- 學位論文
台灣地區大型醫院生產效率之評估—結合ICA與DEA方法之應用
Integrating ICA and DEA Models to Measure the Relative Efficiency of Large Hospitals in Taiwan
摘要
醫療產業競爭日趨激烈，大型醫院需要更大量的資金投注，而全民健保實施吸引更多民眾就醫，如何利用有限資源做更有效的產出利用，將成為大型醫院重要的經營管理議題。傳統資料包絡分析法（Data Envelopment Analysis，DEA）評估模式仍有易受極端值影響、評估出的有效率決策單位（Decision Making Units，DMUs）過多等缺點，並忽略各產業不同生產要素的重要程度與內涵，因此國內外學者衍伸研究出兩階段資料包絡分析法（Two stage Data Envelopment Analysis，Two-stage DEA），期望彌補傳統DEA方法的不足之處。本研究採廣泛運用於未知訊號分離（Blind Source Separation）的獨立成份分析法（Independent Components Analysis，ICA ），藉由其統計獨立性將投入變數轉化為數個具有綜合性內涵的獨立成份（Independent Components，ICs ），進而篩選具代表性的成份作為新指標變數，使DEA分析的投入變數更具實質意義，藉此找出影響大型醫療機構服務效率的關鍵因素，並作為未來其他醫療機構績效評估時的思考方向。
並列摘要
The competition of medical treatment industry is more and more vigorous, and the national health insurance implement attracts more people. How make use of a limited resource effectively will become an important management subject for large hospitals. Traditional Data Envelopment Analysis（DEA）mode is easily influenced by outliners, and the efficient Decision Making Units（DMUs）is excessive. The scholars find out Two stage Data Envelopment Analysis（Two-stage DEA）to make up the shortages of traditional DEA. Because of the Independent Components Analysis（ICA）is statistical independence. It will transfer the input variables to several meaningful index variables. The input variables will be simplified and will meet the situation more actually. We can find the key factors influence efficiency in large hospitals to make thinking while making up the management strategies.