Evidence map›Paper›PMID 42550717›Full record

ArticleThe western journal of emergency medicine2026

Clinical Characteristics of an Emergency Department-led Asynchronous Care Platform.

Shivam Shah, Ikaasa Suri, Helen Gordan, Nicole Schwartz, Rubayet Hossain, Donald Apakama, Rishi Khakhkhar, Taylor Marren, Benjamin S Abella, Nicholas Gavin and 1 more

Abstract read
In one paragraph

Article in The western journal of emergency medicine, 2026. 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

11 authors.

Shivam ShahIcahn School of Medicine at Mount Sinai, Department of Emergency Medicine, New York, New York.
Ikaasa SuriIcahn School of Medicine at Mount Sinai, Charles Bronfman Institute for Personalized Medicine, New York, New York.
Helen GordanIcahn School of Medicine at Mount Sinai, Charles Bronfman Institute for Personalized Medicine, New York, New York.
Nicole SchwartzIcahn School of Medicine at Mount Sinai, Department of Emergency Medicine, New York, New York.
Rubayet HossainIcahn School of Medicine at Mount Sinai, Department of Emergency Medicine, New York, New York.
Donald ApakamaIcahn School of Medicine at Mount Sinai, Institute for Health Equity Research, New York, New York.
Rishi KhakhkharIcahn School of Medicine at Mount Sinai, Department of Emergency Medicine, New York, New York.
Taylor MarrenIcahn School of Medicine at Mount Sinai, Department of Emergency Medicine, New York, New York.
Benjamin S AbellaIcahn School of Medicine at Mount Sinai, Department of Emergency Medicine, New York, New York.
Nicholas GavinIcahn School of Medicine at Mount Sinai, Department of Emergency Medicine, New York, New York.
Ethan E AbbottIcahn School of Medicine at Mount Sinai, Institute for Health Equity Research, New York, New York.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAsynchronous care has emerged as a promising approach to improving healthcare accessibility while potentially reducing costs, particularly for low-acuity conditions. Our objective was to describe the use patterns, patient characteristics, and short-term clinical outcomes of an emergency department (ED)-led asynchronous care platform managing low-acuity conditions in a large, academic health system.

methodsWe conducted a retrospective cohort study evaluating the Mount Sinai Health System asynchronous care platform for managing urinary tract infections, conjunctivitis, cold sores, vaginal candidiasis, emergency contraception, and oral contraceptive prescriptions between December 2023-October 2024 during an initial rollout period. Individual charts were reviewed by two trained abstractors and two emergency physicians. The primary outcome was any subsequent ED or clinic visit within seven days. Secondary outcomes included change in diagnosis and medication at relevant follow-up visits. We used descriptive statistics to characterize the cohort and outcomes.

resultsDuring the study period, there were 19,204 ED encounters for conditions matching asynchronous care chief complaint categories, of which 343 encounters (1.8%) from 277 unique patients were managed via the asynchronous care platform. The median patient age was 32.6 years (interquartile range IQR 28.3-41.2), and 258 (93.1%) were female. Overall chief complaints included cystitis/urinary complaints in 157 (45.8%) encounters, conjunctivitis/eye complaints in 57 (16.6%), and vaginal/vulvar candidiasis in 96 (28.0%). At the encounter level, 18 (5.2%) were up-triaged from the asynchronous care platform to synchronous virtual urgent care or in-person evaluation after initial screening. We observed the primary outcome of a subsequent ED or clinic visit within seven days in 68 patients (24.5%). Five patients (1.5%; 95% CI, 0.5-3.5%) were identified with a change in diagnosis within the seven-day outcome window, with all diagnostic changes occurring within 1-3 days of the index asynchronous care encounter (median one day).

conclusionIn this single-center study, an asynchronous care platform demonstrated a viable pathway for managing select low-acuity conditions in an urban academic health system. This structured platform, with appropriate triage pathways and low rates of diagnostic discordance, shows promise as a model to expand access to care for select low-acuity complaints.

Indexed as

Emergency Service, HospitalAdultCandidiasis, VulvovaginalConjunctivitisEmergency Room VisitsFemaleHumansMaleRetrospective StudiesUrinary Tract Infections

Identifiers

PMID42550717
PMCPMC13436643

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.