# Increasing the Utility of Real-World Data to Inform Public Health Decision Making Through a US-based Private–Public Partnership: 10 Lessons Learned from a Principled Approach to Rapid Pandemic RWE Generation

**Authors:** Nicolle M. Gatto, Elizabeth M. Garry, Melanie Wang, Névine Zariffa, Laura Roe, Aloka Chakravarty, Donna Rivera

PMC · DOI: 10.1007/s43441-025-00748-4 · 2025-03-18

## TL;DR

A US-based public-private partnership used real-world data during the pandemic to improve public health decisions and share lessons learned for future health crises.

## Contribution

The paper outlines 10 lessons from a principled approach to rapidly generating real-world evidence during the pandemic.

## Key findings

- A four-phase research process was developed for rapid evidence generation.
- Challenges in evolving clinical landscapes were identified and addressed.
- The approach can inform future public health research using real-world data.

## Abstract

In response to the COVID-19 pandemic, a collaborative public–private partnership was launched to harness evidence from rapidly accruing real-world data (RWD) in various healthcare settings, with the goal of characterizing and understanding COVID-19 in near real-time, by applying rigorous epidemiological methods and defining research best practices. Projects were conducted in 4 phases: Research Planning and Prioritization, Protocol Development, Protocol Implementation, and Results Dissemination. During these projects, areas were identified with a current or future need to enhance existing best practices. This report provides a summary of our research processes, including application of new and existing practices, along with key learnings related to the challenges of conducting research when the clinical landscape is rapidly evolving as was the case during the first year of the COVID-19 pandemic. Such processes and learnings may be helpful to the broader research community when using RWD to understand or address future public health priorities.

The online version contains supplementary material available at 10.1007/s43441-025-00748-4.

## Linked entities

- **Diseases:** COVID-19 (MONDO:0100096)

## Full-text entities

- **Diseases:** COVID-19 (MESH:D000086382)

## Figures

1 figure with captions in the complete paper: https://tomesphere.com/paper/PMC12018611/full.md

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Source: https://tomesphere.com/paper/PMC12018611