| The proposal of hierarchical health care delivery system aims to allocate medical resources reasonably,promote the fairness of basic medical and health services,and improve the overall efficiency and benefits of China's medical service system.The clinical application of smart healthcare services is an important means to solve the problem of insufficient and uneven distribution of high-quality medical resources in China at this stage,and it is also an effective way to help the implementation of hierarchical health care delivery system.However,at present,there are a large number of potential factors that may lead to the risk of medical errors,such as the difficulty in ensuring the quality of basic data used for development,algorithm bias and "black box" process,lack of regulatory system,etc.,leading to poor user recognition and low adoption rates in the promotion process of smart healthcare services.Existing research focuses on issues such as the construction of smart healthcare service systems,technology improvement and optimization,and privacy ethics protection strategies.There is still a large research gap on the user adoption of smart healthcare services.Theoretical and practical fields urgently need relevant research for scientific explanation and guidance,so as to promote the diffusion and development of smart healthcare services.Based on summary of the current situation of medical services industry and existing domestic and foreign studies,this dissertation conducts research on the service modes and user adoption of smart healthcare under the background of hierarchical health care delivery system.Three smart healthcare service modes: platform-based mode,productbased mode,and resource-integrated mode are first analyzed.The key influencing factors of user adoption are then identified from the perspective of patients,doctors and hospitals respectively.The patients' adoption model of platform-based smart healthcare services,the doctors' adoption model of product-based smart healthcare services,and the hospitals' adoption model of resource-integrated smart healthcare services are constructed.Research data is collected from network crawling,questionnaire,and expert group.Empirical analyses are carried out by using econometric equation,structural equation model,and interpretative structural modeling.Combined with the development status of smart healthcare services and research conclusions,this dissertation further discusses countermeasures and suggestions to promote the development of smart healthcare services in three levels of government,industry and market.The specific research contents and innovations of this dissertation are as follows:(1)Research on smart healthcare service modes under the background of hierarchical health care delivery system.Three smart healthcare service modes(i.e.,platform-based,product-based,and resource integration-based modes)are analyzed.The relationships among patients,doctors,and hospitals under three smart healthcare service modes are discussed.The key elements like the operation mode,development status and representative services are finally compared.(2)The patients' adoption model of platform-based smart healthcare services is proposed.Taking patients' adoption behavior as the research object,this dissertation puts forward relevant research hypotheses based on dual-factor theory and service quality theory.The patients' adoption model of smart healthcare services combined with patients' decision-making characteristics(i.e.,the types of diseases)is then constructed.Taking the online consultation services as the research context,consultation data from oncology department and cardiovascular department on haodf.com are collected,and the data variables are selected based on research model and hypothesis.Through the construction of econometric model,this dissertation verifies the influence of service quality,service cost,service diversity and disease type on the decision-making of patients' adoption of platform-based smart healthcare services.(3)The doctors' adoption model of product-based smart healthcare services is proposed.Based on the technology acceptance model,this dissertation constructs a doctors' adoption model of smart healthcare services from the perspective of adoption transfer.According to the research model and the conventional adoption scale,the questionnaire items are redesigned.The questionnaire data of 484 doctors are collected by survey.The research model and hypothesis are tested by using structural equation model and multi group analysis method.The impact of experience of using m Health and professional differences on doctors' adoption of smart healthcare products are analyzed.(4)The hospitals' adoption models of resource-integrated smart healthcare services are constructed.This dissertation identifies and classifies the key influencing factors in the existing literature based on the technology-organization-environment framework.The research data is collected from expert group.The interpretative structural modeling method is used to establish secondary and tertiary hospitals' and primary medical institutions' adoption models of smart healthcare services.This dissertation reveals the influence mechanism of technology,organization,and environmental factors on the adoption of resource-integrated smart healthcare services by different levels of medical institutions.At present,smart healthcare services are becoming an effective way to solve the problem of insufficient and uneven distribution of high-quality medical resources in China.The wide adoption of smart healthcare services by patients,doctors and hospitals is an important breakthrough to help realize the hierarchical health care delivery system.In conclusion,this dissertation enriches the empirical research in the field of smart healthcare services,and provides practical suggestions and reference for the promotion and long-term development of smart healthcare services.It is worth noting that user adoption is only the first step in the diffusion of smart healthcare services.An important research direction in the future is how to provide personalized and precise smart healthcare services for patients,doctors and hospitals by acquiring,processing and integrating actual user behavior data. |
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