Central South University Reports Findings in Medical Informatics (Construction and validation of a revised satisfaction index model for the Chinese urban and rural resident-based basic medical insurance scheme): Health Information Technology – Medical Informatics

2022 OCT 13 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- New research on Health Information Technology - Medical Informatics is the subject of a report. According to news reporting originating from Hunan, People’s Republic of China, by NewsRx correspondents, research stated, “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.”

Our news editors obtained a quote from the research from Central South University, “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. 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. 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). 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.”

According to the news editors, the research concluded: “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.”

For more information on this research see: Construction and validation of a revised satisfaction index model for the Chinese urban and rural resident-based basic medical insurance scheme. BMC Medical Informatics and Decision Making, 2022;22(1):259. BMC Medical Informatics and Decision Making can be contacted at: Bmc, Campus, 4 Crinan St, London N1 9XW, England. (BioMed Central - http://www.biomedcentral.com/; BMC Medical Informatics and Decision Making - http://www.biomedcentral.com/bmcmedinformdecismak/)

The news editors report that additional information may be obtained by contacting Shiwen Wang, Dept. of Epidemiology and Medical Statistics, Xiangya School of Public Health, Central South University, Xiangya Road 110, Changsha, 410078, Hunan, People’s Republic of China. Additional authors for this research include Wenwei Cheng, Xiaofang Liu, Yanyan Wu, Jin Cheng, Weichu Sun, Xiaofang Yan, Qi Wang, Liai Peng, Xiaoli Liu, Tingting Sha, Jingcheng Shi and Fang Yang.

The direct object identifier (DOI) for that additional information is: https://doi.org/10.1186/s12911-022-02002-5. This DOI is a link to an online electronic document that is either free or for purchase, and can be your direct source for a journal article and its citation.

Publisher contact information for the journal BMC Medical Informatics and Decision Making is: Bmc, Campus, 4 Crinan St, London N1 9XW, England.

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