Evidence map›Paper›PMID 42791307›Full record

Reviewnpj health systems2026

Patient-governed agentic health data exchange.

Steve Drew, Guojun Tang, Zainab Saad, Jiayu Zhou, Yong Chen, Fei Wang

Abstract readReview
In one paragraph

Review in npj health systems, 2026. 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

6 authors.

Steve DrewDepartment of Electrical and Software Engineering, University of Calgary, Calgary, AB, Canada. steve.drew@ucalgary.ca.
Guojun TangDepartment of Electrical and Software Engineering, University of Calgary, Calgary, AB, Canada.
Zainab SaadDepartment of Electrical and Software Engineering, University of Calgary, Calgary, AB, Canada.
Jiayu ZhouSchool of Information, University of Michigan, Ann Arbor, MI, USA.
Yong ChenPerelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Fei WangWeill Cornell Medicine, Cornell University, New York, NY, USA.

Funding

Natural Sciences and Engineering Research Council of Canada RGPIN-2024-03954
6 · The paper itself

Abstract

Health data exchange remains constrained by fragmentation, consent burden, limited auditability, and weak incentives. We propose STARFISH, a patient-governed agentic framework where personal health agents manage granular permissions, while institutional research agents request data or execute privacy-preserving analyses. Cryptographically verifiable mandates, automated compliance, and optional benefit sharing align incentives while preserving autonomy. Agentic workflows could accelerate trials and safety surveillance, enabling trustworthy, scalable, and participatory digital health research ecosystems.

Identifiers

PMID42791307
PMCPMC13614945

What OpenQuestion holds

Textmetadata
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.