The Challenges and Lessons Learned Building a New UK Infrastructure for Finding and Accessing Population-WideCOVID-19 Data for Research and Public Health Analysis: The CO-CONNECT Project

被引：2

作者：

Jefferson, Emily ^{[1
,2
]}

Milligan, Gordon ^{[3
]}

Johnston, Jenny ^{[3
]}

Mumtaz, Shahzad

Cole, Christian ^{[1
,3
]}

Best, Joseph ^{[4
]}

Giles, Thomas Charles ^{[4
]}

Cox, Samuel ^{[4
]}

Masood, Erum ^{[3
]}

Horban, Scott ^{[3
]}

Urwin, Esmond ^{[4
]}

Beggs, Jillian ^{[5
]}

Chuter, Antony ^{[5
]}

Reilly, Gerry ^{[2
]}

Morris, Andrew ^{[2
]}

Seymour, David ^{[2
]}

Hopkins, Susan ^{[6
]}

Sheikh, Aziz ^{[7
]}

Quinlan, Philip ^{[4
]}

机构：

[1] Univ Dundee, Sch Med, Populat Hlth & Genom, Dundee, Scotland

[2] Hlth Data Res UK, London, England

[3] Univ Dundee, Hlth Informat Ctr, Sch Med, Dundee, Scotland

[4] Univ Nottingham, Sch Med, Nottingham, England

[5] Patient & Publ Representat, London, England

[6] Publ Hlth England, London, England

[7] Univ Edinburgh, Usher Inst, Ctr Populat Hlth Sci, Edinburgh, Scotland

来源：

JOURNAL OF MEDICAL INTERNET RESEARCH | 2024年 / 26卷

关键词：

COVID-19; infrastructure; trusted research environments; safe havens; feasibility analysis; cohort discovery; federated analytics; federated discovery; lessons learned; population wide; data; public health; analysis; CO-CONNECT; challenges; data transformation;

D O I：

10.2196/50235

中图分类号：

R19 [保健组织与事业（卫生事业管理）];

学科分类号：

摘要：

The COVID-19-Curated and Open Analysis and Research Platform (CO-CONNECT) project worked with 22 organizations across the United Kingdom to build a federated platform, enabling researchers to instantaneously and dynamically query federated datasets to find relevant data for their study. Finding relevant data takes time and effort, reducing the efficiency of research. Although data controllers could understand the value of such a system, there were significant challenges and delays in setting up the platform in response to COVID-19. This paper aims to present the challenges and lessons learned from the CO-CONNECT project to support other similar initiatives in the future. The project encountered many challenges, including the impacts of lockdowns on collaboration, understanding the new architecture, competing demands on people's time during a pandemic, data governance approvals, different levels of technical capabilities, data transformation to a common data model, access to granular-level laboratory data, and how to engage public and patient representatives meaningfully on a highly technical project. To overcome these challenges, we developed a range of methods to support data partners such as explainer videos; regular, short, "touch base" videoconference calls; drop-in workshops; live demos; and a standardized technical onboarding documentation pack. A 4-stagedata governance process emerged. The patient and public representatives were fully integrated team members. Persistence, patience, and understanding were key. We make 8 recommendations to change the landscape for future similar initiatives. The new architecture and processes developed are being built upon for non-COVID-19-related data, providing an infrastructural legacy.

引用

页数：11