ArticleHealth policy and planning2025
Psychological constructs and preferences for a complementary inclusive health insurance: a hybrid choice model.
Article in Health policy and planning, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Residents' preferences for inclusive commercial supplementary medical insurance: a discrete choice experiment.Health economics review · 2026Article
- Huimin Insurance and unequal economic welfare between urban and rural areas: evidence from Chinese cities.Frontiers in public health · 2026Article
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Authors and funding
5 authors.
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Abstract
Many low- and middle-income countries are affected by catastrophic health expenditures due to overstretched public health financing, indicating need for complementary inclusive health insurance solutions. Promoting these solutions requires understanding drivers, including psychological determinants, of health insurance purchase. Yet, relevant evidence is lacking. We employed hybrid choice models to analyze discrete choice experiment data and examine preferences for Huimin Insurance, a widely diffused complementary inclusive health insurance in China. We relied on KuRunData to collect our discrete choice experiment data. We found that people who regarded themselves to be at greater health risk preferred more generous benefits, while they did not value strong government involvement in product operation, design, and publicity. Higher scheme awareness was associated with a greater propensity to purchase coverage, to be willing to pay higher premium, and to accept lower reimbursement rates. High awareness coupled with a low perception of the scheme value resulted in a preference for an expanded package covering prevention and screening services. Stronger value was attributed to the Huimin Insurance among population groups that lack access to other insurance products, such as women and rural residents. By integrating psychological constructs in the decision-making analysis, we provide new evidence to guide design and promotion of appropriate health insurance schemes, especially catastrophic diseases.
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