Applying the Period Moving Average Method to Forecast the Number of Emergency Patients

• Main Authors: Yi-Lin Chen, 陳憶琳
• Other Authors: Yan-Kuen Wu
• Format: Others
• Language: zh-TW
• Published: 2013
• Online Access: http://ndltd.ncl.edu.tw/handle/09058295816467089277

碩士 === 萬能科技大學 === 經營管理研究所 === 101 === The higher education specifically dedicates to diversified social needs in Taiwan's formal education system. The nursing education attached to the Department of Technological and Vocational Education has being more and more attention in the dark moment of nurses in Taiwan recently. The medical staffs of the emergency room need the professional knowledge and skills covering professional ethics and the spirit of service. In this study, the time series methods of ARMA model, fuzzy-ARMA, moving average, exponential smoothing, the period moving average method are applied to forecast the number of emergency patients. By the prediction to the number of emergency patients can provide medical staff the comprehensive data of need to emergency room in advance. The precise forecast of the number emergency patients will affect the manpower planning and arrangement of medical staffs. The medical staffs must pay attention to the work how to select the right method to make reliable forecast when they face the uncertain number of emergency patients. This study selects total 730 pieces of daily the number of emergency patients from a hospital emergency room between July 1, 2010 to June 30, 2012. These emergency patient data are employed to construct as modeling and testing samples for the time series model of ARMA model, fuzzy-ARMA, moving average, exponential smoothing, the period moving average method. Based on the mean absolute percentage error (MAPE) to measure the accuracy of the applied methods, the MAPE is 10.81% for the period moving average method has better accuracy.