[1]刘 焰,卢萍萍.基于移动平均季节指数法的门诊量分析及预测[J].医学信息,2021,34(23):156-158.[doi:10.3969/j.issn.1006-1959.2021.23.047]
　LIU Yan,LU Ping-ping.Analysis and Prediction of Outpatient Volume Based on Moving Average Seasonal Index Method[J].Medical Information,2021,34(23):156-158.[doi:10.3969/j.issn.1006-1959.2021.23.047]
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基于移动平均季节指数法的门诊量分析及预测()
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医学信息[ISSN:1006-1959/CN:61-1278/R]

卷:
34卷
期数:
2021年23期
页码:
156-158
栏目:
调查分析
出版日期:
2021-12-01

文章信息/Info

Title:
Analysis and Prediction of Outpatient Volume Based on Moving Average Seasonal Index Method
文章编号:
1006-1959（2021）23-0156-03
作者:
刘 焰; 卢萍萍
（南通市第三人民医院信息科1，综合统计科2，江苏 南通 226000）
Author(s):
LIU Yan; LU Ping-ping
(Department of Information1,Department of Comprehensive Statistics2,Nantong Third People’s Hospital,Nantong 226000,Jiangsu,China)
关键词:
移动平均季节指数法; 最小二乘法; 门诊量预测; 医疗资源
Keywords:
Moving average seasonal index method; Least squares method; Outpatient volume prediction; Medical resources
分类号:
R197
DOI:
10.3969/j.issn.1006-1959.2021.23.047
文献标志码:
A
摘要:
目的 了解某院门诊量季节变动规律并进行趋势预测，为医院的卫生资源配置和管理决策提供科学的参考依据。方法 收集某院2013-2018年门诊量数据，运用移动平均季节指数法对数据进行分析，结合最小二乘法原理求得直线回归方程，计算2019年的门诊量预测值。结果 2013-2018年，该院除2016年门诊人次有下降外，其余各年门诊量均逐年增加，门诊量各年度季节指数以第一季度最低（90.32%），第三季度最高（104.48%）；趋势预测显示，2019年四个季度的预测值依次为138 279人次、160 613人次、163 196人次、159 859人次，预测值与实际值的相对误差为4.4%~14.0%，平均相对误差为9.95%。结论 该院门诊量呈逐年增加的趋势且存在季节变动规律，移动平均季节指数法构建的模型能较好地用于门诊量的预测，为医疗资源的合理配置和现代化医院的精细化管理提供参考。
Abstract:
Objective To understand the seasonal variation of outpatient volume in a hospital and forecast the trend, so as to provide scientific reference for the allocation and management of health resources in the hospital.Methods The data of outpatient visits in a hospital from 2013 to 2018 were collected and analyzed by moving average seasonal index method. The linear regression equation was obtained by combining the principle of least squares method, and the predicted value of outpatient volume in 2019 was calculated.Results From 2013 to 2018, except for the decrease of outpatient visits in 2016, the annual outpatient visits increased year by year. The annual seasonal index of outpatient visits was the lowest in the first quarter (90.32%) and the highest in the third quarter (104.48%). Trend prediction showed that the predicted values of the four quarters in 2019 were 138 279, 160 613, 163 196 and 159 859, respectively. The relative error between the predicted value and the actual value was 4.4%-14.0%, and the average relative error was 9.95%.Conclusion The outpatient volume of the hospital is increasing year by year and has seasonal variation. The model constructed by moving average seasonal index method can be used to predict the outpatient volume, and provide reference for the rational allocation of medical resources and the fine management of modern hospitals.

参考文献/References:

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更新日期/Last Update: 1900-01-01