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

Jayson S Marwaha; Maren Downing; John Halamka; Amy Abernethy; Joseph B Franklin; Brian Anderson; Isaac Kohane; Kavishwar Wagholikar; John Brownstein; Melissa Haendel; Gabriel A Brat

doi:10.1016/j.hjdsi.2024.100738

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

Healthc (Amst). 2024 Mar 25;12(2):100738. doi: 10.1016/j.hjdsi.2024.100738. Online ahead of print.

Authors

Affiliations

¹ Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA; Department of Surgery, Beth Israel Deaconess Medical Center, Boston, MA, USA.
² Department of Surgery, Beth Israel Deaconess Medical Center, Boston, MA, USA; Campbell University School of Osteopathic Medicine, Lillington, NC, USA.
³ Mayo Clinic Platform, USA.
⁴ Verily Life Sciences LLC, USA.
⁵ The MITRE Corporation, USA.
⁶ Harvard Medical School, USA.
⁷ University of Colorado Anschutz Medical Campus School of Medicine, USA.
⁸ Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA; Department of Surgery, Beth Israel Deaconess Medical Center, Boston, MA, USA. Electronic address: gbrat@bidmc.harvard.edu.

PMID: 38531228
DOI: 10.1016/j.hjdsi.2024.100738

Abstract

The COVID-19 pandemic generated tremendous interest in using real world data (RWD). Many consortia across the public and private sectors formed in 2020 with the goal of rapidly producing high-quality evidence from RWD to guide medical decision-making, public health priorities, and more. Experiences were gathered from five large consortia on rapid multi-institutional evidence generation during the COVID-19 pandemic. Insights have been compiled across five dimensions: consortium composition, governance structure and alignment of priorities, data sharing, data analysis, and evidence dissemination. The purpose of this piece is to offer guidance on building large-scale multi-institutional RWD analysis pipelines for future public health issues. The composition of each consortium was largely influenced by existing collaborations. A central set of priorities for evidence generation guided each consortium, however different approaches to governance emerged. Challenges surrounding limited access to clinical data due to various contributors were overcome in unique ways. While all consortia used different methods to construct and analyze patient cohorts ranging from centralized to federated approaches, all proved effective for generating meaningful real-world evidence. Actionable recommendations for clinical practice and public health agencies were made from translating insights from consortium analyses. Each consortium was successful in rapidly answering questions about COVID-19 diagnosis and treatment despite all taking slightly different approaches to data sharing and analysis. Leveraging RWD, leveraged in a manner that applies scientific rigor and transparency, can complement higher-level evidence and serve as an important adjunct to clinical trials to quickly guide policy and critical care, especially for a pandemic response.

Keywords: COVID-19; Consortia; Pandemic response; Rapid evidence generation; Real world data.