Evidence map›Paper›PMID 40917584›Full record

Reviewnpj health systems2025

Reimagining clinical AI: from clickstreams to clinical insights with EHR use metadata.

Chao Yan, Xinmeng Zhang, Thomas G Kannampallil, Julia Adler-Milstein, You Chen

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in npj health systems, 2025. 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. 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

5 authors.

Chao Yan *Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN USA.
Xinmeng Zhang *Department of Computer Science, Vanderbilt University, Nashville, TN USA.
Thomas G KannampallilDepartment of Anesthesiology, Washington University School of Medicine, St. Louis, MO USA.
Julia Adler-MilsteinDivision of Clinical Informatics & Digital Transformation, Department of Medicine, University of California San Francisco, San Francisco, CA USA.
You ChenDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN USA.

Funding

Discovering Care Coordination Practice Patterns in the EMR: Interpretation and Impact on Patient OutcomesR01LM012854 · NLM · VANDERBILT UNIVERSITY MEDICAL CENTER · PI CHEN, YOU · 2019 to 2022
$1.5M
Generative AI for synthetic data: A framework to expand health data reach for research and ensure algorithmic fairnessK99LM014428 · NLM · VANDERBILT UNIVERSITY MEDICAL CENTER · PI YAN, CHAO · 2024 to 2025
$174k
AHRQ HHS R01 HS029020NLM NIH HHS K99 LM014428NLM NIH HHS R01 LM012854
6 · The paper itself

Abstract

Most clinical AI solutions center on patient data-particularly those from electronic health records (EHR)-while overlooking the clinician activities that shape care and signal patient outcomes. EHR use metadata, which capture fine-grained clinician-EHR interactions, represent a powerful yet underutilized resource that complements patient data. This perspective highlights the opportunity of integrating EHR use metadata with patient data to advance the development, evaluation, and real-world impact of clinical AI.

Indexed as

Computer scienceHealth careSoftware

Identifiers

PMID40917584
PMCPMC12411277

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.