A large linked data platform to inform the COVID-19 response in British Columbia: The BC COVID-19 Cohort.

IF 1.6 Q3 HEALTH CARE SCIENCES & SERVICES International Journal of Population Data Science Pub Date : 2022-08-25 DOI:10.23889/ijpds.v7i3.2095
J. Wilton, Jalud Abdulmenan, M. Chong, A. Becerra, Mike Coss, Marsha Taylor, O. Djurdjev, D. Rasali, H. Sbihi, M. Krajden, A. Flatt, Seyed Ali Mussavi Rizi, N. Janjua
{"title":"A large linked data platform to inform the COVID-19 response in British Columbia: The BC COVID-19 Cohort.","authors":"J. Wilton, Jalud Abdulmenan, M. Chong, A. Becerra, Mike Coss, Marsha Taylor, O. Djurdjev, D. Rasali, H. Sbihi, M. Krajden, A. Flatt, Seyed Ali Mussavi Rizi, N. Janjua","doi":"10.23889/ijpds.v7i3.2095","DOIUrl":null,"url":null,"abstract":"ObjectivesThe COVID-19 pandemic has necessitated access to large health system datasets to inform the public health response. To meet this need, the Provincial Health Services Authority and the British Columbia (BC) Ministry of Health collaborated to create a population-based platform that integrates COVID-19 datasets with sociodemographic and administrative health data. \nApproachA BC COVID Data Library proof-of-concept was created as a cloud-based, dynamic platform composed of de-identified datasets. The BC COVID-19 Cohort (BCC19C) represents a subset composed of people accessing COVID-19 health services (e.g., testing, vaccination) and linked health histories. Provincial COVID-19 datasets are updated daily and include COVID-19 lab tests, case surveillance, vaccinations and hospitalizations/deaths. These can be linked to administrative data holdings for the BC population, which are updated weekly/monthly and include vital statistics, medications, hospital admissions, medical visits, among others. A patient matching algorithm creates unique patient keys that allows the same individual to be linked across datasets. \nResultsThe BCC19C has been used provincially to 1) support ongoing surveillance, reporting, and modelling of COVID-19; 2) describe and characterize the epidemiology of COVID-19; and 3) inform acute care planning, public health interventions and health care services in BC. Ongoing and completed BCC19C analyses include assessment of vaccine safety, vaccine effectiveness, and characteristics associated with infection and severe outcomes; use of medical visit data for syndromic surveillance and monitoring of unintended outcomes of the pandemic (e.g., mental health visits); and characterization of long-COVID. Availability of linked administrative data holdings has been crucial for identifying non-COVID control groups, measuring sociodemographics and co-morbidities, and complementing COVID-19 datasets for more complete capture of health outcomes (e.g., deaths, hospitalizations). \nConclusionsThe large scope/breadth and timeliness of the linkable datasets integrated within the COVID Data Library and the BCC19C has supported the public health response in BC. Additional linkage to other data sources will further strengthen this data platform.","PeriodicalId":36483,"journal":{"name":"International Journal of Population Data Science","volume":" ","pages":""},"PeriodicalIF":1.6000,"publicationDate":"2022-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Population Data Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23889/ijpds.v7i3.2095","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
引用次数: 1

Abstract

ObjectivesThe COVID-19 pandemic has necessitated access to large health system datasets to inform the public health response. To meet this need, the Provincial Health Services Authority and the British Columbia (BC) Ministry of Health collaborated to create a population-based platform that integrates COVID-19 datasets with sociodemographic and administrative health data. ApproachA BC COVID Data Library proof-of-concept was created as a cloud-based, dynamic platform composed of de-identified datasets. The BC COVID-19 Cohort (BCC19C) represents a subset composed of people accessing COVID-19 health services (e.g., testing, vaccination) and linked health histories. Provincial COVID-19 datasets are updated daily and include COVID-19 lab tests, case surveillance, vaccinations and hospitalizations/deaths. These can be linked to administrative data holdings for the BC population, which are updated weekly/monthly and include vital statistics, medications, hospital admissions, medical visits, among others. A patient matching algorithm creates unique patient keys that allows the same individual to be linked across datasets. ResultsThe BCC19C has been used provincially to 1) support ongoing surveillance, reporting, and modelling of COVID-19; 2) describe and characterize the epidemiology of COVID-19; and 3) inform acute care planning, public health interventions and health care services in BC. Ongoing and completed BCC19C analyses include assessment of vaccine safety, vaccine effectiveness, and characteristics associated with infection and severe outcomes; use of medical visit data for syndromic surveillance and monitoring of unintended outcomes of the pandemic (e.g., mental health visits); and characterization of long-COVID. Availability of linked administrative data holdings has been crucial for identifying non-COVID control groups, measuring sociodemographics and co-morbidities, and complementing COVID-19 datasets for more complete capture of health outcomes (e.g., deaths, hospitalizations). ConclusionsThe large scope/breadth and timeliness of the linkable datasets integrated within the COVID Data Library and the BCC19C has supported the public health response in BC. Additional linkage to other data sources will further strengthen this data platform.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
为不列颠哥伦比亚省新冠肺炎应对提供信息的大型关联数据平台:不列颠哥伦比亚省新冠肺炎队列。
目的新冠肺炎大流行需要访问大型卫生系统数据集,为公共卫生应对提供信息。为了满足这一需求,省卫生服务局和不列颠哥伦比亚省卫生部合作创建了一个基于人口的平台,该平台将新冠肺炎数据集与社会人口统计和行政卫生数据相结合。方法不列颠哥伦比亚省新冠肺炎数据库的概念验证是作为一个基于云的动态平台创建的,由未识别的数据集组成。BC新冠肺炎队列(BCC19C)代表了一个由获得新冠肺炎医疗服务(如检测、疫苗接种)和相关健康史的人组成的子集。省级新冠肺炎数据集每天更新,包括新冠肺炎实验室检测、病例监测、疫苗接种和住院/死亡。这些数据可以与不列颠哥伦比亚省人口的行政数据存储联系起来,这些数据每周/每月更新,包括生命统计数据、药物、住院人数、医疗就诊等。患者匹配算法创建唯一的患者密钥,允许同一个人在数据集之间链接。结果BCC19C已在省级用于1)支持新冠肺炎的持续监测、报告和建模;2) 描述和描述新冠肺炎的流行病学;以及3)为不列颠哥伦比亚省的急性护理规划、公共卫生干预和卫生保健服务提供信息。正在进行和完成的BCC19C分析包括对疫苗安全性、疫苗有效性以及与感染和严重后果相关的特征的评估;使用医疗就诊数据进行症状监测和监测疫情的意外结果(如心理健康就诊);以及长期新冠肺炎的特征。相关行政数据的可用性对于识别非COVID控制群体、测量社会人口统计和合并症以及补充新冠肺炎数据集以更完整地获取健康结果(如死亡、住院)至关重要。结论整合在COVID数据库和BCC19C内的可链接数据集的大范围/广度和及时性支持了不列颠哥伦比亚省的公共卫生应对措施。与其他数据源的额外链接将进一步加强这一数据平台。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
CiteScore
2.50
自引率
0.00%
发文量
386
审稿时长
20 weeks
期刊最新文献
Defining a low-risk birth cohort: a cohort study comparing two perinatal data sets in Ontario, Canada. Data resource profile: nutrition data in the VA million veteran program. Deprivation effects on length of stay and death of hospitalised COVID-19 patients in Greater Manchester. Variation in colorectal cancer treatment and outcomes in Scotland: real world evidence from national linked administrative health data. Examining the quality and population representativeness of linked survey and administrative data: guidance and illustration using linked 1958 National Child Development Study and Hospital Episode Statistics data
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1