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Crowdsourced Community Support Resources Among Patients Discharged From the Emergency Department During the COVID-19 Pandemic: Pilot Feasibility Study
BACKGROUND: The COVID-19 pandemic has placed strains on communities. During this public health crisis, health systems have created remote methods of monitoring symptom progression and delivering care virtually. OBJECTIVE: Using an SMS text message-based system, we sought to build and test a remote m...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8869378/ https://www.ncbi.nlm.nih.gov/pubmed/35037886 http://dx.doi.org/10.2196/31909 |
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author | Agarwal, Anish K Southwick, Lauren Schneider, Rachelle Pelullo, Arthur Ortiz, Robin Klinger, Elissa V Gonzales, Rachel E Rosin, Roy Merchant, Raina M |
author_facet | Agarwal, Anish K Southwick, Lauren Schneider, Rachelle Pelullo, Arthur Ortiz, Robin Klinger, Elissa V Gonzales, Rachel E Rosin, Roy Merchant, Raina M |
author_sort | Agarwal, Anish K |
collection | PubMed |
description | BACKGROUND: The COVID-19 pandemic has placed strains on communities. During this public health crisis, health systems have created remote methods of monitoring symptom progression and delivering care virtually. OBJECTIVE: Using an SMS text message-based system, we sought to build and test a remote model to explore community needs, connect individuals to curated resources, and facilitate community health worker intervention when needed during the pandemic. The primary aims of this pilot study were to establish the feasibility (ie, engagement with the text line) and acceptability (ie, participant ratings of resources and service) of delivering automated well-being resources via smartphone technology. METHODS: Eligible patients (aged 18 years or older, having a cell phone with SMS text messaging capability, and recently visited the emergency department) were identified using the electronic health record. The patients were consented to enroll and begin receiving COVID-19–related information and links to community resources. We collected open-ended and close-ended resource and mood ratings. We calculated the frequencies and conducted a thematic review of the open-ended responses. RESULTS: In 7 weeks, 356 participants were enrolled; 13,917 messages were exchanged including 333 resource ratings (mean 4) and 673 well-being scores (mean 6.8). We received and coded 386 open-ended responses, most of which elaborated upon their self-reported mood score (29%). Overall, 77% (n=274) of our participants rated the platform as a service they would highly recommend to a family member or friend. CONCLUSIONS: This approach is designed to broaden the reach of health systems, tailor to community needs in real time, and connect at-risk individuals with robust community health support. |
format | Online Article Text |
id | pubmed-8869378 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-88693782022-03-10 Crowdsourced Community Support Resources Among Patients Discharged From the Emergency Department During the COVID-19 Pandemic: Pilot Feasibility Study Agarwal, Anish K Southwick, Lauren Schneider, Rachelle Pelullo, Arthur Ortiz, Robin Klinger, Elissa V Gonzales, Rachel E Rosin, Roy Merchant, Raina M JMIR Ment Health Original Paper BACKGROUND: The COVID-19 pandemic has placed strains on communities. During this public health crisis, health systems have created remote methods of monitoring symptom progression and delivering care virtually. OBJECTIVE: Using an SMS text message-based system, we sought to build and test a remote model to explore community needs, connect individuals to curated resources, and facilitate community health worker intervention when needed during the pandemic. The primary aims of this pilot study were to establish the feasibility (ie, engagement with the text line) and acceptability (ie, participant ratings of resources and service) of delivering automated well-being resources via smartphone technology. METHODS: Eligible patients (aged 18 years or older, having a cell phone with SMS text messaging capability, and recently visited the emergency department) were identified using the electronic health record. The patients were consented to enroll and begin receiving COVID-19–related information and links to community resources. We collected open-ended and close-ended resource and mood ratings. We calculated the frequencies and conducted a thematic review of the open-ended responses. RESULTS: In 7 weeks, 356 participants were enrolled; 13,917 messages were exchanged including 333 resource ratings (mean 4) and 673 well-being scores (mean 6.8). We received and coded 386 open-ended responses, most of which elaborated upon their self-reported mood score (29%). Overall, 77% (n=274) of our participants rated the platform as a service they would highly recommend to a family member or friend. CONCLUSIONS: This approach is designed to broaden the reach of health systems, tailor to community needs in real time, and connect at-risk individuals with robust community health support. JMIR Publications 2022-02-23 /pmc/articles/PMC8869378/ /pubmed/35037886 http://dx.doi.org/10.2196/31909 Text en ©Anish K Agarwal, Lauren Southwick, Rachelle Schneider, Arthur Pelullo, Robin Ortiz, Elissa V Klinger, Rachel E Gonzales, Roy Rosin, Raina M Merchant. Originally published in JMIR Mental Health (https://mental.jmir.org), 23.02.2022. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Mental Health, is properly cited. The complete bibliographic information, a link to the original publication on https://mental.jmir.org/, as well as this copyright and license information must be included. |
spellingShingle | Original Paper Agarwal, Anish K Southwick, Lauren Schneider, Rachelle Pelullo, Arthur Ortiz, Robin Klinger, Elissa V Gonzales, Rachel E Rosin, Roy Merchant, Raina M Crowdsourced Community Support Resources Among Patients Discharged From the Emergency Department During the COVID-19 Pandemic: Pilot Feasibility Study |
title | Crowdsourced Community Support Resources Among Patients Discharged From the Emergency Department During the COVID-19 Pandemic: Pilot Feasibility Study |
title_full | Crowdsourced Community Support Resources Among Patients Discharged From the Emergency Department During the COVID-19 Pandemic: Pilot Feasibility Study |
title_fullStr | Crowdsourced Community Support Resources Among Patients Discharged From the Emergency Department During the COVID-19 Pandemic: Pilot Feasibility Study |
title_full_unstemmed | Crowdsourced Community Support Resources Among Patients Discharged From the Emergency Department During the COVID-19 Pandemic: Pilot Feasibility Study |
title_short | Crowdsourced Community Support Resources Among Patients Discharged From the Emergency Department During the COVID-19 Pandemic: Pilot Feasibility Study |
title_sort | crowdsourced community support resources among patients discharged from the emergency department during the covid-19 pandemic: pilot feasibility study |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8869378/ https://www.ncbi.nlm.nih.gov/pubmed/35037886 http://dx.doi.org/10.2196/31909 |
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