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Application of exponential smoothing method in prediction of regional health human resource allocation |
Lin Jianchao1, Sun Huanhuan2, Ruan Weiliang1 |
1 Shaoxing Second Hospital, Shaoxing 312000, China;
2 Shaoxing Central hospital, Shaoxing 312030, China |
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Abstract Objective To discuss the application of exponential smoothing method in forecasting the allocation of regional health human resources.Methods Based on the number of physicians per thousand permanent residents in a city from 2011 to 2020, SPSS 23.0 was used to establish the exponential smoothing model, Which was used to predict and evaluate the number of physicians per thousand permanent residents of the city from 2021 to 2023.Results The R2 value of the model constructed by the non-seasonal Holt′s linear trend was the largest, and the R2 value was 0.988, RMSE was 0.053, and MAPE was 1.495, which was the best fitting model.Conclusion The non-seasonal Holt′s linear trend model can better fit the regional health human resource allocation and can be used to predict the regional health human resource allocation.
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Received: 26 March 2022
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[1]曹媛媛.线性回归耦合灰色模型在区域卫生人力资源预测中的应用[J].中国医院统计,2019,26(2):130-132.DOI:10.3969/j.issn.1006-5253.2019.02.014.
[2]周绪凤.基于马尔科夫模型的中国养老护理员需求量预测研究[D].苏州:苏州大学,2018.
[3]李涛,彭传薇,李小华,等.Excel2000指数平滑在冠心病住院病人预测分析中的应用[J].中国医院统计,2005,12(4):381.DOI:10.3969/j.issn.1006-5253.2005.04.043.
[4]陈媛.应用holtwinters加法模型预测出院人次[J].中国卫生统计,2012,29(2):260-261.DOI:10.3969/j.issn.1002-3674.2012.02.036.
[5]童强,张克功,杜吉梁.指数平滑预测法及其在经济预测中的应用[J].经济研究导刊,2013(4):11-12.
[6]周孟君,刘世全,周祖宏.基于HoltWinters指数平滑法的入院人次预测[J].中国病案,2018,19(9):46-48.DOI:10.3969/j.issn.1672-2566.2018.09.017.
[7]李红艳,耿婷婷.GM(1,1)灰色模型在上海市医院诊疗人次预测中的应用[J].现代医院管理,2019,17(6):26-28.DOI:10.3969/j.issn.1672-4232.2019.06.007.
[8]言晨绮,王瑞白,刘海灿,等.ARIMA模型预测2018—2019年我国肺结核发病趋势的应用[J].中华流行病学杂志,2019,40(6):633-637.DOI:10.3760/cma.j.issn.0254-6450.2019.06.006.
[9]刘建峰,张立川,王书华.指数平滑法在临床用血管理中的应用[J].国际检验医学杂志,2014,35(24):3445-3447.DOI:10.3969/j.issn.1673-4130.2014.24.070.
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