Evidence map›Paper›PMID 41941183›Full record

Observational studyJAMA network open2026

Acute Care Use and Mortality by Tele-Emergency Care Use, Modality, and Clinician Type.

Kathleen Yinran Li, Linda Diem Tran, Liam Rose, Jacqueline M Ferguson, Tracy H Urech, Allison Engstrom Buggaveeti, Anita A Vashi

Abstract readMulticenter StudyObservational Study
In one paragraph

Observational study in JAMA network open, 2026. 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. Bridging Gaps in Acute Care Access for Rural Veterans: The Reach and Impact of VA's Virtual Emergency and Urgent Care Programs.The Journal of rural health : official journal of the American Rural Health Association and the National Rural Health Care Association · 2026
    Article
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

7 authors.

Kathleen Yinran LiDepartment of Emergency Medicine, University of Washington School of Medicine, Seattle.
Linda Diem TranHealth Economics Resource Center, Veterans Affairs Palo Alto Health Care System, Palo Alto, California.
Liam RoseHealth Economics Resource Center, Veterans Affairs Palo Alto Health Care System, Palo Alto, California.
Jacqueline M FergusonCenter for Innovation to Implementation, Palo Alto Veterans Affairs Health Care System, Menlo Park, California.
Tracy H UrechCenter for Innovation to Implementation, Palo Alto Veterans Affairs Health Care System, Menlo Park, California.
Allison Engstrom BuggaveetiStanford Surgery, Policy, Improvement, Research and Education Center, Palo Alto, California.
Anita A VashiCenter for Innovation to Implementation, Palo Alto Veterans Affairs Health Care System, Menlo Park, California.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Importance: While tele-emergency care pilots have demonstrated potential utility as a model for assessing patients with acute concerns without requiring in-person emergency department evaluation, large-scale evaluations are lacking, and important questions regarding implementation remain. Objective: To examine associations between tele-emergency care receipt, modality, and clinician type, and subsequent outcomes. Design, Setting, and Participants: This cohort study included veterans who called the nurse advice line from January 2018 through April 2024 during business hours and were triaged as requiring urgent or emergent evaluation in a national, multicenter setting within the Veterans Health Administration. Exposures: Tele-emergency care vs usual care, tele-emergency care modality (phone vs video), and tele-emergency care clinician type (physician vs advanced practice clinician). Main Outcomes and Measures: The primary outcome was emergency department visit within 7 days, and the secondary outcomes were hospitalization within 7 days and 30-day mortality. Propensity score weighting was applied, and heterogeneous difference-in-differences models were estimated. Results: The study included 2 511 932 nurse advice line calls from 719 028 veterans (mean [SD] age, 62.3 [16.0] years; 627 515 [87.3%] male). After tele-emergency care implementation, 99 994 of eligible nurse calls (17.4%) resulted in a tele-emergency care visit. Tele-emergency care receipt was associated with a lower probability of emergency department visits within 7 days compared with propensity-weighted calls that did not (28.5% vs 45.0%; average treatment effect, -16.5%; 95% CI, -18.6% to -14.4%), with similar associations for hospitalization and no difference in mortality. The average treatment effect was greater for calls triaged as emergent (-22.0%; 95% CI, -24.1% to -19.9%) vs urgent (-5.6%; 95% CI, -8.4% to -2.9%). Minimal differences were observed by tele-emergency care modality or clinician type. At the facility level, tele-emergency care implementation was associated with a small reduction in emergency department visits for emergent calls (average treatment effect, -2.6%; 95% CI, -5.0% to -0.2%). Conclusions and Relevance: In this cohort study, tele-emergency care receipt was associated with lower emergency department use, particularly for higher-acuity calls, regardless of modality or clinician type, though facility-level differences were limited. Broader implementation of tele-emergency care could be a solution for health systems seeking to mitigate emergency department crowding while addressing patients' acute care needs.

Indexed as

Emergency Medical ServicesEmergency Service, HospitalTelemedicineAgedCohort StudiesFemaleHospitalizationHumansMaleMiddle AgedTriageUnited StatesVeterans

Identifiers

PMID41941183
PMCPMC13054618

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.