Clinical Informatics & Health Outcomes Research Group, Nuffield Department of Primary Care Health Sciences, University of Oxford, UK.
Royal College of General Practitioners Research and Surveillance Centre, 30 Euston Square, London, UK.
Stud Health Technol Inform. 2022 Aug 31;298:137-141. doi: 10.3233/SHTI220923.
The Oxford-Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC) is one of Europe's oldest sentinel systems, providing sentinel surveillance since 1967. We report the interdisciplinary informatics required to run such a system. We used the Donabedian framework to describe the interdisciplinary informatics roles that support the structures, processes and outcomes of the RSC. Over the course of the COVID-19 pandemic University, RCGP, information technology specialists, SQL developers, analysts, practice liaison team, network member primary care providers, and their registered patients have nearly quadrupled the size of the RSC from working with 5 million to 19 million peoples pseudonymised health data. We have produced outputs used by the UK Health Security Agency to describe the epidemiology of COVID-19 and report vaccine effectiveness. We have also supported a trial of community-based therapies for COVID-19 and other observational studies. The home of the primary care sentinel surveillance network is with a clinical informatics research group. Interdisciplinary informatics teamwork was required to support primary care sentinel surveillance; such teams can accelerate the scale, scope and digital maturity of surveillance systems as demonstrated by the RSC across the COVID-19 pandemic.
牛津-皇家全科医师学院(RCGP)研究与监测中心(RSC)是欧洲历史最悠久的哨点系统之一,自 1967 年以来一直提供哨点监测。我们报告了运行此类系统所需的跨学科信息学。我们使用 Donabedian 框架来描述支持 RSC 结构、过程和结果的跨学科信息学角色。在 COVID-19 大流行期间,大学、RCGP、信息技术专家、SQL 开发人员、分析师、实践联络团队、网络成员初级保健提供者及其注册患者将 RSC 的规模从 500 万人扩大到 1900 万人,使用了化名健康数据。我们已经生成了英国卫生安全局用于描述 COVID-19 流行病学和报告疫苗有效性的输出。我们还支持了 COVID-19 社区治疗试验和其他观察性研究。初级保健哨点监测网络的所在地是临床信息学研究小组。跨学科信息学团队合作是支持初级保健哨点监测所必需的;正如 RSC 在整个 COVID-19 大流行期间所展示的那样,这样的团队可以加速监测系统的规模、范围和数字化成熟度。