CSA&TISC2019丨临床研究大数据与脑重大疾病负担

2019-06-30 国际循环编辑部 国际循环

编者按:近年来,互联网、大数据等技术的快速发展,极大推动医院信息化管理建设。如何充分利用积累的海量数据资源,为疾病诊疗提供助力,成为大家关注的话题。6月28日,CSA&TISC 2019大会于北京召开,首都医科大学附属北京天坛医院潘岳松博士,介绍了怎样通过统一标准化数据元实现不同临床研究数据库的关联,进而加速疾病负担研究结果的产出。

编者按:近年来,互联网、大数据等技术的快速发展,极大推动医院信息化管理建设。如何充分利用积累的海量数据资源,为疾病诊疗提供助力,成为大家关注的话题。6月28日,CSA&TISC 2019大会于北京召开,首都医科大学附属北京天坛医院潘岳松博士,介绍了怎样通过统一标准化数据元实现不同临床研究数据库的关联,进而加速疾病负担研究结果的产出。

疾病负担是疾病、伤残和早死对整个社会经济及健康的压力。常用疾病测量指标包括发病率、患病率、死亡率和门诊和住院率等流行病学指标,以及潜在减寿年数、质量调整生命年、伤残调整生命年(disability adjusted life year,DALY)和健康寿命年等反映疾病负担的指标。其中,DALY被广泛应用于疾病负担的研究,它包括早逝所致寿命损失和伤残所致寿命损失。

了解疾病流行情况方法包括随机抽样调查、疾病监测和大数据技术等方法。由于随机抽样调查的方法现场组织难度大、费时又费力,经常采用疾病监测和大数据技术的方法获得疾病负担的数据。比较经典有美国行为危险因素系统(BRFSS)、美国国民健康访问调查(NHIS)、美国营养与健康调查(NHANES)、加拿大慢病监测系统(CCDSS)、中国CDC死因监测和中国CDC慢性病及其危险因素监测等等。

在中国,北京天坛医院已建立多个脑血管临床研究数据库,包括社区人群队列、全国脑血管病流调数据和慢病监测行政数据库等以人群为基础的人群数据,CNSR-1,CNSR-2,CNSR-3等以医院为基础的临床数据,依托北京脑血管病样本资源库的多项研究血尿样样本资源,以金桥工程、CAMERA慢病监测项目等为主要脑血管病医疗服务质量数据库。这些数据库包括基本信息、行为饮食、疾病与治疗、血液样本、基因、生物标志物、影像、病史与体检、随访信息和认知信息等多维度信息。目前,已完成1161个卒中数据元的标准化和注册,并形成一系列E-CRF表单,现在应用的E-CRF表单分为8大领域,28个子领域,共计63个E-CRF表单。在此基础上,通过北京市科委的课题,进一步将数据元扩展到各脑重大疾病,建立脑重大疾病数据元字典,并与国际神经系统疾病通用数据元实现互认,方便国际合作。同时,通过统一的脑血管病通用数据元,实现不同数据库之间的互联互通,最大限度地发挥数据库的价值。





利用现已建立的脑血管病大数据平台,产出大量权威的疾病负担数据,为政府决策与科学研究提供依据。其中,北京地区重大慢性病发病监测平台,利用全市病案首页与死因行政数据库,提供每年全市心脑血管事件发病人数,为政府决策提供依据。国家神经系统疾病质控中心,通过采集全国31个省份三级医院病案首页信息,统计19种神经系统重点疾病,每年更新并动态展示全国各省神经系统的疾病负担与医疗服务质量质控数据,如脑梗死11项KPI指标执行率、全国卒中中心建设医院数量、脑血管病病种分类、脑血管病平均住院日、次均费用、住院病死率等。

在芬兰,通过关联患者个体水平的多个行政注册数据库,建立国家卒中监测体系(PERFECT),系统评价卒中患者的治疗、服务和结局,不仅对疾病的监测有较高的覆盖率和较完整的随访信息,而且维持费用较低、节省监测成本。在美国,美国心脏协会(AHA)在2003年组织开展Get With The Guidelines-Stroke项目(GWTG-Stroke)。截至2013年7月,全美范围内超过1680家医院自愿加入GWTG-Stroke项目,已使得美国71.7%的人口从该项目中获益,各项指南推荐的治疗措施在临床的使用率在参与项目的医院得到显著提高。

在国际上,另一个有代表性的研究是华盛顿大学健康测量评估中心(IHME)开展的全球疾病负担研究(GBD)。通过采集如疾病监测系统、死亡监测系统和伤害监测系统等结构化数据,卫星遥感数据、社会经济调查等非结构化数据,计算并报道195个国家或地区359种疾病和伤害、3228种后遗症和84种危险因素的疾病负担数据。基于云计算的大数据技术加速GBD研究结果的产出,对世界各国卫生政策产生深远的影响。根据2016年GBD报道,相比于1990年,2016年神经系统疾病是首位致残(2.76亿DALY,占总DALY的11.6%)与第二位致死疾病(900万,占总死亡的16.5%)。相比于1990年,2016年神经系统疾病总体绝对致残与致死数上升分别15%与39%,总体年龄标化致残与致死数下降分别27%与28%。造成这个数据差异的主要原因是人口增长与人口老龄化。



影响DALY的四大神经系统原因为卒中42.2%,偏头痛(16.3%),AD及其他痴呆(10.4%),脑膜炎(7.9%)。其中,卒中是疾病负担最重的疾病,全球卒中终生患病风险达24.9%,而中国人卒中终生患病风险最高,达到39.3%。患者发生卒中事件后1年痴呆发生率较高,在严重卒中人群中为34.4%,轻型卒中人群中为8.2%,TIA人群中为5.2%。神经系统疾病所致死亡的第二位病因为阿尔茨海默病和其他类型痴呆。近年来,痴呆患病率呈增加趋势,痴呆负担持续增长。根据2018全球痴呆报告,每3秒1例痴呆患者,2018年痴呆患者达5000万,预计2050年增长到2018年的3倍。阿尔茨海默病与痴呆患病率随着年龄增加而快速增长,50~80岁间每5岁增加一倍。



总之,通过统一标准化数据元可实现不同临床研究数据库的关联,多途径的临床研究大数据可加速疾病负担研究结果的产出,对卫生政策产生深远的影响。神经系统疾病的疾病负担较重,是所有疾病中首位致残与第二位致死疾病,影响DALY的四大神经系统疾病包括卒中、偏头痛、阿尔茨海默病及其他痴呆和脑膜炎。

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    0

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  3. [GetPortalCommentsPageByObjectIdResponse(id=814552, encodeId=d8b6814552e2, content=学习, beContent=null, objectType=article, channel=null, level=null, likeNumber=90, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=, createdBy=64245268311, createdName=14818eb4m67暂无昵称, createdTime=Fri Aug 28 08:30:27 CST 2020, time=2020-08-28, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=1984778, encodeId=7f221984e7872, content=<a href='/topic/show?id=ddc11e48295' target=_blank style='color:#2F92EE;'>#TISC#</a>, beContent=null, objectType=article, channel=null, level=null, likeNumber=33, replyNumber=0, topicName=null, topicId=null, topicList=[TopicDto(id=17482, encryptionId=ddc11e48295, topicName=TISC)], attachment=null, authenticateStatus=null, createdAvatar=https://thirdwx.qlogo.cn/mmopen/vi_32/Q0j4TwGTfTI5PdY90y5Jib8FnPhCXTR2d9v3K17epNSwB2eb0vmXUldNJl2e72S4unZTAHLAojicdVSialTDFHAxA/132, createdBy=78d82500042, createdName=ms7514935887898259, createdTime=Wed Jan 29 08:43:00 CST 2020, time=2020-01-29, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=371579, encodeId=25373e1579f2, content=好, beContent=null, objectType=article, channel=null, level=null, likeNumber=97, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=http://cdnapi.center.medsci.cn/medsci/head/2019/07/01/577acf4668c2eb760152040cdd4c4196.jpg, createdBy=dc3f5107879, createdName=最帅小男护, createdTime=Wed Aug 21 01:20:27 CST 2019, time=2019-08-21, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=1333612, encodeId=ee921333612c7, content=<a href='/topic/show?id=1a1de07305e' target=_blank style='color:#2F92EE;'>#疾病负担#</a>, beContent=null, objectType=article, channel=null, level=null, likeNumber=37, replyNumber=0, topicName=null, topicId=null, topicList=[TopicDto(id=70730, encryptionId=1a1de07305e, topicName=疾病负担)], attachment=null, authenticateStatus=null, createdAvatar=http://thirdqq.qlogo.cn/qqapp/1103841572/B389FA68ECBF51BE2FE14093CF61F6AE/100, createdBy=eb8e2500096, createdName=夏天与十三菇凉, createdTime=Tue Jul 02 13:43:00 CST 2019, time=2019-07-02, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=1587876, encodeId=1a29158e876e7, content=<a href='/topic/show?id=cb1e1006ebd' target=_blank style='color:#2F92EE;'>#ISC#</a>, beContent=null, objectType=article, channel=null, level=null, likeNumber=41, replyNumber=0, topicName=null, topicId=null, topicList=[TopicDto(id=10067, encryptionId=cb1e1006ebd, topicName=ISC)], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=173417575755, createdName=yankaienglish, createdTime=Tue Jul 02 13:43:00 CST 2019, time=2019-07-02, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=1628958, encodeId=28ee162895879, content=<a href='/topic/show?id=c27a95e7106' target=_blank style='color:#2F92EE;'>#重大疾病#</a>, beContent=null, objectType=article, channel=null, level=null, likeNumber=36, replyNumber=0, topicName=null, topicId=null, topicList=[TopicDto(id=95771, encryptionId=c27a95e7106, topicName=重大疾病)], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=c95421243926, createdName=雕雕, createdTime=Tue Jul 02 13:43:00 CST 2019, time=2019-07-02, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=368722, encodeId=a445368e223a, content=666, beContent=null, objectType=article, channel=null, level=null, likeNumber=94, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=http://cdnapi.center.medsci.cn/medsci/head/2019/01/04/2540fb84decb81d47a7f2868070e6cbd.jpg, createdBy=ed3f2205793, createdName=百草, createdTime=Mon Jul 01 07:14:02 CST 2019, time=2019-07-01, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=368690, encodeId=343b36869086, content=666, beContent=null, objectType=article, channel=null, level=null, likeNumber=74, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=http://cdnapi.center.medsci.cn/medsci/head/2019/01/04/2540fb84decb81d47a7f2868070e6cbd.jpg, createdBy=ed3f2205793, createdName=百草, createdTime=Sun Jun 30 23:07:10 CST 2019, time=2019-06-30, status=1, ipAttribution=)]
    2019-08-21 最帅小男护

    0

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    2019-07-02 yankaienglish
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    2019-07-01 百草

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    2019-06-30 百草

    666

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