Evidence map›Paper›PMID 40776063›Full record

ArticleStudies in health technology and informatics2025

Exploring Task Patterns in EHR Workflows Using Action Sequence Embedding and Graph-Based Analysis.

Seunghwan Kim, Thomas Kannampallil, Brett D Wick, A Jay Holmgren, Robert Thombley, Sunny S Lou

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Studies in health technology and informatics, 2025. 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.

Seunghwan KimRoy and Diana Vagelos Division of Biology and Biomedical Sciences, Washington University St. Louis, Saint Louis, USA.
Thomas KannampallilInstitute for Informatics, Data Science, and Biostatistics (I2DB), Washington University St. Louis, Saint Louis, USA.
Brett D WickDepartment of Mathematics, Washington University St. Louis, Saint Louis, USA.
A Jay HolmgrenDivision of Clinical Informatics and Digital Transformation, Department of Medicine, University of California, San Francisco, San Francisco, CA, USA.
Robert ThombleyDivision of Clinical Informatics and Digital Transformation, Department of Medicine, University of California, San Francisco, San Francisco, CA, USA.
Sunny S LouInstitute for Informatics, Data Science, and Biostatistics (I2DB), Washington University St. Louis, Saint Louis, USA.

Funding

Intelligent Clinical Decision Support for Perioperative Blood ManagementK23HL166880 · NHLBI · WASHINGTON UNIVERSITY · PI Sunny S. Lou · 2024 to 2026
$521k
NHLBI NIH HHS K23 HL166880
6 · The paper itself

Abstract

This study investigates clinician workflows in electronic health records (EHR) using a novel combination of context-based embedding and graph-based dimensionality reduction techniques to EHR-based audit log sequences. We identified distinct clinical task groups, suggesting the potential for semi-automated, unsupervised methods for characterizing EHR-based workflow patterns.

Indexed as

Computer GraphicsElectronic Health RecordsTask Performance and AnalysisWorkflowWorkloadAlgorithmsaction sequenceaudit logsclinical workflowcontext embeddingElectronic health recordstask identificationunsupervised learning

Identifiers

PMID40776063
PMCPMC13047917

What OpenQuestion holds

Textmetadata
LicenceTDM
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.