Construction and validation of a revised satisfaction index model for the Chinese urban and rural resident-based basic medical insurance scheme

Autor: Wenwei Cheng, Shiwen Wang, Xiaofang Liu, Yanyan Wu, Jin Cheng, Weichu Sun, Xiaofang Yan, Qi Wang, Liai Peng, Xiaoli Liu, Tingting Sha, Jingcheng Shi, Fang Yang
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: BMC Medical Informatics and Decision Making, Vol 22, Iss 1, Pp 1-15 (2022)
Druh dokumentu: article
ISSN: 1472-6947
DOI: 10.1186/s12911-022-02002-5
Popis: Abstract Background Quality is the most important factor in satisfaction. However, the existing satisfaction index model of urban and rural resident-based basic medical insurance scheme (SIM_URRBMI) lacks the segmentation of perceived quality elements, it couldn’t provide a reference for quality improvement and satisfaction promotion. This study aims to construct a revised SIM_URRBMI that can accurately and detailly measure perceived quality and provide feasible and scientific suggestions for improving the satisfaction of urban and rural residents' basic medical insurance scheme (URRBMI) in China. Methods Based on the theoretical framework of the American Customer Satisfaction Index, the elements of perceived quality were refined through literature review and expert consultation, and a pool of alternative measurement variables was formed. A three-stage randomized stratified cluster sampling was adopted. The main decision makers of URRBMI in the families of primary school students in 8 primary schools in Changsha were selected. Both the classic test theory and the item response theory were used for measurement variables selection. The reliability and validity of the model were tested by partial least squares (PLS)-related methods. Results A total of 1909 respondents who had URRBMI for their children were investigated. The SIM_URRBMI1.0 consists of 11 latent variables and 28 measurement variables with good reliability and validity. Among the three explanatory variables of public satisfaction, perceived quality had the largest total effect (path coefficient) (0.737). The variable with the greatest effect among the five first-order latent variables on perceived quality was the quality of the medical insurance policy (0.472). Conclusions The SIM_URRBMI1.0 consists of 28 measurement variables and 11 latent variables. It is a reliable, valid, and standard satisfaction measurement tool for URRBMI with good prediction ability for public satisfaction. In addition, the model provides an accurate evaluation of the perceived quality, which will greatly help with performance improvement diagnosis. The most critical aspects of satisfaction improvement are optimizing the scope and proportion of reimbursement as well as setting appropriate level of deductible and capitation of URRBMI.
Databáze: Directory of Open Access Journals
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