Evidence map›Paper›PMID 40747456›Full record

ArticleJAMIA open2025

VetDash: a clinical dashboard for enhancing measurement-based care in veteran health.

Santiago Allende, Hayley S Sullivan, Peter J Bayley

Abstract read
In one paragraph

Article in JAMIA open, 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

3 authors.

Santiago AllendeWar Related Illness and Injury Study Center, Palo Alto VA Medical Center, Palo Alto, CA 94304-1290, United States.
Hayley S SullivanWar Related Illness and Injury Study Center, Palo Alto VA Medical Center, Palo Alto, CA 94304-1290, United States.
Peter J BayleyWar Related Illness and Injury Study Center, Palo Alto VA Medical Center, Palo Alto, CA 94304-1290, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: Measurement-based care (MBC) improves clinical decision-making but remains underutilized in the Veterans Health Administration due to barriers such as provider awareness, time constraints, and user-experience limitations. This study describes the development of the War Related Illness and Injury Study Center Veteran Dashboard (VetDash), a patient-level clinical dashboard designed to integrate the VA's Materials and Methods: VetDash was developed using R Shiny, utilizing data from the WRIISC Clinical Intake Packet Database. It integrates patient-reported health data and military history into a dashboard hosted on a Linux-based Shiny Server within the VA's intranet. Results: VetDash includes four modules: Patient Characteristics, Patient Health Symptoms, Patient Exposures, and Patient Self-Report Measures. Providers can visualize patient-reported symptoms, military exposures, and self-report measures, and compare patients to provider-defined cohorts. Discussion and Conclusion: VetDash facilitates MBC integration into the clinical workflow, potentially improving personalized patient care. Future research should evaluate its impact on clinical decisions, outcomes, and explore further enhancements.

Indexed as

chronic multisymptom illnessdashboardmeasurement-based careR Shinyveteran health

Identifiers

PMID40747456
PMCPMC12313089

What OpenQuestion holds

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Registered trials

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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.