Research on Predicting the Number of Outpatient Visits
Objective To build prediction model and provide data for the management and policy-making of the hospital by analyzing the data of outpatient visits by time series analysis. Methods The prediction model was built by regression equation and elimination met
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Research on Predicting the Number of Outpatient Visits Hang Lu, Yi Feng, Zhaoxia Zhu, Liu Yang, Yuezhong Xu and Yingjia Jiang
Abstract Objective To build prediction model and provide data for the management and policy-making of the hospital by analyzing the data of outpatient visits by time series analysis. Methods The prediction model was built by regression equation and elimination method to perform value prediction and interval prediction about the future trend of outpatient visits. Standard value was calculated according to staff distribution. Results The change of the number of outpatient visits was closely related to seasonality. Error rate of outpatient visits prediction was less than 5 % except that the rate was about 10 % in 2003 and 2006. Actual number of every year was within the scope of prediction interval. The prediction value of 2013 was 549856 (497739, 601974), an increase of 7.22 % compared with that of 2012 (512852). Standard values of 2013 were 887680 and 543120, increasing by 73.09 and 5.90 % respectively compared with that of 2012 (512852). Conclusion Based on the prediction, we can rationally allocate resources, guide the management of outpatient departments, increase the number of outpatient visits and improve the efficiency of outpatient service. Keywords Time series analysis and elimination method
Season index
Regression equation
The number of patients is a significant statistical index for the work of the hospital [1]. The scientific prediction can provide basis for the planning and development of hospital, setting objectives and responsibilities for president and heads of departments in hospital, performance evaluation and human resources management. It is necessary for scientific management and rational arrangement of manpower, materials and financial resources to predict the number of outpatient visits [2, 3].
H. Lu Y. Feng Z. Zhu L. Yang Y. Xu Y. Jiang (&) Sichuan Provincial Hospital for Women and Children, Chengdu 610045, Sichuan, China e-mail: [email protected]
S. Li et al. (eds.), Frontier and Future Development of Information Technology in Medicine and Education, Lecture Notes in Electrical Engineering 269, DOI: 10.1007/978-94-007-7618-0_27, Springer Science+Business Media Dordrecht 2014
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27.1 Data and Methods 27.1.1 Sources of Data The data came from outpatient enquiry mode of hospital information system.
27.1.2 Statistic Methods [4–9] 27.1.2.1 Calculation of Prediction Value The number of outpatient visits varies with seasonality, and shows an increasing trend in the long term. To accurately reflect the characteristics and eliminate longterm influence, we adopted regression equation and elimination method as follows: Firstly, calculate season index: calculate chronological average of each year, and then contrast the average with the whole average to get the seasonality ratio. Secondly, regression equation and elimination method: with month x as independent variable and the number of outpatient visits y as dependent variable, we g
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