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Not Home Alone: Leveraging Telehealth and Informatics to Create a Lean Model for COVID-19 Patient Home Care
In response to the emerging COVID-19 public health emergency in March 2020, the Medical University of South Carolina rapidly implemented an analytics-enhanced remote patient monitoring (RPM) program with state-wide reach for SARS-CoV-2-positive patients. Patient-reported data and other analytics wer...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Mary Ann Liebert, Inc., publishers
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8621622/ https://www.ncbi.nlm.nih.gov/pubmed/34841422 http://dx.doi.org/10.1089/tmr.2021.0020 |
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author | Ford, Dee Warr, Emily Hamill, Cheryl He, Wenjun Pekar, Ekaterina Harvey, Jillian DuBose-Morris, Ragan McGhee, Kimberly King, Kathryn Lenert, Leslie |
author_facet | Ford, Dee Warr, Emily Hamill, Cheryl He, Wenjun Pekar, Ekaterina Harvey, Jillian DuBose-Morris, Ragan McGhee, Kimberly King, Kathryn Lenert, Leslie |
author_sort | Ford, Dee |
collection | PubMed |
description | In response to the emerging COVID-19 public health emergency in March 2020, the Medical University of South Carolina rapidly implemented an analytics-enhanced remote patient monitoring (RPM) program with state-wide reach for SARS-CoV-2-positive patients. Patient-reported data and other analytics were used to prioritize the sickest patients for contact by RPM nurses, enabling a small cadre of RPM nurses, with the support of ambulatory providers and urgent care video visits, to oversee 1234 patients, many of whom were older, from underserved populations, or at high risk of serious complications. Care was escalated based on prespecified criteria to primary care provider or emergency department visit, with 89% of moderate- to high-risk patients treated solely at home. The RPM nurses facilitated the continuity of care during escalation or de-escalation of care, provided much-needed emotional support to patients quarantining at home and helped find medical homes for patients with tenuous ties to health care. |
format | Online Article Text |
id | pubmed-8621622 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Mary Ann Liebert, Inc., publishers |
record_format | MEDLINE/PubMed |
spelling | pubmed-86216222021-11-26 Not Home Alone: Leveraging Telehealth and Informatics to Create a Lean Model for COVID-19 Patient Home Care Ford, Dee Warr, Emily Hamill, Cheryl He, Wenjun Pekar, Ekaterina Harvey, Jillian DuBose-Morris, Ragan McGhee, Kimberly King, Kathryn Lenert, Leslie Telemed Rep Short Report In response to the emerging COVID-19 public health emergency in March 2020, the Medical University of South Carolina rapidly implemented an analytics-enhanced remote patient monitoring (RPM) program with state-wide reach for SARS-CoV-2-positive patients. Patient-reported data and other analytics were used to prioritize the sickest patients for contact by RPM nurses, enabling a small cadre of RPM nurses, with the support of ambulatory providers and urgent care video visits, to oversee 1234 patients, many of whom were older, from underserved populations, or at high risk of serious complications. Care was escalated based on prespecified criteria to primary care provider or emergency department visit, with 89% of moderate- to high-risk patients treated solely at home. The RPM nurses facilitated the continuity of care during escalation or de-escalation of care, provided much-needed emotional support to patients quarantining at home and helped find medical homes for patients with tenuous ties to health care. Mary Ann Liebert, Inc., publishers 2021-10-28 /pmc/articles/PMC8621622/ /pubmed/34841422 http://dx.doi.org/10.1089/tmr.2021.0020 Text en © Dee Ford et al., 2021; Published by Mary Ann Liebert, Inc. https://creativecommons.org/licenses/by/4.0/This Open Access article is distributed under the terms of the Creative Commons License [CC-BY] (http://creativecommons.org/licenses/by/4.0 (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Short Report Ford, Dee Warr, Emily Hamill, Cheryl He, Wenjun Pekar, Ekaterina Harvey, Jillian DuBose-Morris, Ragan McGhee, Kimberly King, Kathryn Lenert, Leslie Not Home Alone: Leveraging Telehealth and Informatics to Create a Lean Model for COVID-19 Patient Home Care |
title | Not Home Alone: Leveraging Telehealth and Informatics to Create a Lean Model for COVID-19 Patient Home Care |
title_full | Not Home Alone: Leveraging Telehealth and Informatics to Create a Lean Model for COVID-19 Patient Home Care |
title_fullStr | Not Home Alone: Leveraging Telehealth and Informatics to Create a Lean Model for COVID-19 Patient Home Care |
title_full_unstemmed | Not Home Alone: Leveraging Telehealth and Informatics to Create a Lean Model for COVID-19 Patient Home Care |
title_short | Not Home Alone: Leveraging Telehealth and Informatics to Create a Lean Model for COVID-19 Patient Home Care |
title_sort | not home alone: leveraging telehealth and informatics to create a lean model for covid-19 patient home care |
topic | Short Report |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8621622/ https://www.ncbi.nlm.nih.gov/pubmed/34841422 http://dx.doi.org/10.1089/tmr.2021.0020 |
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