Evidence map›Paper›PMID 35191842›Full record

ArticleJMIR medical informatics2022

Pandemic-Related Impairment in the Monitoring of Patients With Hypertension and Diabetes and the Development of a Digital Solution for the Community Health Worker: Quasiexperimental and Implementation Study.

Christiane Correa Rodrigues Cimini, Junia Xavier Maia, Magda Carvalho Pires, Leonardo Bonisson Ribeiro, Vânia Soares de Oliveira E Almeida Pinto, James Batchelor, Antonio Luiz Pinho Ribeiro, Milena Soriano Marcolino

Open access · goldAbstract read
In one paragraph

Article in JMIR medical informatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.9field-weighted citation impact, top 24% 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

5 citing papers in PubMed, 10 citations in OpenAlex.

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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

8 authors at 4 institutions in 2 countries.

Christiane Correa Rodrigues CiminiMedical School and Telehealth Center, Universidade Federal dos Vales do Jequitinhonha e Mucuri, Teófilo Otoni-MG, Brazil.ORCID https://orcid.org/0000-0002-1973-1343
Junia Xavier MaiaTelehealth Center, Hospital das Clínicas, Faculdade de Medicina, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.ORCID https://orcid.org/0000-0001-9293-5257
Magda Carvalho PiresDepartment of Statistics, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.ORCID https://orcid.org/0000-0003-3312-4002
Leonardo Bonisson RibeiroTelehealth Center, Hospital das Clínicas, Faculdade de Medicina, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.ORCID https://orcid.org/0000-0001-9035-0722
Vânia Soares de Oliveira E Almeida PintoMedical School and Telehealth Center, Universidade Federal dos Vales do Jequitinhonha e Mucuri, Teófilo Otoni-MG, Brazil.ORCID https://orcid.org/0000-0002-4440-0976
James BatchelorClinical Informatics Research Unit, Faculty of Medicine, University of Southampton, Southampton, United Kingdom.ORCID https://orcid.org/0000-0002-5307-552X
Antonio Luiz Pinho RibeiroTelehealth Center and Cardiology Service, Hospital das Clínicas, Faculdade de Medicina, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.ORCID https://orcid.org/0000-0002-2740-0042
Milena Soriano MarcolinoTelehealth Center, Hospital das Clínicas, Faculdade de Medicina, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.ORCID https://orcid.org/0000-0003-4278-3771
Hospital das Clínicas da Universidade Federal de Minas Gerais · BRUniversidade Federal dos Vales do Jequitinhonha e Mucuri · BRUniversidade Federal de Minas Gerais · BRUniversity of Southampton · GB

Funding

Medical Research Council MR/T02528X/1
6 · The paper itself

Abstract

backgroundThe restrictions imposed by the COVID-19 pandemic reduced health service access by patients with chronic diseases. The discontinuity of care is a cause of great concern, mainly in vulnerable regions.

objectiveThis study aimed to assess the impact of the COVID-19 pandemic on people with hypertension and diabetes mellitus (DM) regarding the frequency of consultations and whether their disease was kept under control. The study also aimed to develop and implement a digital solution to improve monitoring at home.

methodsThis is a multimethodological study. A quasiexperimental evaluation assessed the impact of the pandemic on the frequency of consultations and control of patients with hypertension and DM in 34 primary health care centers in 10 municipalities. Then, an implementation study developed an app with a decision support system (DSS) for community health workers (CHWs) to identify and address at-risk patients with uncontrolled hypertension or DM. An expert panel assessment evaluated feasibility, usability, and utility of the software.

resultsOf 5070 patients, 4810 (94.87%) had hypertension, 1371 (27.04%) had DM, and 1111 (21.91%) had both diseases. There was a significant reduction in the weekly number of consultations (107, IQR 60.0-153.0 before vs 20.0, IQR 7.0-29.0 after social restriction; P<.001). Only 15.23% (772/5070) of all patients returned for a consultation during the pandemic. Individuals with hypertension had lower systolic (120.0, IQR 120.0-140.0 mm Hg) and diastolic (80.0, IQR 80.0-80.0 mm Hg) blood pressure than those who did not return (130.0, IQR 120.0-140.0 mm Hg and 80.0, IQR 80.0-90.0 mm Hg, respectively; P<.001). Also, those who returned had a higher proportion of controlled hypertension (64.3% vs 52.8%). For DM, there were no differences in glycohemoglobin levels. Concerning the DSS, the experts agreed that the CHWs can easily incorporate it into their routines and the app can identify patients at risk and improve treatment.

conclusionsThe COVID-19 pandemic caused a significant drop in the number of consultations for patients with hypertension and DM in primary care. A DSS for CHW has proved to be feasible, useful, and easily incorporated into their routines.

Indexed as

clinical decision support systemsCOVID-19diabetes mellitushypertensionpandemicpatient care managementprimary health caretelemedicine

Identifiers

PMID35191842
PMCPMC8966891
OpenAlexW4213364696

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.