南華大學機構典藏系統:Item 987654321/23203
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    Title: 醫療資訊系統導入雲端運算之研究
    Other Titles: Applications of Cloud Computing in Medical Information Systems
    Authors: 李承霖
    Lee, Chen-Lin
    Contributors: 企業管理學系管理科學碩博士班
    黃國忠;褚麗絹
    Kuo-Chung Huang;Li-Chuan Chu
    Keywords: 科技接受模式;成本模式;雲端運算;心流經驗
    Technology Acceptance Model;Cost Model;Cloud Computing;Flow Experience
    Date: 2015
    Issue Date: 2015-08-26 14:15:04 (UTC+8)
    Abstract:   雲端運算的發展日趨成熟並已被廣泛應用,惟尚未推廣至醫療領域。本研究分別以醫院決策者觀點進行成本分析,以及使用者觀點進行使用意願之實證分析,以探討醫療資訊系統是否該採用雲端運算之議題。因此,本研究先透過成本模式的建構與分析,推估自行維護醫療資訊系統之成本,係建立兩個假設模式加以推導。一為醫療資訊系統不穩定模式,考慮零件損壞或故障造成資訊系統的不穩定,而衍生出損失風險,除了推導出資訊人員對資訊系統實施維護保養比率之最適值,亦推論出導入雲端運算系統之判斷值,以提供醫院決策者評估與決定。另一為醫療資訊系統自行維護模式,求解自行維護資訊系統之最小成本支出,與已知的雲端系統租賃成本比較,模式採用尤拉方程式求解,經推論後所得到結果將有助於醫院決策者進行決策參考。  其次,透過使用意願調查模式瞭解醫院員工對於醫療資訊系統採用雲端運算的看法,此模式係以科技接受模式為基礎,結合心流理論加以建構而成,針對醫院員工就醫療資訊系統導入雲端的認知、態度與持續性使用意圖進行探討,其中心流經驗作為調節變項,藉以分析員工的態度對持續使用意圖的調節效果。分析結果顯示,整個模式適配度良好,各項測量指標均符合標準,徑路分析結果亦顯示各項假說均獲得支持。  此外,調節變項之影響測試結果顯示,心流經驗於使用者態度與持續使用意圖之間有顯著的正向調節效果,特別是高頻率心流經驗群組與使用態度交互後對持續使用之影響最為顯著,此結果說明當員工使用雲端運算建置之醫療資訊系統因而產生心流經驗時,更專注在其工作活動中,工作的表現也更加有效率。最後,本研究依據研究結果提出適當的建議,以供醫療領域後續實務應用或學術研究之參考。
      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.
    Appears in Collections:[Department of Business Administration, Master/Ph.D Program in Management Sciences] Disserations and Theses(Master and Doctoral Program in Management Sciences)

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