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某三甲综合医院门诊量ARIMA预测分析
引用本文:李运明,吴凡,郑驰,侯凯文,王魁英,孙年怡,许贲,赵靖,李勇.某三甲综合医院门诊量ARIMA预测分析[J].中国病案,2014(8):53-55.
作者姓名:李运明  吴凡  郑驰  侯凯文  王魁英  孙年怡  许贲  赵靖  李勇
作者单位:成都军区总医院,成都市610083
基金项目:成都军区总医院首批研究型人才工程培养基金(2011YG-C12,2013YG-B021),四川省卫生厅科研课题(120566)
摘    要:目的 探讨ARIMA模型预测医院门诊量效果,短期预测某院门诊量,为医院门诊管理决策提供依据.方法 在医院信息系统中,提取某三甲综合医院2010年1月至2014年3月门诊患者数据,采用PASW软件时间序列预测模块,拟合门诊量ARIMA模型,评价模型效果,预测未来2年门诊量.结果 2010至2013年累计接诊门诊患者303.6万人次,年平均增长率为24.07%.男女性别比0.81∶1,平均年龄40.36±19.32岁,内外科比为1.35∶1.基于2010年-2013年门诊量数据,采用ARIMA模型预测2014年1季度门诊量相对误差为4.11%,模型预测效果较好.基于2010年1月-2014年3月门诊量数据,预测2014年门诊量为113.2万人次,2015年门诊量为129.5万人次.结论 借助PASW软件,采用ARIMA模型预测大型综合医院门诊量操作简单,模型拟合和预测效果较好,结果易于解释,是一种值得推广的医院季节性波动数量指标(门诊量、收容量、手术量等)短期预测工具.

关 键 词:医院信息管理  门诊管理  门诊量  ARIMA  预测

Predictive Analysis of Outpatient Amount of a First-class Grade A General Hospital upon ARIMA Model
Li Yunming,Wu Fan,Zheng Chi,Hou Kaiwen,Wang Kuiying,Sun Nianyi,Xu Ben,Zhao Jing,Li Yong.Predictive Analysis of Outpatient Amount of a First-class Grade A General Hospital upon ARIMA Model[J].Chinese Medical Record,2014(8):53-55.
Authors:Li Yunming  Wu Fan  Zheng Chi  Hou Kaiwen  Wang Kuiying  Sun Nianyi  Xu Ben  Zhao Jing  Li Yong
Institution:, (Chengdu Military General Hospital, Chengdu 610083, Sichuan Province, China)
Abstract:Objectives To explore the effect of ARIMA model in predicting the outpatient amount of hospital, short-term forecasts outpatient amount of a hospital, thus to provide a basis for hospital outpatient management decisions. Methods Extract data of outpatient from hospital information system of a first-class grade A general hospital, with time scope from January, 2010 to March 2014. The data was analyzed as time series by PASW in order to predict module. Fit the ARIMA model to the outpatient amount, thus to evaluate the effect of this model and to predict the outpatient amount in the next 2 years. Results From 2010 to 2013, the outpatients treated add up to 3,036 million person-time, with an annual average growth rate of 24.07%. Male-female ratio 0. 81:1, mean age 40. 36 ± 19. 32, internal-external medicine ratio 1.35:1. Based on the outpatient amount data from 2010-2013, the predictive value of outpatient amount in first quarter of 2014 is with a relative error of 4. 11%, the model has a good predictive effect. Based on the outpatient amount data from January, 2010 to March 2014, the predictive value of outpatient amount in 2014 is 1. 132 million person-time, and in 2015 is 1. 295 million person-time. Conclusions With the help of PASW, predict the outpatient amount of large general hospital by ARIMA model has the characteristics of easy operation, good model fitting and predictive effect, and the result is easy to explain. It is a short-term forecasting tool to predict quantitative index (outpatient amount, capacity, surgery quantity, etc. ) with characteristics of seasonal fluctuation of hospital, and is worthy to be popularized.
Keywords:Hospital information management  Outpatient management  Outpatient amount  ARIMA  Prediction
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