建立手術時間預測模式於手術室排程管理－－以某個案醫院為例

Building an Operating Time Forecasting Model in Operating Room Scheduling Administration - Experiences in a Hospital

手術室的營運作業對於外科系的醫療業務有相當重要的影響，由於手術室單位人力成本高且投入儀器設備資本相當昂貴，所以醫院管理者應重視其管理效率及其資源是否有被妥善利用。在既有的空間及設備下手術室每天可執行的手術次數，端賴手術室有無有效率的管理，而手術室管理最重要的議題就是排程問題，排程好壞會直接影響手術室的使用效率及營運效益。本研究主要目的是利用個案醫院2004年度手術室的所有相關資料進行分析，特別是著重於每一術式的手術時間分佈、變異及手術時間的預測，以供手術室管理人員進行排程作業時的參考。本研究方法是利用統計學的廻歸分析法來探討影響手術時間的因素，利用複廻歸、一般線性模式以知道手術時間和自變項之間影響的相關與模式，從而建立起可應用的手術時間預測模式，以期應用在電腦化的手術室排程。研究結果發現手術式本身是影響手術時間的最大因素，而在本研究中的其他自變項中，會因為不同的手術式而產生或多或少不同程度的影響，在驗證模式5與6中手術本身也準確預測手術可能花費的時間，如此，對於排程人員而言可以預先掌控相當的資訊，對每天手術室手術排程就能有莫大的助益。

The operation unit involved intensive manpower and high-cost equipment. The efficiency and efficacy of the operation system in operation unit would greatly impact on the hospital finance. The efficiency of operation scheduling is the priority in operating room management. Among many factors that may influence the system running, accurate estimation of operation time plays an important role in reducing resources waste and increasing health care quality. This study aims to establish a forecasting model of operation time. We retrospectively reviewed all profiles of operation patients in the hospital during 2004 to especially focus on the operating time distribution, variances, and operating time prediction of each surgery type. The research method was to use the regression analysis to investigate the factors that may influence the operation time. Besides, the multiple regression analysis and general linear model were used to find out the correlation between the operating time and independent variables in order to establish an applicable forecasting model for scheduling administration in operation room. This forecasting model will serve as a basis for computerized operation scheduling system. We found surgery type is the major factor that may affect the operation time. Factors may vary in predicting different types of surgeries. In models 5 and 6, surgery type proved to be the most important factor that may accurately predict the operating time. The information gathered from this study may help operating room managers to forecast actual operation time in advance.