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已发表论文
中国黑龙江省居民对包容性商业健康保险的偏好：基于离散选择实验和最佳-最差尺度法的比较研究
Authors Jia Y, Zhu X , Liu X, Gu W, Cao Y , Li H , Xu L, Leng L, Yu H , Zhai T, Huang W
Received 6 August 2025
Accepted for publication 30 October 2025
Published 6 November 2025 Volume 2025:19 Pages 3453—3467
DOI https://doi.org/10.2147/PPA.S558869
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Dr Ramón Morillo-Verdugo
Yanni Jia,1,* Xiaoying Zhu,2,3,* Xianna Liu,4,* Wen Gu,1 Yiyin Cao,1 Haofei Li,1 Lijun Xu,1 Lei Leng,1 Hongjuan Yu,5 Tiemin Zhai,6 Weidong Huang1
1School of Health Management, Harbin Medical University, Harbin, People’s Republic of China; 2School of Elderly Care Services and Management, Nanjing University of Chinese Medicine, Nanjing, People’s Republic of China; 3Nossal Institute for Global Health, School of Population and Global Health, The University of Melbourne, Melbourne, Australia; 4Office of the President, The Second Affiliated Hospital of Harbin Medical University, Harbin, People’s Republic of China; 5Department of Hematology, The First Affiliated Hospital of Harbin Medical University, Harbin, People’s Republic of China; 6Department of Health Economics and Security Research, China National Health Development Research Center, Beijing, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Weidong Huang, Email huangweidong@hrbmu.edu.cn Hongjuan Yu, Email yuhongjuan2008@163.com
Objective: The primary objective of this study is to evaluate residents’ preferences for inclusive commercial health insurance to inform policy optimization, as well as to assess the applicability of the Best-Worst Scaling (BWS) and Discrete Choice Experiments (DCE) methods.
Methods: A face-to-face survey incorporating both DCE and BWS tasks was conducted with residents recruited in Heilongjiang Province, China. The attributes include insurance liability, premium, reimbursement ratio, deductible, government involvement, and payment methods. Data from BWS and DCE tasks were analyzed using mixed logit and conditional logit models to estimate preference weights for each attribute level. The optimal measurement method was evaluated based on internal consistency, validity, and acceptability.
Results: A total of 415 respondents were included in the analysis. Comparative analysis of DCE and the BWS methodologies revealed a pronounced preference among respondents for a 90% reimbursement rate and a streamlined, one-stop claims settlement process. However, notable discrepancies emerged in the ranking of preferences for other attributes. Further analysis indicated a correlation between the preference weights derived from the two methods, although the concordance was only moderate. Additionally, the DCE method demonstrated superior validity and reliability compared to BWS-2.
Conclusion: This study reveals residents’ preferences for inclusive commercial health insurance (ICHI), providing valuable insights for optimizing product design and informing policy development. It also provides the first comparative analysis of DCE and BWS methods in the context of ICHI, which validates the superior applicability of DCE for health insurance, offering new perspectives and methodological guidance for future studies.
Keywords: preferences, discrete choice experiment, best-worst scaling, inclusive commercial health insurance
1School of Health Management, Harbin Medical University, Harbin, People’s Republic of China; 2School of Elderly Care Services and Management, Nanjing University of Chinese Medicine, Nanjing, People’s Republic of China; 3Nossal Institute for Global Health, School of Population and Global Health, The University of Melbourne, Melbourne, Australia; 4Office of the President, The Second Affiliated Hospital of Harbin Medical University, Harbin, People’s Republic of China; 5Department of Hematology, The First Affiliated Hospital of Harbin Medical University, Harbin, People’s Republic of China; 6Department of Health Economics and Security Research, China National Health Development Research Center, Beijing, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Weidong Huang, Email huangweidong@hrbmu.edu.cn Hongjuan Yu, Email yuhongjuan2008@163.com
Objective: The primary objective of this study is to evaluate residents’ preferences for inclusive commercial health insurance to inform policy optimization, as well as to assess the applicability of the Best-Worst Scaling (BWS) and Discrete Choice Experiments (DCE) methods.
Methods: A face-to-face survey incorporating both DCE and BWS tasks was conducted with residents recruited in Heilongjiang Province, China. The attributes include insurance liability, premium, reimbursement ratio, deductible, government involvement, and payment methods. Data from BWS and DCE tasks were analyzed using mixed logit and conditional logit models to estimate preference weights for each attribute level. The optimal measurement method was evaluated based on internal consistency, validity, and acceptability.
Results: A total of 415 respondents were included in the analysis. Comparative analysis of DCE and the BWS methodologies revealed a pronounced preference among respondents for a 90% reimbursement rate and a streamlined, one-stop claims settlement process. However, notable discrepancies emerged in the ranking of preferences for other attributes. Further analysis indicated a correlation between the preference weights derived from the two methods, although the concordance was only moderate. Additionally, the DCE method demonstrated superior validity and reliability compared to BWS-2.
Conclusion: This study reveals residents’ preferences for inclusive commercial health insurance (ICHI), providing valuable insights for optimizing product design and informing policy development. It also provides the first comparative analysis of DCE and BWS methods in the context of ICHI, which validates the superior applicability of DCE for health insurance, offering new perspectives and methodological guidance for future studies.
Keywords: preferences, discrete choice experiment, best-worst scaling, inclusive commercial health insurance