Although the development of cloud computing has gradually matured, studies on the use of cloud computing for medical information systems remain deficient. In this study, a two-stage model was used to perform related analysis. Stage one of the model employed a mathematical model to estimate the cost model for self-built information systems as well as the involved risk loss. The difference in the information systems' costs and operational performance with and without cloud computing technology

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... e discussed. Stage Two of the model used the technology acceptance model integrated with the flow theory to investigate the behaviour and attitude of the medical staff toward cloud computing technology, the criteria for them to accept the technology, and their subsequent continuous use intention. The moderated structural equation modelling results generally supported the hypotheses. The article concludes by discussing the theoretical and implications of the research findings. This research offers management the opportunity to asset the overall hospital information system process and improve efficiency and effectiveness. system may be the optimal solution among those currently available. Shi, Zhang, and Li [1] indicated that cloud computing tenants face new challenges in secure data storage, including challenges related to data privacy and securing data stored on untrustworthy servers. Whether computing technology can be accepted by medical institutions depends on the ability of cloud system supplier to propose appropriate measures for ensuring uninterrupted service and secure access to network data and for protecting the system from malicious program attacks. Most importantly, a transparent security management system must be in place. Cloud technology is a crucial information technology of this century; it has been gradually accepted by businesses in various industries, features several advantages, and creates corporate competitive advantages. However, studies that employ information system costs and risk aversion capability to assess the feasibility of using cloud computing systems in hospitals remain scant. Therefore, this study adopted a two-stage model to perform analysis. Stage One of the model involves employing a mathematical model to estimate the cost model of a self-built information system as well as the relevant risk loss, and subsequently analyse the difference in the information systems' costs and operational performance with and without cloud computing technology. Stage Two of the model used the technology acceptance model (TAM) combined with the flow theory to investigate the behavior and attitude of medical staff toward cloud computing technology, the criteria for them to accept the technology, and their subsequent continuous use intention (CI). The next section presents the proposed research hypothesis, the underlying construct and moderating variables, as well as the measurement items. Various construct variables and items were validated using factor analysis. The final section of the study presents the conclusion and a discussion regarding cloud computing and its key features.