Evidence map›Paper›PMID 40896380›Full record

ArticleHealth affairs scholar2025

Time to use large-scale biobank databases in health policy and public health research.

José A Pagán, Vivian Hsing-Chun Wang, Hannah Sur

Abstract read
In one paragraph

Article in Health affairs scholar, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Review
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

3 authors.

José A PagánDepartment of Public Health Policy and Management, School of Global Public Health, New York University, New York, NY 10003, United States.ORCID https://orcid.org/0000-0002-8915-9602
Vivian Hsing-Chun WangCenter for Population and Health Services Research, Department of Foundations of Medicine, NYU Grossman Long Island School of Medicine, Mineola, NY 11501, United States.ORCID https://orcid.org/0000-0002-5638-204X
Hannah SurDepartment of Public Health Policy and Management, School of Global Public Health, New York University, New York, NY 10003, United States.ORCID https://orcid.org/0009-0001-5056-7203

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Large-scale biobank databases link data from thousands of participants and multiple sources such as electronic health records, surveys, imaging, and biomarkers. These data infrastructure research initiatives have the potential to inform health care and public health solutions that can address the needs of different populations, facilitate cross-sector collaboration, and improve the overall responsiveness of health care and public health systems. Despite this potential, large-scale biobanks are severely underutilized to answer health policy and public health research questions. Part of the reason is that information available in these data sources is usually collected for purposes such as improving health care within an integrated health care delivery system or advancing precision medicine. Still, the depth and breadth of these data collection efforts around the world together with advances in data science and artificial intelligence provide new opportunities to answer important health policy and public health questions using large-scale biobank data.

Indexed as

health policylarge-scale biobank databasespublic health

Identifiers

PMID40896380
PMCPMC12393043

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.