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Seasonal change trend analysis of the number of inpatients in a southern province from 2010 to 2019. |
Chen Long. |
Government Affair Service Center, Health Commission of Guangdong Province, Guangzhou 510060, China |
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Abstract Objective To analyze the change rule of the number of inpatients in a southern province from 2010 to 2019, and to provide scientific basis for health resource allocation, planning and development, scientific management and service improvement in the province.Methods Based on the monthly data of the inpatients in the province in 10 years, the time series analysis method was adopted to calculate the quarterly and monthly seasonal index through the moving average method to find out the seasonal variation rule of the inpatients.Results The number of inpationts in this southern province has been steadily increasing yearly for ten years.Seasonal indexes of January, February, September and October were less than 100%,and the seasonal indexes in the remaining months were greater than 100%.The seasonal indexes of the first quarter were less than 100% and those of the remaining quarters were greater than 100%.Conclusion Inpatient medical services are growing steadily year by year. It is necessary to constantly improve the capacity of inpatient admission and treatment, rationally make use of the changing characteristics of inpatient demand in "offseason" and "peak season", and formulate appropriate response measures to meet the increasing needs of the people for inpatient services.
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Received: 25 April 2020
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[1]吴鸿鹏,张淑静.山东某三甲医院2007—2016年入院人数季节因素分析[J].中国医院统计,2018,25(2):107-110.
[2]任小超.应用最小二乘法和季节变动法预测某院2018年门诊人数[J].中国医院统计,2018,25(5):335-337.
[3]孙玲.某医院患者住院规律分析[J].中国医院统计,2018,25(3):239-240.
[4]苗静.2010—2014年某院住院人次季节变化分析[J].中国卫生统计,2016,33(3):503-504.
[5]徐国祥.统计预测和决策[M].上海:上海财经大学出版社,2008.
[6]刘洋.基于季节指数的入院患者变动规律分析[J].中国卫生统计,2017,34(4):644-645.
[7]张敏,李志勇.我院2014—2018年门诊人次的季节趋势分析[J].中国卫生统计,2019,36(6):932-933.
[8]董捷.某院5年(2009—2013)住院人次季节变动规律与趋势分析[J].数理医药学杂志,2015,28(6):860-861.
[9]AIK J, ONG J, NG L C. The effects of climate variability and seasonal influence on diarrhoeal disease in the tropical City-state of Singapore -A time-series analysis[J]. Int J HygEnvironHealth, 2020, 227:113517.
[10]PATZ J A, FRUMKIN H, HOLLOWAY T, et al. Climate change: Challenges and opportunities for global health[J]. JAMA, 2014, 312(15):1565-1580.
[11]PHUNG D, CHU C, RUTHERFORD S, et al. Heavy rainfall and risk of infectious intestinal diseases in the most populous City in Vietnam[J]. Sci Total Environ, 2017, 580:805812.
[12]薛允莲,张晋昕.移动假日效应调整对春节影响月份的出院病例数预测效果研究[J].中国卫生统计,2015,32(4):683-685.
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[2] |
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[3] |
Wu Hongpeng, Zhang Shujing. Analysis of seasonal factors of the number of hospital admissions from 2007 to 2016 in a tertiary hospital in Shandong province[J]. journal1, 2018, 25(2): 107-110. |
[4] |
. [J]. journal1, 2016, 23(4): 296-298. |
[5] |
. [J]. journal1, 2016, 23(2): 141-142. |
[6] |
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