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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.
  • Huang M; Department of Artificial Intelligence and Informatics, Mayo Clinic, Rochester, MN, United States.
  • Khurana A; Mayo Clinic Alix School of Medicine, Mayo Clinic, Scottsdale, AZ, United States.
  • Mastorakos G; Mayo Clinic Alix School of Medicine, Mayo Clinic, Scottsdale, AZ, United States.
  • Wen A; Department of Artificial Intelligence and Informatics, Mayo Clinic, Rochester, MN, United States.
  • He H; Department of Artificial Intelligence and Informatics, Mayo Clinic, Rochester, MN, United States.
  • Wang L; Department of Artificial Intelligence and Informatics, Mayo Clinic, Rochester, MN, United States.
  • Liu S; Department of Artificial Intelligence and Informatics, Mayo Clinic, Rochester, MN, United States.
  • Wang Y; Department of Artificial Intelligence and Informatics, Mayo Clinic, Rochester, MN, United States.
  • Zong N; Department of Artificial Intelligence and Informatics, Mayo Clinic, Rochester, MN, United States.
  • Prigge J; Center for Connected Care, Mayo Clinic, Rochester, MN, United States.
  • Costello B; Center for Connected Care, Mayo Clinic, Rochester, MN, United States.
  • Shah N; Department of Artificial Intelligence and Informatics, Mayo Clinic, Rochester, MN, United States.
  • Ting H; Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, United States.
  • Fan J; Department of Artificial Intelligence and Informatics, Mayo Clinic, Rochester, MN, United States.
  • Patten C; Center for Clinical and Translational Science, Mayo Clinic, Rochester, MN, United States.
  • Liu H; Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, United States.
JMIR Hum Factors ; 9(2): e35187, 2022 May 05.
Article in English | MEDLINE | ID: covidwho-1834181
ABSTRACT

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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Full text: Available Collection: International databases Database: MEDLINE Type of study: Observational study Language: English Journal: JMIR Hum Factors Year: 2022 Document Type: Article Affiliation country: 35187

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Observational study Language: English Journal: JMIR Hum Factors Year: 2022 Document Type: Article Affiliation country: 35187