The Relationship between IT Infrastructure Flexibility and Hospital Technical Efficiency and Building the Performance Evaluated Model

• Main Authors: Fu-Jeng Yang, 楊馥甄
• Other Authors: 林榮禾
• Format: Others
• Language: zh-TW
• Published: 2006
• Online Access: http://ndltd.ncl.edu.tw/handle/b53wh6

碩士 === 國立臺北科技大學 === 商業自動化與管理研究所 === 94 === Taiwan started its National Health Insurance Program（NHIP）on March 1, 1995. It means limited medical resources redistributed and medical income registered by payment standard. It causes the unheard-of competition in the whole medical environment in Taiwan. Therefore, hospitals must decrease medical cost and raise medical quality to improve competitiveness and achieve the purpose of sustainable business. In recent years, the advancement of information technology including applying software, raising computer hardware function and developing internet application greatly supports the operational efficiency for doctors and nurses and raises the administrative efficiency to improve the whole medical care and service quality. This research proposes a model to evaluate a hospital’s efficiency and discusses the effects of IT infrastructure flexibility on hospital’s efficiency. The purpose is to know what factors affect hospital’s efficiency most significantly. The research methods includes the data envelopment analysis（DEA）, Tobit regression（TR） and classification and regression tree（CART）. This research applies DEA to evaluate hospitals’ efficiencies. Then, we use CART to build the model to find the rule of evaluating a hospital’s operation efficiency. Further, we use the TR method to find the effects of IT infrastructure flexibility on hospital’s operation efficiency. This research could be a valuable reference for government to promote domestic hospital’s operation efficiency and IT update. Results indicate that medical centers significantly operate more efficiently than regional hospitals and district teaching hospitals. IT compatibility, data transparency, management knowledge and technical knowledge positively contribute to the efficiency for hospitals. The classification tree constructed in this study, the average correct classification rate is 89.29% for learning sample and the average correct classification rate is 75% for testing sample. This research could be a valuable reference for hospitals to evaluate operation efficiency.