ARIMA模型与GM(1,1) 模型在医院门诊人次预测中的比较研究

doi:10.3969/j.issn.1006-5253.2017.01.002

Abstract
Figure/Table
References
Related Citation (15)

Download: PDF (1099 KB) HTML (1 KB)
Export: BibTeX | EndNote (RIS)

Abstract Objective To evaluate the effectiveness of ARIMA and GM(1,1) models in outpatient population forecasting, and to provide the basis for selecting appropriate predictive methods. Methods ARIMA model and GM (1, 1) model were constructed using monthly data of outpatient visits from 2005 to 2014. At the same time, the number of outpatients in 2015 was forecasted, and the results of the two models were validated by the actual number of outpatients in 2015. The evaluation indexes were average relative error and mean absolute value error. Results The average error rate (MER) of ARIMA and GM(1,1) models were 3.90% and 4.41%, respectively. The coefficients of determination R² were 0.961 and 0.955, respectively. For the year 2015, the average relative errors between the predicted value and the measured value were 23 959 and 35 397, the average absolute errors were 4.62% and 6.83% respectively. Conclusion ARIMA model has a better effect than GM (1,1) model on samples over 30 and on the long-term trend, cyclical trend and implicit seasonal change trend. For the data such as the number of outpatients in time series, we should consider ARIMA Model first to get a better fitting effect, and the relative error is smaller.

Received: 28 September 2016

	Service

	E-mail this article
	Add to my bookshelf
	Add to citation manager
	E-mail Alert
	RSS
	Articles by authors
	Liu Guozhu

Cite this article:

Liu Guozhu. Comparative study of ARIMA model and GM (1,1) model in hospital outpatient service forecast[J]. journal1, 2017, 24(1): 5-8.

URL:

http://manu58.magtech.com.cn/Jwk_zgyytj/EN/10.3969/j.issn.1006-5253.2017.01.002 OR http://manu58.magtech.com.cn/Jwk_zgyytj/EN/Y2017/V24/I1/5

[1] 李哲.西京信息科工作手册[M].西安:第四军医大学出版社,2012:30-64 .
[2] 熊巨全.医院管理与医学统[M].北京:人民军医出版社,2002:95-130.
[3] 苑继承,高湘伟,石岳琴,等.门诊患者挂号与就诊时间调查分析[J].第四军医大学学报,2005,26(1):83-85.
[4] 于亚滨.医院门急诊、住院病人量预测及变动趋势分析[J].中国病案,2005,6(6):62-63.
[5] 赵琳,肖蓓.门急诊量和出院人次预测线性回归模型的建立和应用[J].中国病案,2014,15(11):39-40.
[6] 曹阳,徐峰.利用直线回归方程预测医院门急诊人数、出院人数、住院手术人数[J].中国医院统计,2013,20(5):354-355.
[7] 邓维斌,唐兴艳,胡大权,等.SPSS19统计分析实用教程[M].北京:电子工业出版社,2012:264-266.
[8] 邓聚龙.灰预测与灰决策[M].武汉:华中科技大学出版社,2002:1-244.
[9] 王丙刚,曲波,郭海强,等.传染病预测的数学模型研究[J].中国卫生统计,2007,24( 5):536-540.
[10]范引光,吕金伟,戴色莺,等. ARIMA 模型与灰色预测模型GM( 1,1) 在HIV 感染人数预测中的应用[J].中华疾病控制杂志,2012,16(12):1100-1103.
[11]刘晓钰陈莉雅,陈平雁.用指数平滑模型预测广州某三甲医院出院量[J].中国医院统计,2016,23(2):92-95.
[12]周忠彬,吕红梅,邹郢.ARIMA 干预模型在医院门诊量预测中的应用[J].中国医院统计,2008,15(2):110-112.
[13]刘刚,唐宋,孙文杰.时间序列分析法在香港结核病预测中的应用[J].中国卫生统计,2012,29(2):226-228.
[14]贾丹丹,陈用贵,周助人.灰色预测模型在我国年采血量预测中的应用探讨[J].中国卫生统计,2012,29(3):414-415.
[15]周琴.利用ARIMA乘积季节模型预测某综合性医院门诊量[J].中国医院统计,2016,23(2):141-142.
[16]徐永强,周静,陈学军,等.ARIMA(p,d,q)模型在不同地区来源门诊量预测中的应用[J].中国医院统计,2009,16(3):202-206.
[17]吴伟,关鹏,郭军巧,等.GM(1,1) 灰色模型和ARIMA模型HFRS发病率预测中的比较研究[J].中国医科大学学报,2008,37(1):52-55.
[18]潘浩,胡家瑜,吴寰宇,等.GM(1,1)灰色模型和ARIMA模型在上海市手足口病发病率应用中的比较研究[J].中华疾病控制杂志,2011,15(5):445-448.
[19]韩春蕾,高婉君. 我国月度CPI的组合预测及分析[J].统计与决策,2014(1):11-13.