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Patient Portal Messaging for Asynchronous Virtual Care During the COVID-19 Pandemic: Retrospective Analysis

BACKGROUND: During the COVID-19 pandemic, patient portals and their message platforms allowed remote access to health care. Utilization patterns in patient messaging during the COVID-19 crisis have not been studied thoroughly. In this work, we propose characterizing patients and their use of asynchr...

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Autores principales: Huang, Ming, Khurana, Aditya, Mastorakos, George, Wen, Andrew, He, Huan, Wang, Liwei, Liu, Sijia, Wang, Yanshan, Zong, Nansu, Prigge, Julie, Costello, Brian, Shah, Nilay, Ting, Henry, Fan, Jungwei, Patten, Christi, Liu, Hongfang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9084445/
https://www.ncbi.nlm.nih.gov/pubmed/35171108
http://dx.doi.org/10.2196/35187
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author Huang, Ming
Khurana, Aditya
Mastorakos, George
Wen, Andrew
He, Huan
Wang, Liwei
Liu, Sijia
Wang, Yanshan
Zong, Nansu
Prigge, Julie
Costello, Brian
Shah, Nilay
Ting, Henry
Fan, Jungwei
Patten, Christi
Liu, Hongfang
author_facet Huang, Ming
Khurana, Aditya
Mastorakos, George
Wen, Andrew
He, Huan
Wang, Liwei
Liu, Sijia
Wang, Yanshan
Zong, Nansu
Prigge, Julie
Costello, Brian
Shah, Nilay
Ting, Henry
Fan, Jungwei
Patten, Christi
Liu, Hongfang
author_sort Huang, Ming
collection PubMed
description BACKGROUND: During the COVID-19 pandemic, patient portals and their message platforms allowed remote access to health care. Utilization patterns in patient messaging during the COVID-19 crisis have not been studied thoroughly. In this work, we propose characterizing patients and their use of asynchronous virtual care for COVID-19 via a retrospective analysis of patient portal messages. OBJECTIVE: This study aimed to perform a retrospective analysis of portal messages to probe asynchronous patient responses to the COVID-19 crisis. METHODS: We collected over 2 million patient-generated messages (PGMs) at Mayo Clinic during February 1 to August 31, 2020. We analyzed descriptive statistics on PGMs related to COVID-19 and incorporated patients’ sociodemographic factors into the analysis. We analyzed the PGMs on COVID-19 in terms of COVID-19–related care (eg, COVID-19 symptom self-assessment and COVID-19 tests and results) and other health issues (eg, appointment cancellation, anxiety, and depression). RESULTS: The majority of PGMs on COVID-19 pertained to COVID-19 symptom self-assessment (42.50%) and COVID-19 tests and results (30.84%). The PGMs related to COVID-19 symptom self-assessment and COVID-19 test results had dynamic patterns and peaks similar to the newly confirmed cases in the United States and in Minnesota. The trend of PGMs related to COVID-19 care plans paralleled trends in newly hospitalized cases and deaths. After an initial peak in March, the PGMs on issues such as appointment cancellations and anxiety regarding COVID-19 displayed a declining trend. The majority of message senders were 30-64 years old, married, female, White, or urban residents. This majority was an even higher proportion among patients who sent portal messages on COVID-19. CONCLUSIONS: During the COVID-19 pandemic, patients increased portal messaging utilization to address health care issues about COVID-19 (in particular, symptom self-assessment and tests and results). Trends in message usage closely followed national trends in new cases and hospitalizations. There is a wide disparity for minority and rural populations in the use of PGMs for addressing the COVID-19 crisis.
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spelling pubmed-90844452022-05-10 Patient Portal Messaging for Asynchronous Virtual Care During the COVID-19 Pandemic: Retrospective Analysis Huang, Ming Khurana, Aditya Mastorakos, George Wen, Andrew He, Huan Wang, Liwei Liu, Sijia Wang, Yanshan Zong, Nansu Prigge, Julie Costello, Brian Shah, Nilay Ting, Henry Fan, Jungwei Patten, Christi Liu, Hongfang JMIR Hum Factors Original Paper BACKGROUND: During the COVID-19 pandemic, patient portals and their message platforms allowed remote access to health care. Utilization patterns in patient messaging during the COVID-19 crisis have not been studied thoroughly. In this work, we propose characterizing patients and their use of asynchronous virtual care for COVID-19 via a retrospective analysis of patient portal messages. OBJECTIVE: This study aimed to perform a retrospective analysis of portal messages to probe asynchronous patient responses to the COVID-19 crisis. METHODS: We collected over 2 million patient-generated messages (PGMs) at Mayo Clinic during February 1 to August 31, 2020. We analyzed descriptive statistics on PGMs related to COVID-19 and incorporated patients’ sociodemographic factors into the analysis. We analyzed the PGMs on COVID-19 in terms of COVID-19–related care (eg, COVID-19 symptom self-assessment and COVID-19 tests and results) and other health issues (eg, appointment cancellation, anxiety, and depression). RESULTS: The majority of PGMs on COVID-19 pertained to COVID-19 symptom self-assessment (42.50%) and COVID-19 tests and results (30.84%). The PGMs related to COVID-19 symptom self-assessment and COVID-19 test results had dynamic patterns and peaks similar to the newly confirmed cases in the United States and in Minnesota. The trend of PGMs related to COVID-19 care plans paralleled trends in newly hospitalized cases and deaths. After an initial peak in March, the PGMs on issues such as appointment cancellations and anxiety regarding COVID-19 displayed a declining trend. The majority of message senders were 30-64 years old, married, female, White, or urban residents. This majority was an even higher proportion among patients who sent portal messages on COVID-19. CONCLUSIONS: During the COVID-19 pandemic, patients increased portal messaging utilization to address health care issues about COVID-19 (in particular, symptom self-assessment and tests and results). Trends in message usage closely followed national trends in new cases and hospitalizations. There is a wide disparity for minority and rural populations in the use of PGMs for addressing the COVID-19 crisis. JMIR Publications 2022-05-05 /pmc/articles/PMC9084445/ /pubmed/35171108 http://dx.doi.org/10.2196/35187 Text en ©Ming Huang, Aditya Khurana, George Mastorakos, Andrew Wen, Huan He, Liwei Wang, Sijia Liu, Yanshan Wang, Nansu Zong, Julie Prigge, Brian Costello, Nilay Shah, Henry Ting, Jungwei Fan, Christi Patten, Hongfang Liu. Originally published in JMIR Human Factors (https://humanfactors.jmir.org), 05.05.2022. 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 Human Factors, is properly cited. The complete bibliographic information, a link to the original publication on https://humanfactors.jmir.org, as well as this copyright and license information must be included.
spellingShingle Original Paper
Huang, Ming
Khurana, Aditya
Mastorakos, George
Wen, Andrew
He, Huan
Wang, Liwei
Liu, Sijia
Wang, Yanshan
Zong, Nansu
Prigge, Julie
Costello, Brian
Shah, Nilay
Ting, Henry
Fan, Jungwei
Patten, Christi
Liu, Hongfang
Patient Portal Messaging for Asynchronous Virtual Care During the COVID-19 Pandemic: Retrospective Analysis
title Patient Portal Messaging for Asynchronous Virtual Care During the COVID-19 Pandemic: Retrospective Analysis
title_full Patient Portal Messaging for Asynchronous Virtual Care During the COVID-19 Pandemic: Retrospective Analysis
title_fullStr Patient Portal Messaging for Asynchronous Virtual Care During the COVID-19 Pandemic: Retrospective Analysis
title_full_unstemmed Patient Portal Messaging for Asynchronous Virtual Care During the COVID-19 Pandemic: Retrospective Analysis
title_short Patient Portal Messaging for Asynchronous Virtual Care During the COVID-19 Pandemic: Retrospective Analysis
title_sort patient portal messaging for asynchronous virtual care during the covid-19 pandemic: retrospective analysis
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9084445/
https://www.ncbi.nlm.nih.gov/pubmed/35171108
http://dx.doi.org/10.2196/35187
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