Evidence map›Paper›PMID 41343776›Full record

ArticleJMIR formative research2025

A Novel Primary Care Planning Informatics Tool Informed by Data-Driven Multimorbidity Grouping: User-Centered Design and Feasibility Testing.

Linnaea Schuttner, Karin Daniels, Srinidhi Venkatesh, Franya Hutchins, Karley Atchison, Rebecca Piegari, Timothy Bober, Xinhua Zhao, Ann-Marie Rosland

Abstract read
In one paragraph

Article in JMIR formative research, 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

9 authors.

Linnaea SchuttnerHealth Services Research & Development, VA Puget Sound Health Care System, 1660 S Columbian Way, Seattle, WA, 98108, United States, 1 2062776126.ORCID 0000-0003-2289-0684
Karin DanielsVA Center for Health Equity Research and Promotion (CHERP), VA Pittsburgh Healthcare System, Pittsburgh, PA, United States.ORCID 0000-0003-0204-3285
Srinidhi VenkateshDepartment of Medicine and Caring for Complex Chronic Conditions Research Center, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United States.ORCID 0000-0001-8227-0933
Franya HutchinsVA Center for Health Equity Research and Promotion (CHERP), VA Pittsburgh Healthcare System, Pittsburgh, PA, United States.ORCID 0000-0002-8797-2632
Karley AtchisonVA Center for Health Equity Research and Promotion (CHERP), VA Pittsburgh Healthcare System, Pittsburgh, PA, United States.ORCID 0009-0000-4211-4362
Rebecca PiegariAnalytics and Performance Integration, Veterans Health Administration, Washington, DC, United States.ORCID 0009-0008-1754-6559
Timothy BoberDepartment of Medicine and Caring for Complex Chronic Conditions Research Center, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United States.ORCID 0000-0002-5313-2387
Xinhua ZhaoVA Center for Health Equity Research and Promotion (CHERP), VA Pittsburgh Healthcare System, Pittsburgh, PA, United States.ORCID 0009-0003-5350-9986
Ann-Marie RoslandVA Center for Health Equity Research and Promotion (CHERP), VA Pittsburgh Healthcare System, Pittsburgh, PA, United States.ORCID 0000-0002-5809-5861

Funding

AHRQ HHS K12 HS026369HSRD VA IK2 HX003462
6 · The paper itself

Abstract

Background: Patients with multimorbidity have complex health care needs and are at high risk for adverse health outcomes. Primary care teams need tools to effectively and proactively plan care for these patients. We developed VET-PATHS (Veteran Panel Management Tool for High-Risk Subgroups), a novel care planning informatics tool for complex primary care patients. VET-PATHS groups patients by chronic condition via latent class analysis of electronic health record data, then jump-starts care planning by suggesting "care steps" based on data-driven high-priority care for the group. Objective: The study aimed to iteratively adapt VET-PATHS with user input, then test feasibility and acceptability by frontline primary care teams for empaneled patients at high risk. Methods: Three rounds of user-centered design sessions with 17 primary care providers and registered nurses at 5 sites from 2019 to 2021 were conducted to obtain feedback on the VET-PATHS layout, content, and user interface. Feedback was summarized into 4 user experience domains (useful, desirable, credible, and usable), leading to progressively updated prototypes. After the national tool release, we conducted a pilot intervention study in 2023-2024 with 6 primary care teams at 4 sites using VET-PATHS during asynchronous regular meetings. Tool use and resulting care plans were assessed by templated observation during meetings, postpilot chart review, and administrative data. Individual qualitative interviews were analyzed by rapid template analysis for feasibility, acceptability, and utility. Results: User-centered feedback led to updated tool content, context (eg, use in proactive panel management), targeted users (eg, focusing on primary care providers), and display layout. Pilot teams used VET-PATHS over 4 to 8 weekly meetings (mean length 24, range 16-49 min), actively reviewing 80% (280/351) of empaneled patients at high risk visible in the tool. Tool use prompted 127 new actions for 91 unique patients (33% of patients reviewed) and documentation of >1 new care plan for 19% of patients reviewed. Common actions included requests to return to the clinic (n=34, 27%), referrals (n=25, 20%), or vaccinations (n=24, 19%). Of the 127 actions planned, 53 (42%) were received by patients. Difference-in-difference trends for acute hospitalizations declined post pilot, while outpatient utilization was stable or increased for pilot team patients compared to all patients at high risk at pilot sites (per-patient counts: acute hospitalizations -0.15; primary care visits 0.00; mental health visits 0.99). Four generalist teams (n=11 interviews) described higher acceptability. Two "focused" teams with more homogenous panels, for example, substance use disorder (n=3 interviews), found care steps less useful. Teams described how VET-PATHS improved efficiency of care planning through automated patient grouping and identification of care gaps and increased multidisciplinary involvement. Conclusions: User-centered improvements to VET-PATHS were designed to help clinicians process and use complex information about patient multimorbidity to efficiently create new care plans. Subsequently, VET-PATHS was acceptable and feasible to frontline primary care teams, particularly with more general patient panels, and led to concrete changes to clinical care delivery.

Indexed as

MultimorbidityPatient Care PlanningPrimary Health CareUser-Centered DesignElectronic Health RecordsFeasibility StudiesFemaleHumansMaleMiddle Agedcare planningcomplex caremultimorbiditypanel managementpopulation healthprimary care

Identifiers

PMID41343776
PMCPMC12677874

What OpenQuestion holds

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LicenceCC BY
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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.