Applications of Cloud Computing in Medical Information Systems

• Main Authors: Chen-Lin Lee, 李承霖
• Other Authors: Li-Chuan Chu
• Format: Others
• Language: zh-TW
• Published: 2015
• Online Access: http://ndltd.ncl.edu.tw/handle/33204850790236799204

博士 === 南華大學 === 企業管理學系管理科學碩博士班 === 103 === 　　Although cloud computing has been broadly applied to information technology industries worldwide since its maturity, it has not been promoted in the medical field. From the analytical viewpoints of hospital authorities and users, the study discussed whether cloud computing must be applied to medical information systems. Through the establishment and analysis of a budget model, the costs of maintaining medical information systems by the hospital authorities were estimated, and two hypothetical models were used to deduce the estimation. One of the models assumed a scenario in which component damages or malfunctions rendered a medical information system unstable, thereby incurring a risk of potential financial losses. Within the budget limit, an optimal value for the maintenance ratio generated by information personnel in maintaining the information system was estimated, and an acceptance value to be used in the cloud computing system was inferred, thereby providing hospital authorities with references for assessment and decision-making. The other model involved maintaining the medical information system by hospital authorities themselves. The minimal cost for the maintaining the system was calculated using the Euler formula and compared to the known costs of renting cloud computing systems. The inferential result provided hospital authorities with a reference for decision making. 　　Secondly, a usage-intention investigation model was used to understand the opinions of hospital workers on applying cloud computing in medical information systems. Based on the technology acceptance model combined with flow theory, this model was used to examine hospital workers’ perceptions, attitudes, and intentions to continue to use cloud-computing-based medical information systems. Particularly, the experiences explained by flow theory was regarded as a moderator of the effect of worker attitudes on intentions to continue to use the systems. The analysis result revealed favorable goodness of fit in the entire model; all of the measurement indices were consistent with the standards. In addition, the path analysis indicated that the hypotheses were supported. 　　Examining the moderator effect revealed that flow experience positively moderates the effect of user attitudes on intentions to continue using the system. Particularly, after the high-frequency flow experience group and the usage attitude group switched with each other, the effect on intentions to continue using the systems was the greatest. The result indicated that when workers acquired flow experience in using cloud-computing-based medical information systems, workers concentrated more on their work activities, and work efficiency improved. Finally, appropriate suggestions were proposed according to the results, thereby providing a reference for future practical applications and academic studies in the medical field.