TY - JOUR
T1 - The Challenges and Lessons Learned Building a New UK Infrastructure for Finding and Accessing Population-Wide COVID-19 Data for Research and Public Health Analysis
T2 - The CO-CONNECT Project
AU - Jefferson, Emily
AU - Milligan, Gordon
AU - Johnston, Jenny
AU - Mumtaz, Shahzad
AU - Cole, Christian
AU - Best, Joseph
AU - Giles, Thomas Charles
AU - Cox, Samuel
AU - Masood, Erum
AU - Horban, Scott
AU - Urwin, Esmond
AU - Beggs, Jillian
AU - Chuter, Antony
AU - Reilly, Gerry
AU - Morris, Andrew
AU - Seymour, David
AU - Hopkins, Susan
AU - Sheikh, Aziz
AU - Quinlan, Philip
N1 - Publisher Copyright:
© 2024 JMIR Publications Inc.. All rights reserved.
PY - 2024
Y1 - 2024
N2 - 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-stage data 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.
AB - 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-stage data 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.
KW - CO-CONNECT
KW - COVID-19
KW - analysis
KW - challenges
KW - cohort discovery
KW - data
KW - data transformation
KW - feasibility analysis
KW - federated analytics
KW - federated discovery
KW - infrastructure
KW - lessons learned
KW - population wide
KW - public health
KW - safe havens
KW - trusted research environments
UR - http://www.scopus.com/inward/record.url?scp=85210285343&partnerID=8YFLogxK
UR - https://www.mendeley.com/catalogue/03d7a8f5-f7ad-3894-9d4f-cfdd8a5764f2/
U2 - 10.2196/50235
DO - 10.2196/50235
M3 - Review article
C2 - 39566065
AN - SCOPUS:85210285343
SN - 1438-8871
VL - 26
JO - Journal of Medical Internet Research
JF - Journal of Medical Internet Research
IS - 1
M1 - e50235
ER -