What Do HTA Agencies Across the Globe Need for Generating Health-Related Quality of Life Evidence? Findings From a Global Survey

Speaker(s)

Vasan Thakumar A1, Lorgelly P2, Longworth L3, Rey Ares L4, Purba F5, Golicki D6, Augustovski F7, Rand K8, Viney R9, Bansback N10, Luo N11
1National University of Singapore, Subang Jaya, 10, Malaysia, 2University of Auckland, Auckland, New Zealand, 3Arrow Health Economics, London, England, UK, 4Pfizer, Villa Adelina, B, Argentina, 5Faculty of Psychology, Padjadjaran University, West Java, Indonesia, 6Medical University of Warsaw, Warsaw, Poland, 7Institute for Clinical Effectiveness and Health Policy (IECS), CABA, Buenoa Aires, Argentina, 8Maths in Health B.V., Klimmen, Limburg, Netherlands, 9University of Technology Sydney, Sydney, NSW, Australia, 10University of British Columbia, Vancouver, BC, Canada, 11National University of Singapore, Singapore, Singapore, Singapore

Presentation Documents

OBJECTIVES: The overall study aim was to understand the practices and needs of health technology assessment (HTA) practitioners globally regarding measurement and use of health-related quality of life (HRQoL) data.

METHODS: We identified 60 countries where national HTA agencies, or bodies existed, and/or HTA was used to inform healthcare decision-making. We invited HTA practitioners in those countries to complete an online survey inquiring their views on: i) utility instruments; ii) utility elicitation methods, iii) health preference sources, iv) data quality, and v) research priorities. For questions using a Likert-type response scale, we used the mode (or median if no or multiple modes) of all responses for that country, and reported the median based on all country responses. We performed descriptive analyses of the overall sample, and examined response differences across six regions (Commonwealth, Europe, Central/Eastern Europe, Asia, Latin America, and Middle East/Africa).

RESULTS: Overall, 238 individuals from 45 countries completed the survey. The mean response number per country was 5.28 (SD: 4.45). The most frequently used utility instrument was EQ-5D. The top three most frequently used utility elicitation methods were time trade-off, visual analogue scale, and standard gamble. Health-state preferences of another country’s general public was more frequently used than local public preferences. The top data quality issue that arose was the poor matching of health-state utility data (UD) with those of cost-effectiveness models. In Asia, Europe and Latin America, the top-voted research priority was to develop utility instruments capturing health and social care impact; in the Middle East/Africa and Central/Eastern Europe, it was to make more recent UD available; in the Commonwealth, the priority was to develop instruments capturing treatment impact on carers and caregivers.

CONCLUSIONS: The survey filled important knowledge gaps within the current practices of measurement and valuation of HRQoL in HTA and preferences for new evidence.

Code

OP8

Topic

Health Technology Assessment, Organizational Practices, Patient-Centered Research

Topic Subcategory

Health State Utilities, Patient-reported Outcomes & Quality of Life Outcomes, Systems & Structure

Disease

No Additional Disease & Conditions/Specialized Treatment Areas