Evidence map›Paper›PMID 37480281›Full record

ArticleMedical decision making : an international journal of the Society for Medical Decision Making2023

Evaluation of EuroQol Valuation Technology (EQ-VT) Designs to Generate National Value Sets: Learnings from the Development of an EQ-5D Value Set for India Using an Extended Design (DEVINE) Study.

Gaurav Jyani, Zhihao Yang, Atul Sharma, Aarti Goyal, Elly Stolk, Fredrick Dermawan Purba, Sandeep Grover, Manmeet Kaur, Shankar Prinja

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Article in Medical decision making : an international journal of the Society for Medical Decision Making, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

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4citing papers in PubMed
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4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Gaurav JyaniPostgraduate Institute of Medical Education and Research, Chandigarh, India.ORCID 0000-0003-3787-2446
Zhihao YangGuizhou Medical University, Guiyang, People's Republic of China.ORCID 0000-0001-5468-0847
Atul SharmaPostgraduate Institute of Medical Education and Research, Chandigarh, India.
Aarti GoyalPostgraduate Institute of Medical Education and Research, Chandigarh, India.
Elly StolkEuroQol Research Foundation, Rotterdam, South Holland, the Netherlands.ORCID 0000-0001-5968-0416
Fredrick Dermawan PurbaDepartment of Developmental Psychology, Faculty of Psychology, Universitas Padjadjaran, Bandung, Jawa Barat, Indonesia.
Sandeep GroverPostgraduate Institute of Medical Education and Research, Chandigarh, India.
Manmeet KaurPostgraduate Institute of Medical Education and Research, Chandigarh, India.
Shankar PrinjaPostgraduate Institute of Medical Education and Research, Chandigarh, India.ORCID 0000-0001-7719-6986

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionCountries develop their EQ-5D-5L value sets using the EuroQol Valuation Technology (EQ-VT) protocol. This study aims to assess if extension in the conventional EQ-VT design can lead to development of value sets with improved precision.

methodsA cross-sectional survey was undertaken in a representative sample of 3,548 adult respondents, selected from 5 different states of India using a multistage stratified random sampling technique. A novel extended EQ-VT design was created that included 18 blocks of 10 health states, comprising 150 unique health states and 135 observations per health state. In addition to the standard EQ-VT design, which is based on 86 health states and 100 observations per health state, 3 extended designs were assessed for their predictive performance. The extended designs were created by 1) increasing the number of observations per health state in the design, 2) increasing the number of health states in the design, and 3) implementing both 1) and 2) at the same time. Subsamples of the data set were created for separate designs. The root mean squared error (RMSE) and mean absolute error (MAE) were used to measure the predictive accuracy of the conventional and extended designs.

resultsThe average RMSE and MAE for the standard EQ-VT design were 0.055 and 0.041, respectively, for the 150 health states. All 3 types of design extensions showed lower RMSE and MAE values as compared with the standard design and hence yielded better predictive performance. RMSE and MAE were lowest (0.051 and 0.039, respectively) for the designs that use a greater number of health states. Extending the design with inclusion of more health states was shown to improve the predictive performance even when the sample size was fixed at 1,000.

conclusionAlthough the standard EQ-VT design performs well, its prediction accuracy can be further improved by extending its design. The addition of more health states in EQ-VT is more beneficial than increasing the number of observations per health state. HIGHLIGHTS: The EQ-5D-5L value sets are developed using the standardized EuroQol Valuation Technology (EQ-VT) protocol. This is the first study to empirically assess how much can be gained from extending the standard EQ-VT design in terms of sample size and/or health states. It not only presents useful insights into the performance of the standard design of the EQ-VT but also tests the potential extensions in the standard EQ-VT design in terms of increasing the health states to be directly valued as well as the number of observations recorded to predict the utility value of each of these health states.The study demonstrates that the standard EQ-VT design performs good, and an extension in the design of the standard EQ-VT can lead to further improvement in its performance. The addition of more health states in EQ-VT is more beneficial than increasing the number of observations per health state. Extending the design with inclusion of more health states marginally improves the predictive performance even when the sample size was fixed at 1,000.The findings of the study will streamline the systematic process for generating precise EQ-5D-5L value sets, thus facilitating the conduct of credible, transparent, and robust outcome valuation in health technology assessments.

Indexed as

Health StatusQuality of LifeAdultCross-Sectional StudiesHumansIndiaSurveys and QuestionnairesTechnologyEQ-5Dextended designhealth technology assessmentmodel predictionperformancepredictive accuracytime tradeoffvaluationvalue set

Identifiers

PMID37480281
PMCPMC10422850

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.