Mobilizing data during a crisis: Building rapid evidence pipelines using multi-institutional real world data

Area of Science:

• Public Health
• Data Science
• Epidemiology

Background:

• The COVID-19 pandemic highlighted the need for rapid evidence generation using real-world data (RWD).
• Numerous public and private consortia formed in 2020 to leverage RWD for medical decision-making and public health.
• Experiences from five large consortia were analyzed to provide insights into multi-institutional RWD analysis.

Purpose of the Study:

• To offer guidance on establishing large-scale, multi-institutional RWD analysis pipelines for future public health challenges.
• To share lessons learned from consortia that rapidly generated evidence during the COVID-19 pandemic.
• To inform the development of robust RWD analysis frameworks for emerging health crises.

Main Methods:

• Analysis of experiences across five major consortia focused on RWD evidence generation.
• Examination of consortium composition, governance, data sharing, analysis approaches, and evidence dissemination.
• Compilation of insights across five key dimensions of collaborative RWD analysis.

Main Results:

• Consortium composition was often based on existing collaborations, with varied governance structures but aligned priorities.
• Challenges in accessing clinical data were overcome through diverse strategies.
• Both centralized and federated data analysis approaches proved effective for generating meaningful RWD insights.
• Actionable recommendations for clinical practice and public health were derived from consortium findings.

Conclusions:

• Consortia successfully generated timely evidence on COVID-19 diagnosis and treatment using RWD.
• RWD analysis, when conducted with scientific rigor and transparency, complements clinical trials and informs policy.
• Leveraging RWD is crucial for effective pandemic response and guiding critical care decisions.