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Published on: December 11, 2016
What Drives Public Preference for Rare Drugs Coverage in China? Insights From a Multi-Center Discrete Choice
Ya'nan Wu1,2,3,4, Jingdan Chen1,2,3,4, Jiachen Shao1,2,3,4
1Department of Social Medicine and Health Management, Cheeloo College of Medicine, School of Public Health, Shandong University, Jinan, China.
Introduction:
Reimbursement decisions for orphan drugs are complex, as conventional cost-effectiveness frameworks may not fully capture broader societal values. To investigate public preferences regarding the inclusion of rare disease drugs in China's Basic Medical Insurance (BMI) using a multi-center discrete choice experiment.
Methods:
From July to September 2024, a face-to-face, filed-based discrete choice experiment (DCE) was conducted across four regions in China. Using non probability sampling technique which is known as Quota sampling, participants evaluated drug profiles varying in six attributes. Mixed logit model and latent class model were used for analysis. Relative importance, willingness to pay (WTP), scenario analysis and preference heterogeneity were estimated.
Results:
Of the 761 respondents retained after initial data cleaning, 622 passed the internal consistency check and were included in the final analysis. Most participants were urban residents (62.7%), employed (66.6%), and covered by urban and rural resident basic medical insurance (BMI) (57.7%). The general public preferred including orphan drugs in BMI coverage when treatments provided greater health gains, targeted diseases with moderate untreated life expectancy, and lacked existing reimbursed alternatives. In contrast, poorer untreated quality of life and larger increases in BMI financing reduced utility. Health gains were the most important, followed by increases in BMI financing, untreated quality of life, existing BMI coverage, and untreated life expectancy. Annual WTP was ¥1.225 per capita for quality-adjusted life years (QALY) gains (0.01-4), with lower WTP observed among respondents facing poorer untreated quality of life. Scenario analysis showed that 78.5% would support reimbursement for drugs providing maximal health gains (0.01-4). Preference heterogeneity was observed across age, sex, education, household income, insurance type, and urban-rural residence. Latent class analysis identified two subgroups. The "life-saving group" (23%) showed strong preferences for greater disease severity and larger health gains, whereas the "pragmatist group" (77%) demonstrated relatively flatter preferences and negative utility associated with declining untreated life expectancy.
Conclusion:
While health gains drive preferences, the public also values equity, disease severity and affordability. Policymakers must integrate these multidimensional social values to ensure legitimacy and fairness in allocating finite resources for rare diseases.
Patient Or Public Contribution:
Members of the public were involved in the development of the DCE. In the attribute development phase, members of the public participated in a pilot study to help ensure the clarity and comprehensibility of attribute descriptions and levels. And their feedback informed revisions to the questionnaire. In the main study, members of the public participated as respondents, providing data on societal preferences for orphan drug reimbursement.
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