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A randomized trial examining the effect of predictive analytics and tailored interventions on the cost of care
This two-arm randomized controlled trial evaluated the impact of a Stepped-Care intervention (predictive analytics combined with tailored interventions) on the healthcare costs of older adults using a Personal Emergency Response System (PERS). A total of 370 patients aged 65 and over with healthcare...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8175712/ https://www.ncbi.nlm.nih.gov/pubmed/34083743 http://dx.doi.org/10.1038/s41746-021-00449-w |
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author | Nikolova-Simons, Mariana Golas, Sara Bersche den Buijs, Jorn op Palacholla, Ramya S. Garberg, Gary Orenstein, Allison Kvedar, Joseph |
author_facet | Nikolova-Simons, Mariana Golas, Sara Bersche den Buijs, Jorn op Palacholla, Ramya S. Garberg, Gary Orenstein, Allison Kvedar, Joseph |
author_sort | Nikolova-Simons, Mariana |
collection | PubMed |
description | This two-arm randomized controlled trial evaluated the impact of a Stepped-Care intervention (predictive analytics combined with tailored interventions) on the healthcare costs of older adults using a Personal Emergency Response System (PERS). A total of 370 patients aged 65 and over with healthcare costs in the middle segment of the cost pyramid for the fiscal year prior to their enrollment were enrolled for the study. During a 180-day intervention period, control group (CG) received standard care, while intervention group (IG) received the Stepped-Care intervention. The IG had 31% lower annualized inpatient cost per patient compared with the CG (3.7 K, $8.1 K vs. $11.8 K, p = 0.02). Both groups had similar annualized outpatient costs per patient ($6.1 K vs. $5.8 K, p = 0.10). The annualized total cost reduction per patient in the IG vs. CG was 20% (3.5 K, $17.7 K vs. $14.2 K, p = 0.04). Predictive analytics coupled with tailored interventions has great potential to reduce healthcare costs in older adults, thereby supporting population health management in home or community settings. |
format | Online Article Text |
id | pubmed-8175712 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-81757122021-06-07 A randomized trial examining the effect of predictive analytics and tailored interventions on the cost of care Nikolova-Simons, Mariana Golas, Sara Bersche den Buijs, Jorn op Palacholla, Ramya S. Garberg, Gary Orenstein, Allison Kvedar, Joseph NPJ Digit Med Article This two-arm randomized controlled trial evaluated the impact of a Stepped-Care intervention (predictive analytics combined with tailored interventions) on the healthcare costs of older adults using a Personal Emergency Response System (PERS). A total of 370 patients aged 65 and over with healthcare costs in the middle segment of the cost pyramid for the fiscal year prior to their enrollment were enrolled for the study. During a 180-day intervention period, control group (CG) received standard care, while intervention group (IG) received the Stepped-Care intervention. The IG had 31% lower annualized inpatient cost per patient compared with the CG (3.7 K, $8.1 K vs. $11.8 K, p = 0.02). Both groups had similar annualized outpatient costs per patient ($6.1 K vs. $5.8 K, p = 0.10). The annualized total cost reduction per patient in the IG vs. CG was 20% (3.5 K, $17.7 K vs. $14.2 K, p = 0.04). Predictive analytics coupled with tailored interventions has great potential to reduce healthcare costs in older adults, thereby supporting population health management in home or community settings. Nature Publishing Group UK 2021-06-03 /pmc/articles/PMC8175712/ /pubmed/34083743 http://dx.doi.org/10.1038/s41746-021-00449-w Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Nikolova-Simons, Mariana Golas, Sara Bersche den Buijs, Jorn op Palacholla, Ramya S. Garberg, Gary Orenstein, Allison Kvedar, Joseph A randomized trial examining the effect of predictive analytics and tailored interventions on the cost of care |
title | A randomized trial examining the effect of predictive analytics and tailored interventions on the cost of care |
title_full | A randomized trial examining the effect of predictive analytics and tailored interventions on the cost of care |
title_fullStr | A randomized trial examining the effect of predictive analytics and tailored interventions on the cost of care |
title_full_unstemmed | A randomized trial examining the effect of predictive analytics and tailored interventions on the cost of care |
title_short | A randomized trial examining the effect of predictive analytics and tailored interventions on the cost of care |
title_sort | randomized trial examining the effect of predictive analytics and tailored interventions on the cost of care |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8175712/ https://www.ncbi.nlm.nih.gov/pubmed/34083743 http://dx.doi.org/10.1038/s41746-021-00449-w |
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