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The Effect of Telehealth on Hospital Services Use: Systematic Review and Meta-analysis

BACKGROUND: Telehealth interventions, that is, health care provided over a distance using information and communication technology, are suggested as a solution to rising health care costs by reducing hospital service use. However, the extent to which this is possible is unclear. OBJECTIVE: The aim o...

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Autores principales: Peters, Guido M, Kooij, Laura, Lenferink, Anke, van Harten, Wim H, Doggen, Carine J M
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8444037/
https://www.ncbi.nlm.nih.gov/pubmed/34468324
http://dx.doi.org/10.2196/25195
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author Peters, Guido M
Kooij, Laura
Lenferink, Anke
van Harten, Wim H
Doggen, Carine J M
author_facet Peters, Guido M
Kooij, Laura
Lenferink, Anke
van Harten, Wim H
Doggen, Carine J M
author_sort Peters, Guido M
collection PubMed
description BACKGROUND: Telehealth interventions, that is, health care provided over a distance using information and communication technology, are suggested as a solution to rising health care costs by reducing hospital service use. However, the extent to which this is possible is unclear. OBJECTIVE: The aim of this study is to evaluate the effect of telehealth on the use of hospital services, that is, (duration of) hospitalizations, and to compare the effects between telehealth types and health conditions. METHODS: We searched PubMed, Scopus, and the Cochrane Library from inception until April 2019. Peer-reviewed randomized controlled trials (RCTs) reporting the effect of telehealth interventions on hospital service use compared with usual care were included. Risk of bias was assessed using the Cochrane Risk of Bias 2 tool and quality of evidence according to the Grading of Recommendations Assessment, Development and Evaluation guidelines. RESULTS: We included 127 RCTs in the meta-analysis. Of these RCTs, 82.7% (105/127) had a low risk of bias or some concerns overall. High-quality evidence shows that telehealth reduces the risk of all-cause or condition-related hospitalization by 18 (95% CI 0-30) and 37 (95% CI 20-60) per 1000 patients, respectively. We found high-quality evidence that telehealth leads to reductions in the mean all-cause and condition-related hospitalizations, with 50 and 110 fewer hospitalizations per 1000 patients, respectively. Overall, the all-cause hospital days decreased by 1.07 (95% CI −1.76 to −0.39) days per patient. For hospitalized patients, the mean hospital stay for condition-related hospitalizations decreased by 0.89 (95% CI −1.42 to −0.36) days. The effects were similar between telehealth types and health conditions. A trend was observed for studies with longer follow-up periods yielding larger effects. CONCLUSIONS: Small to moderate reductions in hospital service use can be achieved using telehealth. It should be noted that, despite the large number of included studies, uncertainties around the magnitude of effects remain, and not all effects are statistically significant.
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spelling pubmed-84440372021-09-28 The Effect of Telehealth on Hospital Services Use: Systematic Review and Meta-analysis Peters, Guido M Kooij, Laura Lenferink, Anke van Harten, Wim H Doggen, Carine J M J Med Internet Res Review BACKGROUND: Telehealth interventions, that is, health care provided over a distance using information and communication technology, are suggested as a solution to rising health care costs by reducing hospital service use. However, the extent to which this is possible is unclear. OBJECTIVE: The aim of this study is to evaluate the effect of telehealth on the use of hospital services, that is, (duration of) hospitalizations, and to compare the effects between telehealth types and health conditions. METHODS: We searched PubMed, Scopus, and the Cochrane Library from inception until April 2019. Peer-reviewed randomized controlled trials (RCTs) reporting the effect of telehealth interventions on hospital service use compared with usual care were included. Risk of bias was assessed using the Cochrane Risk of Bias 2 tool and quality of evidence according to the Grading of Recommendations Assessment, Development and Evaluation guidelines. RESULTS: We included 127 RCTs in the meta-analysis. Of these RCTs, 82.7% (105/127) had a low risk of bias or some concerns overall. High-quality evidence shows that telehealth reduces the risk of all-cause or condition-related hospitalization by 18 (95% CI 0-30) and 37 (95% CI 20-60) per 1000 patients, respectively. We found high-quality evidence that telehealth leads to reductions in the mean all-cause and condition-related hospitalizations, with 50 and 110 fewer hospitalizations per 1000 patients, respectively. Overall, the all-cause hospital days decreased by 1.07 (95% CI −1.76 to −0.39) days per patient. For hospitalized patients, the mean hospital stay for condition-related hospitalizations decreased by 0.89 (95% CI −1.42 to −0.36) days. The effects were similar between telehealth types and health conditions. A trend was observed for studies with longer follow-up periods yielding larger effects. CONCLUSIONS: Small to moderate reductions in hospital service use can be achieved using telehealth. It should be noted that, despite the large number of included studies, uncertainties around the magnitude of effects remain, and not all effects are statistically significant. JMIR Publications 2021-09-01 /pmc/articles/PMC8444037/ /pubmed/34468324 http://dx.doi.org/10.2196/25195 Text en ©Guido M Peters, Laura Kooij, Anke Lenferink, Wim H van Harten, Carine J M Doggen. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 01.09.2021. 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 the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.
spellingShingle Review
Peters, Guido M
Kooij, Laura
Lenferink, Anke
van Harten, Wim H
Doggen, Carine J M
The Effect of Telehealth on Hospital Services Use: Systematic Review and Meta-analysis
title The Effect of Telehealth on Hospital Services Use: Systematic Review and Meta-analysis
title_full The Effect of Telehealth on Hospital Services Use: Systematic Review and Meta-analysis
title_fullStr The Effect of Telehealth on Hospital Services Use: Systematic Review and Meta-analysis
title_full_unstemmed The Effect of Telehealth on Hospital Services Use: Systematic Review and Meta-analysis
title_short The Effect of Telehealth on Hospital Services Use: Systematic Review and Meta-analysis
title_sort effect of telehealth on hospital services use: systematic review and meta-analysis
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8444037/
https://www.ncbi.nlm.nih.gov/pubmed/34468324
http://dx.doi.org/10.2196/25195
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