华南预防医学 ›› 2016, Vol. 42 ›› Issue (6): 549-552.doi: 10.13217/j.scjpm.2016.0549

• 论著 • 上一篇    下一篇

广东省区域卫生信息平台门诊量时间变化趋势分析

徐勇1,吴伟彬1,伍水平2,张媚1,李胜峰1   

  1. 1.广东省疾病预防控制中心,广东 广州 511430;2.广东智源信息技术有限公司
  • 收稿日期:2016-03-29 修回日期:2016-03-29 出版日期:2017-01-10 发布日期:2017-01-11
  • 作者简介:徐勇(1966―),男,硕士研究生,副主任医师,主要从事信息管理工作
  • 基金资助:
    广东省科技计划项目(2013B040401009); 广东省医学科学技术研究项目(WSTJJ20130422440105196612182439)

Time variation trend analysis of regional health information platform of Guangdong Province

XU Yong1, WU Wei-bin1, WU Shui-ping2, ZHANG Mei1, LI Sheng-feng1   

  1. 1.Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430,China;2.Guangdong Zhiyuan Information Technology Co.,Ltd
  • Received:2016-03-29 Revised:2016-03-29 Online:2017-01-10 Published:2017-01-11

摘要: 目的分析广东省区域卫生信息平台医院门诊量随时间变化规律,检验其与流感样病例(ILI)监测系统监测点门诊量时间趋势的相关性,探索区域卫生信息平台数据替代目前哨点监测数据的可行性。方法从广东省G市和F市区域卫生信息平台中抽取数据质量较高的8家医院的2012―2014年门诊数据,同时收集“中国流感监测信息系统”(以下简称ILI系统)中G市和F市9家监测点医院2012―2014年门诊数据,对2组数据进行相关性分析,同时采用时间序列季节指数分析法分析2组数据1年中门诊量的变化规律。结果G市和F市平台与ILI系统各月门诊量占全年门诊量百分比均较为接近,相关性分析结果显示,G市Pearson相关系数为0.646,F市为0.624(均P<0.01)。门诊量季节指数分析结果显示,G市平台季节指数>100.00%的有3―8、12月,ILI系统季节指数>100.00%的有3―7、9、12月,其中3―7、12月为共同的就诊高峰期;F市平台季节指数>100.00%的有3―8、12月,ILI系统季节指数>100.00%的有3―6月,其中3―6月为共同的就诊高峰期;折线图显示G市和F市平台与ILI系统的季节指数均有较高的相似度。结论广东省区域卫生信息平台门诊量月分布情况与ILI系统基本一致,使用平台门诊数据替代哨点监测数据基本可行。

Abstract: ObjectiveTo analyze the changing rule of the outpatient amount of hospitals from the regional health information platform (RHIP) of Guangdong Province, examine the correlation of the changing rule and time trend of outpatient amount between RHIP and the influenza like illness surveillance system (ILISS), and explore the feasibility of replacing the data from ILISS with data from RHIP.MethodsOutpatient clinical data were collected from 8 hospitals with high data quality in cities G and F during 2012 - 2014 through RHIP of Guangdong Province. Meanwhile outpatient clinical data were collected from 9 sentinel hospitals of influenza surveillance in the same cities and periods through ILISS of China Influenza Surveillance Information System. A correlation analysis between the two sets of data was conducted and seasonal index changes of outpatient visits in one year were analyzed by the time series analysis method.ResultsPercentages of monthly amount of outpatient visits in yearly amount of outpatient visits were similar between the two sets of data. The correlation analysis showed that the Pearson correlation coefficients were 0.646 for City G and 0.624 for City F (Both P<0.01). For City G, the analysis of seasonal index of outpatient amount showed that the seasonal indices were over 100.00% in March to August, and December for data of RHIP, and in March - July, September, and December for data of CNISIS for ILI, and the peak periods of outpatient visits appeared in March - July, and December for both systems. For City F, the seasonal indices were over 100.00% in March - August, and December for data of RHIP, and in March - June for ILISS, and the peak periods of outpatient amount appeared from March to June for both systems. The line chart showed that the seasonal index from RHIP had high similarity with that from ILISS.ConclusionThe monthly distribution of the outpatient amount from RHIP was basically consistent with that from the ILISS. Therefore, it may be feasible to use the outpatient data from RHIP to replace the data from ILISS.

中图分类号: 

  • R195