Residents' Preferences for Inclusive Commercial Health Insurance: A Comparative Study of Discrete Choice Experiment...

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.

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.

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.

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.