Preference for supplementary voluntary health insurance and heterogeneity in China: a discrete choice experiment
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Le résumé fourni par la source
Understanding the population's preferences for health insurance plays an important role in optimizing insurance scheme design and improving enrollment rate. This study aims to quantitatively investigate preference for supplementary voluntary health insurance (SVHI) from a multi-site survey and examine its heterogeneity in China. A discrete choice experiment was conducted in Shandong, Henan, and Sichuan provinces using multi-stage stratified sampling method. Five SVHI attributes were identified: premium, benefit package, deductible, reimbursement rate, and reimbursement for preexisting conditions. Choice sets were generated using a D-efficient design, grouped into two blocks randomly assigned to respondents, with each set comprising two SVHI options and an opt-out. Data were collected via face-to-face computer-assisted interviews. Mixed logit models were used to estimate preference weights, willingness-to-pay (WTP), and attribute importance scores. Preference heterogeneity was analyzed by disease-related financial risk awareness, numeracy, and health insurance knowledge, demographic, socioeconomic, and health characteristics. Of the 1326 respondents who completed the questionnaire, 1254 were included in the analysis. Reimbursement rate was the most important attribute (34.26%), followed by premium (25.06%), benefit package (17.60%), deductible (17.50%), and reimbursement for preexisting conditions (5.58%). Overall, respondents expressed the highest WTP (USD 48.50) for improving the reimbursement rate from 50% to 90%, while they showed lowest WTP (USD 8.60) for decreasing deductible from USD 2777.78 to 1388.89. Heterogeneity analysis revealed stronger enrollment preferences among respondents with risk awareness, higher health insurance knowledge, higher numeracy, higher educational attainment, higher income, and those living in urban areas. In addition, higher levels of risk awareness, insurance knowledge, numeracy, income, and education were associated with increased WTP for SVHI attributes. Preference heterogeneity by risk awareness and insurance knowledge suggests need for targeted risk information communication and education campaign to promote SVHI uptake and diverse insurance design tailored to socioeconomic differences in preferences for attributes.
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Le contrôle bibliographique ouvert
DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- Preference for supplementary voluntary health insurance and heterogeneity in China: a discrete choice experiment
- Date Crossref
- 29/06/2026
- Éditeur
- Oxford University Press (OUP)
- Type
- journal-article
Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.
Où se fait cette recherche
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Shandong University National Institute of Health Data Science of China pays non établi dans la noticeUniversité ou école supérieure
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The George Institute for Global Health pays non établi dans la noticeStructure de recherche
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Anhui Medical University pays non établi dans la noticeUniversité ou école supérieure
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Western Sydney University Translational Health Research Institute pays non établi dans la noticeUniversité ou école supérieure
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Shandong Management University pays non établi dans la noticeUniversité ou école supérieure
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University Town of Shenzhen pays non établi dans la noticeUniversité ou école supérieure
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Tsinghua–Berkeley Shenzhen Institute pays non établi dans la noticeStructure de recherche
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School of Public Health Department of Social Medicine and Health Management pays non établi dans la noticeUniversité ou école supérieure
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Faculty of Medicine and Health The George Institute for Global Health pays non établi dans la noticeUniversité ou école supérieure
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School of Health Management pays non établi dans la noticeUniversité ou école supérieure
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School of Health Sciences pays non établi dans la noticeUniversité ou école supérieure
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Tsinghua University Institute for Hospital Management pays non établi dans la noticeUniversité ou école supérieure
National Institute of Health Data Science of China — Shandong University, The George Institute for Global Health et Anhui Medical University, avec 9 autres affiliations.
Une affiliation ne permet pas de déduire la nationalité d’un auteur.