Evidence map›Paper›PMID 32011317›Full record

ReviewThe Journal of clinical investigation2020

Opportunities and challenges in using real-world data for health care.

Vivek A Rudrapatna, Atul J Butte

Registry-linked trialAbstract readReview
In one paragraph

Review in The Journal of clinical investigation, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06018753 (Umbrella Study for Analysis of Data Related to Patients With Cancer), which is not on this map. Cited by 102 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
102citing papers in PubMed, 3 pooled it
–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.

NCT06018753 completednot on this mapstarted 2023, after this paper: background citation

Umbrella Study for Analysis of Data Related to Patients With Cancer

TypeobservationalSponsorTempus AIRan2023 to 2025Enrolled77ConditionsCancer
3 · Its place in the literature

Who cites it

102 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
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  6. Review
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  9. Recent Advances in AI and GenAI for Health Informatics.Healthcare (Basel, Switzerland) · 2026
    Review
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42 more citing papers are in PubMed but not listed here.

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

2 authors.

Vivek A RudrapatnaBakar Computational Health Sciences Institute.
Atul J ButteBakar Computational Health Sciences Institute.

Funding

Clinical and Translational Science InstituteUL1TR001872 · NCATS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI COLLARD, HAROLD R, JACOBY, VANESSA · 2016 to 2025
$112.1M
NRSA Training CoreTL1TR001871 · NCATS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI KANAYA, ALKA M., SOMSOUK, MA · 2016 to 2025
$10.1M
TRAINING PROGRAM IN DISGESTIVE DISEASES AND NUTRITIONT32DK007007 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI AVERIL I MA · 1986 to 2026
$6.4M
NCATS NIH HHS TL1 TR001871NCATS NIH HHS UL1 TR001872NIDDK NIH HHS T32 DK007007
6 · The paper itself

Abstract

Real-world data (RWD) continue to emerge as a new source of clinical evidence. Although the best-known use case of RWD has been in drug regulation, RWD are being generated and used by many other parties, including biopharmaceutical companies, payors, clinical researchers, providers, and patients. In this Review, we describe 21 potential uses for RWD across the spectrum of health care. We also discuss important challenges and limitations relevant to the translation of these data into evidence.

Indexed as

Delivery of Health CareEvidence-Based PracticeHumans

Identifiers

PMID32011317
PMCPMC6994109

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

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.