Intelligent health management is a crucial countermeasure to solving public health problems. By utilizing high-quality medical resources from a Third-Grade First Class Hospital, this study is able to solve prominent health problems in China, and it also creates medical knowledge bases and model bases. By taking advantage of intelligent additional features including self-testing health, risk estimation, health education, assessment, intelligent consultation, comprehensive intervention, and contracted doctor services, 40 statutory infectious diseases are monitored and warned early, and 260 common diseases are managed intelligently. The insured population can access health assessment, intelligent consultation, comprehensive intervention, and contracted doctor services through this research platform. The service management process is completed by these functions, which include health assessments, health classification management, personalized health plans, and health intervention to improve health status, decrease disease incidence rates, and improve health levels.
Under the background of the promotions concept change from "disease-centered" to "health-centered", Zhejiang province takes the lead in building a future community health scenario for the whole population and the whole life cycle, providing a "Zhejiang model" for the comprehensive reform of grassroots health care. It is of great theoretical significance and practical value to construct a set of scientific and effective service quality evaluation index system for future community health scene.
The purpose of this study is to construct a service quality evaluation index system for future community health scenes in Zhejiang province, aiming to provide a reference for improving the capabilities and quality of community health services and advancing the achievement of public health objectives.
Employing the SERVQUAL theory model, an initial indicators pool was developed through policy analysis, literature review, and field research. From October to December 2023, a two-round Delphi expert consultation method was used to refine the indicators, and the Analytic Hierarchy Process (AHP) was applied to determine the weights and composite weights of each indicator.
A total of 17 experts participated in both rounds of consultation, among which 12 (70.6%) hold senior titles; 15 (88.2%) have 10 or more years of work experience; and there are 5 (29.4%) managers and medical staff from future community. The positivity level of the experts in both rounds was consistently rated at 1.0, with authority coefficients of 0.862 and 0.842, respectively, and the degree of expert consensus increased round by round. The final constructed indicator system includes 5 primary indicators, 13 secondary indicators, and 36 tertiary indicators, and the weights for the primary indicators—tangibles, reliability, assurance, responsiveness, and empathy were 0.168, 0.180, 0.240, 0.174 and 0.238, respectively. For the secondary indicators, the weights for venue facilities, digital equipment, Service Provision, Health Monitoring, Service Efficiency, Service Accessibility, Crisis Prevention and Emergency Rescue Capability, Professional Skills, Activity Organization, Smart Platform Maintenance, Service Attitude and Emotional Support, Service Effectiveness and Personalized Services were 0.399, 0.601, 0.672, 0.328, 0.487, 0.171, 0.342, 0.410, 0.416, 0.174, 0.284, 0.323 and 0.393 respectively.
The indicator system constructed in this study, which is an effective tool for conducting evaluation of future community health scenario, is scientifically reliable and exhibits a degree of systematization, innovation, operability and practical value. It is hoped to provide a reference to fomulate relevant policies and targeted improvement strategies.
