ArticleBMJ open2020
Patients' preferences for health insurance coverage of new technologies for treating chronic diseases in China: a discrete choice experiment.
Article in BMJ open, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it, 8 citations in OpenAlex.
- The Evolving Landscape of Discrete Choice Experiments in Health Economics: A Systematic Review.PharmacoEconomics · 2025Pooled it
- Preferences for public health insurance coverage of new anticancer drugs: a discrete choice experiment among non-small cell lung cancer patients in China.BMC public health · 2025Article
- Assessing patient information needs for new antidiabetic medications to inform shared decision-making: A best-worst scaling experiment in China.Health expectations : an international journal of public participation in health care and health policy · 2024Article
- Factors affecting the willingness of patients with type 2 diabetes to use digital disease management applications: a cross-sectional study.Frontiers in public health · 2023Article
- The Determinants of User Acceptance of Mobile Medical Platforms: An Investigation Integrating the TPB, TAM, and Patient-Centered Factors.International journal of environmental research and public health · 2022Article
- Healthcare preferences of the general Chinese population in the hierarchical medical system: A discrete choice experiment.Frontiers in public health · 2022Article
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Authors and funding
6 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesOur study aimed to inform insurance decision-making in China by investigating patients' preferences for insurance coverage of new technologies for treating chronic diseases.
designWe identified six attributes of new medical technologies for treating chronic diseases and used Bayesian-efficient design to generate choice sets for a discrete choice experiment (DCE). After conducting the DCE, we analysed the data by mixed logit regression to examine patient-reported preferences for each attribute.
settingThe DCE was conducted with patients in six tertiary hospitals from four cities in Jiangsu province.
participantsPatients aged 18 years or older with a history of diabetes or hypertension and taking medications regularly for more than 1 year were recruited (n=408).
resultsThe technology attributes regarding expected gains in health outcomes from the treatment, high likelihood of effective treatment and low incidence of serious adverse events were significant, positive predictors of choice by the study patients (p<0.01). The out-of-pocket cost was a significant, negative attribute for the entire study sample (β = -0.258, p<0.01) and for the patients with Urban-Rural Residents Basic Medical Insurance (URRBMI) (β = -0.511, p<0.01), but not for all the patients with Urban Employees Basic Medical Insurance (UEBMI) (β = -0.071, p>0.05). The severity of target disease was valued by patients with lower EQ-5D-5L index value as well as URRBMI enrollees.
conclusionsPatients highly valued the health benefits and risks of new technologies, which were closely linked to their feelings of disease and perceptions of health-related quality of life. However, there existed heterogeneity in preferences between URRBMI and UEBMI patients. Further efforts should be made to reduce the gap between insurance schemes and make safe and cost-effective new technologies as a priority for health insurance reimbursement.
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