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Virtual healthcare solutions in heart failure: a literature review

The widespread adoption of mobile technologies offers an opportunity for a new approach to post-discharge care for patients with heart failure (HF). By enabling non-invasive remote monitoring and two-way, real-time communication between the clinic and home-based patients, as well as a host of other...

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Autores principales: Lee, Keni Cheng-Siang, Breznen, Boris, Ukhova, Anastasia, Martin, Seth Shay, Koehler, Friedrich
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10513031/
https://www.ncbi.nlm.nih.gov/pubmed/37745104
http://dx.doi.org/10.3389/fcvm.2023.1231000
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author Lee, Keni Cheng-Siang
Breznen, Boris
Ukhova, Anastasia
Martin, Seth Shay
Koehler, Friedrich
author_facet Lee, Keni Cheng-Siang
Breznen, Boris
Ukhova, Anastasia
Martin, Seth Shay
Koehler, Friedrich
author_sort Lee, Keni Cheng-Siang
collection PubMed
description The widespread adoption of mobile technologies offers an opportunity for a new approach to post-discharge care for patients with heart failure (HF). By enabling non-invasive remote monitoring and two-way, real-time communication between the clinic and home-based patients, as well as a host of other capabilities, mobile technologies have a potential to significantly improve remote patient care. This literature review summarizes clinical evidence related to virtual healthcare (VHC), defined as a care team + connected devices + a digital solution in post-release care of patients with HF. Searches were conducted on Embase (06/12/2020). A total of 171 studies were included for data extraction and evidence synthesis: 96 studies related to VHC efficacy, and 75 studies related to AI in HF. In addition, 15 publications were included from the search on studies scaling up VHC solutions in HF within the real-world setting. The most successful VHC interventions, as measured by the number of reported significant results, were those targeting reduction in rehospitalization rates. In terms of relative success rate, the two most effective interventions targeted patient self-care and all-cause hospital visits in their primary endpoint. Among the three categories of VHC identified in this review (telemonitoring, remote patient management, and patient self-empowerment) the integrated approach in remote patient management solutions performs the best in decreasing HF patients' re-admission rates and overall hospital visits. Given the increased amount of data generated by VHC technologies, artificial intelligence (AI) is being investigated as a tool to aid decision making in the context of primary diagnostics, identifying disease phenotypes, and predicting treatment outcomes. Currently, most AI algorithms are developed using data gathered in clinic and only a few studies deploy AI in the context of VHC. Most successes have been reported in predicting HF outcomes. Since the field of VHC in HF is relatively new and still in flux, this is not a typical systematic review capturing all published studies within this domain. Although the standard methodology for this type of reviews was followed, the nature of this review is qualitative. The main objective was to summarize the most promising results and identify potential research directions.
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spelling pubmed-105130312023-09-22 Virtual healthcare solutions in heart failure: a literature review Lee, Keni Cheng-Siang Breznen, Boris Ukhova, Anastasia Martin, Seth Shay Koehler, Friedrich Front Cardiovasc Med Cardiovascular Medicine The widespread adoption of mobile technologies offers an opportunity for a new approach to post-discharge care for patients with heart failure (HF). By enabling non-invasive remote monitoring and two-way, real-time communication between the clinic and home-based patients, as well as a host of other capabilities, mobile technologies have a potential to significantly improve remote patient care. This literature review summarizes clinical evidence related to virtual healthcare (VHC), defined as a care team + connected devices + a digital solution in post-release care of patients with HF. Searches were conducted on Embase (06/12/2020). A total of 171 studies were included for data extraction and evidence synthesis: 96 studies related to VHC efficacy, and 75 studies related to AI in HF. In addition, 15 publications were included from the search on studies scaling up VHC solutions in HF within the real-world setting. The most successful VHC interventions, as measured by the number of reported significant results, were those targeting reduction in rehospitalization rates. In terms of relative success rate, the two most effective interventions targeted patient self-care and all-cause hospital visits in their primary endpoint. Among the three categories of VHC identified in this review (telemonitoring, remote patient management, and patient self-empowerment) the integrated approach in remote patient management solutions performs the best in decreasing HF patients' re-admission rates and overall hospital visits. Given the increased amount of data generated by VHC technologies, artificial intelligence (AI) is being investigated as a tool to aid decision making in the context of primary diagnostics, identifying disease phenotypes, and predicting treatment outcomes. Currently, most AI algorithms are developed using data gathered in clinic and only a few studies deploy AI in the context of VHC. Most successes have been reported in predicting HF outcomes. Since the field of VHC in HF is relatively new and still in flux, this is not a typical systematic review capturing all published studies within this domain. Although the standard methodology for this type of reviews was followed, the nature of this review is qualitative. The main objective was to summarize the most promising results and identify potential research directions. Frontiers Media S.A. 2023-09-07 /pmc/articles/PMC10513031/ /pubmed/37745104 http://dx.doi.org/10.3389/fcvm.2023.1231000 Text en © 2023 Lee, Breznen, Ukhova, Martin and Koehler. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) (https://creativecommons.org/licenses/by/4.0/) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Cardiovascular Medicine
Lee, Keni Cheng-Siang
Breznen, Boris
Ukhova, Anastasia
Martin, Seth Shay
Koehler, Friedrich
Virtual healthcare solutions in heart failure: a literature review
title Virtual healthcare solutions in heart failure: a literature review
title_full Virtual healthcare solutions in heart failure: a literature review
title_fullStr Virtual healthcare solutions in heart failure: a literature review
title_full_unstemmed Virtual healthcare solutions in heart failure: a literature review
title_short Virtual healthcare solutions in heart failure: a literature review
title_sort virtual healthcare solutions in heart failure: a literature review
topic Cardiovascular Medicine
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10513031/
https://www.ncbi.nlm.nih.gov/pubmed/37745104
http://dx.doi.org/10.3389/fcvm.2023.1231000
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