Evidence map›Paper›PMID 33667174›Full record

ArticleJMIR public health and surveillance2021

Use of a Telemedicine Risk Assessment Tool to Predict the Risk of Hospitalization of 496 Outpatients With COVID-19: Retrospective Analysis.

James B O'Keefe, Elizabeth J Tong, Thomas H Taylor, Ghazala A Datoo O'Keefe, David C Tong

Abstract read
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Article in JMIR public health and surveillance, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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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

20 citing papers in PubMed.

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  7. Coronavirus disease and home recovery: a Singapore perspective.Western Pacific surveillance and response journal : WPSAR · 2023
    Review
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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

5 authors.

James B O'KeefeDivision of General Internal Medicine, Department of Medicine, Emory University School of Medicine, Atlanta, GA, United States.ORCID 0000-0002-7151-7184
Elizabeth J TongDivision of General Internal Medicine, Department of Medicine, Emory University School of Medicine, Atlanta, GA, United States.ORCID 0000-0001-7724-5899
Thomas H TaylorTaylor Engineering, Inc, Atlanta, GA, United States.ORCID 0000-0002-0829-3245
Ghazala A Datoo O'KeefeSection of Vitreoretinal Surgery and Diseases, Section of Uveitis and Vasculitis, Department of Ophthalmology, Emory University School of Medicine, Atlanta, GA, United States.ORCID 0000-0002-5641-4195
David C TongDivision of Hospital Medicine, Department of Medicine, Emory University School of Medicine, Atlanta, GA, United States.ORCID 0000-0001-9761-6124

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRisk assessment of patients with acute COVID-19 in a telemedicine context is not well described. In settings of large numbers of patients, a risk assessment tool may guide resource allocation not only for patient care but also for maximum health care and public health benefit.

objectiveThe goal of this study was to determine whether a COVID-19 telemedicine risk assessment tool accurately predicts hospitalizations.

methodsWe conducted a retrospective study of a COVID-19 telemedicine home monitoring program serving health care workers and the community in Atlanta, Georgia, with enrollment from March 24 to May 26, 2020; the final call range was from March 27 to June 19, 2020. All patients were assessed by medical providers using an institutional COVID-19 risk assessment tool designating patients as Tier 1 (low risk for hospitalization), Tier 2 (intermediate risk for hospitalization), or Tier 3 (high risk for hospitalization). Patients were followed with regular telephone calls to an endpoint of improvement or hospitalization. Using survival analysis by Cox regression with days to hospitalization as the metric, we analyzed the performance of the risk tiers and explored individual patient factors associated with risk of hospitalization.

resultsProviders using the risk assessment rubric assigned 496 outpatients to tiers: Tier 1, 237 out of 496 (47.8%); Tier 2, 185 out of 496 (37.3%); and Tier 3, 74 out of 496 (14.9%). Subsequent hospitalizations numbered 3 out of 237 (1.3%) for Tier 1, 15 out of 185 (8.1%) for Tier 2, and 17 out of 74 (23%) for Tier 3. From a Cox regression model with age of 60 years or older, gender, and reported obesity as covariates, the adjusted hazard ratios for hospitalization using Tier 1 as reference were 3.74 (95% CI 1.06-13.27; P=.04) for Tier 2 and 10.87 (95% CI 3.09-38.27; P<.001) for Tier 3.

conclusionsA telemedicine risk assessment tool prospectively applied to an outpatient population with COVID-19 identified populations with low, intermediate, and high risk of hospitalization.

Indexed as

Ambulatory CareTelemedicineAdolescentAdultAgedCOVID-19FemaleHospitalizationHumansMaleMiddle AgedReproducibility of ResultsRetrospective StudiesRisk AssessmentYoung AdultCOVID-19nonhospitalizedoutcomesoutpatientrisk assessmentSARS-CoV-2telemedicine

Identifiers

PMID33667174
PMCPMC8092025

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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.