abstracts and performed full-text reviews and data extraction. Reporting followed Checklist Reporting Valuation Studies of Multi-Attribute Utility-Based Instruments for quality assessment. The synthesis included study characteristics, methodologies, and summarized scoring algorithms from the best-performing models, highlighting variations across countries.

Results

Through screening 9378 studies, 35 studies from 22 LMICs were included. Of these, 20 (58%) were from upper-middle-income countries, whereas low-middle and low-income countries accounted for 13 (37%) and 2 (6%) studies, respectively. Eighteen (51%) studies reported EQ-5D-5L valuations. Sample sizes ranged from 148 to 5503, with the time trade-off method being predominant. Scoring algorithms showed no significant variation between upper-middle- and low-middle-income countries, except for the pain/discomfort dimension in EQ-5D-5L. Mobility was the most reported utility decrement among studies.

Conclusions

There is a growing trend in developing country-specific value sets in LMICs. Contextually relevant designs and adequate pilot studies could enhance the accuracy of value sets in culturally diverse settings, particularly where severe health states are commonly reported.