Evidence map›Paper›PMID 41988463›Full record

ArticleLearning health systems2026

Twenty-First Century Data Systems: Evolving Cancer Registries to a Learning Health System.

Peter P Yu, W Scott Campbell, Eric B Durbin, Lawrence N Shulman, Jeremy L Warner

Abstract read
In one paragraph

Article in Learning health systems, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

5 authors.

Peter P YuHartford HealthCare Cancer Institute Hartford Connecticut USA.
W Scott CampbellUniversity of Nebraska Medical Center Omaha Nebraska USA.
Eric B DurbinKentucky Cancer Registry, Markey Cancer Center, University of Kentucky Lexington Kentucky USA.
Lawrence N ShulmanAbramson Cancer Center, University of Pennsylvania Philadelphia Pennsylvania USA.
Jeremy L WarnerBrown University Warren Alpert School of Medicine Providence Rhode Island USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Oncology is a data-rich environment reflecting the increasing incidence of cancer in the US aging population, transformation of cancer into a chronic disease due to advances in treatment, and the emergence of new data categories such as genomics. Concomitantly, healthcare systems are challenged to meet regulatory and voluntary reporting of cancer data to support government, quality certification, research and strategic partnership needs. Materials and Methods: The National Academies of Science, Engineering, and Medicine organized a workshop entitled "Enabling 21st-century applications for cancer surveillance through enhanced registries and beyond" with representation from NCI Comprehensive Cancer Centers, oncology and medical informatics professional societies, industry, CDC, NCI, and patient advocacy groups. Results: The proliferation of cancer registries has resulted in heterogeneity in data vocabularies and data transport standards. Federal policy is complementing private initiatives to modernize cancer data architecture that would support a Learning Health System. However, business models are needed to provide sustained investments in data infrastructure. Conclusion: A computational approach to cancer registries would set the stage for interoperability and data sharing within a learning health ecosystem. Healthcare systems need to invest in their data infrastructure to improve data quality and adaptation of new data sources such as genomics and wearables. The ecosystem must evolve business models to sustain these investments.

Indexed as

learning health systemneoplasmsregistries

Identifiers

PMID41988463
PMCPMC13078859

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.