Evidence map›Paper›PMID 33100183›Full record

ArticleJournal of telemedicine and telecare2023

Impact of a large-scale telemedicine network on emergency visits and hospital admissions during the coronavirus disease 2019 pandemic in Brazil: Data from the UNIMED-BH system.

Bruno R Nascimento, Luisa Cc Brant, Ana Cristina T Castro, Luiz Eduardo V Froes, Antonio Luiz P Ribeiro, Larissa V Cruz, Cynthia B Araújo, Charles F Souza, Eduardo T Froes, Soraya D Souza

Open access · bronzeAbstract read
PubMed Publisher
In one paragraph

Article in Journal of telemedicine and telecare, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 2 pooled it
2.0field-weighted citation impact, top 11% of its field
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

14 citing papers in PubMed, 2 syntheses or guidelines pooled it, 36 citations in OpenAlex.

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  9. Cardiovascular Statistics - Brazil 2021.Arquivos brasileiros de cardiologia · 2022
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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

10 authors at 3 institutions in 1 country.

Bruno R NascimentoServiço de Cardiologia e Cirurgia Cardiovascular e Centro de Telessaúde do Hospital das Clínicas da UFMG, Brazil.ORCID 0000-0002-5586-774X
Luisa Cc BrantServiço de Cardiologia e Cirurgia Cardiovascular e Centro de Telessaúde do Hospital das Clínicas da UFMG, Brazil.ORCID 0000-0002-7317-1367
Ana Cristina T CastroServiço de Atendimento Móvel (GMOV), UNIMED-BH Cooperativa Médica, Brazil.
Luiz Eduardo V FroesFaculdade de Medicina, Universidade José do Rosário Vellano, Brazil.
Antonio Luiz P RibeiroServiço de Cardiologia e Cirurgia Cardiovascular e Centro de Telessaúde do Hospital das Clínicas da UFMG, Brazil.
Larissa V CruzCentro Médico, CPS Barreiro e Central de Consultas On-line, UNIMED-BH Cooperativa Médica, Brazil.
Cynthia B AraújoGerência de Desenvolvimento de Informações para o Negócio (GDIN), UNIMED-BH Cooperativa Médica, Brazil.
Charles F SouzaGerência de Desenvolvimento de Informações para o Negócio (GDIN), UNIMED-BH Cooperativa Médica, Brazil.
Eduardo T FroesServiço de Atendimento Móvel (GMOV), UNIMED-BH Cooperativa Médica, Brazil.
Soraya D SouzaServiço de Atendimento Móvel (GMOV), UNIMED-BH Cooperativa Médica, Brazil.
Centro Universitário de Belo Horizonte · BRUniversidade Federal de Minas Gerais · BRUniversidade José do Rosário Vellano · BR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionTriage by on-demand telemedicine is a strategy for healthcare surge control in the COVID-19 pandemic. We aimed to assess the impact of a large-scale COVID-19 telemedicine system on emergency department (ED) visits and all-cause and cardiovascular hospital admissions in Brazil.

methodsFrom March 18, 2020-May 18, 2020 we evaluated the database of a cooperative private health insurance, with 1.28 million clients. The COVID-19 telemedicine system consisted of: a) mobile app, which redirects to teleconsultations if indicated; b) telemonitoring system, with regular phone calls to suspected/confirmed COVID-19 cases to monitor progression; c) emergency ambulance system (EAS), with internet phone triage and counselling. ED visits and hospital admissions were recorded, with diagnoses assessed by the Diagnosis Related Groups method. COVID-19 diagnosis and deaths were identified from the patients' registries, and outcomes assessed until June 1st.

resultsIn 60 days, 24,354 patients accessed one of the telemedicine systems. The most frequently utilized was telemonitoring (16,717, 69%), followed by teleconsultation (13,357, 55%) and EAS (687, 3%). The rates of ED and hospital admissions were: telemonitoring 19.7% (3,296) and 4.7% (782); teleconsultation 17.3% (2,313) and 2.4% (318) and EAS: 55.9% (384) and 56.5% (388) patients. At total 4.1% (1,010) had hospital admissions, 36% (363) with respiratory diseases (44 requiring mechanical ventilation) and 4.4% (44) with cardiovascular diagnoses. Overall, 277 (1.1%) patients had confirmed COVID-19 diagnosis, and 160 (0.7%) died, 9 with COVID-19.

conclusionTelemedicine resulted in low rates of ED visits and hospital admissions, suggesting positive impacts on healthcare utilization. Cardiovascular admissions were remarkably rare.

Indexed as

COVID-19TelemedicineBrazilCOVID-19 TestingEmergency Service, HospitalHospitalsHumansPandemicsRetrospective StudiesSARS-CoV-2admissionsCOVID-19pandemic, telemonitoringteleconsultationTelemedicine

Identifiers

PMID33100183
OpenAlexW3094389938

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.