Evidence map›Paper›PMID 40102361›Full record

ArticleTherapeutic innovation & regulatory science2025

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.

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

Abstract read
In one paragraph

Article in Therapeutic innovation & regulatory science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Nicolle M GattoAetion, Inc, 5 Pennsylvania Plaza, New York, NY, 10001, USA. nicolle.gatto@aetion.com.
Elizabeth M GarryAetion, Inc, 5 Pennsylvania Plaza, New York, NY, 10001, USA.
Melanie WangAetion, Inc, 5 Pennsylvania Plaza, New York, NY, 10001, USA.
Névine ZariffaNMD Group Inc, Bala Cynwyd, PA, USA.
Laura RoeMMCi, Verily, San Francisco, CA, USA.
Aloka Chakravarty *U.S. Food and Drug Administration, Silver Spring, MD, USA. alokac@gmail.com.
Donna Rivera *U.S. Food and Drug Administration, Silver Spring, MD, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

COVID-19Decision MakingPublic HealthPublic-Private Sector PartnershipsHumansPandemicsSARS-CoV-2United StatesCOVID-19Epidemiologic methodsPandemic preparednessReal-world dataReal-world evidenceSARS-CoV-2

Identifiers

PMID40102361
PMCPMC12018611

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.