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Sociodemographic Characteristics Predicting Digital Health Intervention Use After Acute Myocardial Infarction
Increasing evidence suggests that digital health interventions (DHIs) are an effective tool to reduce hospital readmissions by improving adherence to guideline-directed therapy. We investigated whether sociodemographic characteristics influence use of a DHI targeting 30-day readmission reduction aft...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8127845/ https://www.ncbi.nlm.nih.gov/pubmed/33999374 http://dx.doi.org/10.1007/s12265-021-10098-9 |
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author | Shah, Lochan M. Ding, Jie Spaulding, Erin M. Yang, William E. Lee, Matthias A. Demo, Ryan Marvel, Francoise A. Martin, Seth S. |
author_facet | Shah, Lochan M. Ding, Jie Spaulding, Erin M. Yang, William E. Lee, Matthias A. Demo, Ryan Marvel, Francoise A. Martin, Seth S. |
author_sort | Shah, Lochan M. |
collection | PubMed |
description | Increasing evidence suggests that digital health interventions (DHIs) are an effective tool to reduce hospital readmissions by improving adherence to guideline-directed therapy. We investigated whether sociodemographic characteristics influence use of a DHI targeting 30-day readmission reduction after acute myocardial infarction (AMI). Covariates included age, sex, race, native versus loaner iPhone, access to a Bluetooth-enabled blood pressure monitor, and disease severity as marked by treatment with CABG. Age, sex, and race were not significantly associated with DHI use before or after covariate adjustment (fully adjusted OR 0.98 (95%CI: 0.95–1.01), 0.6 (95%CI: 0.29–1.25), and 1.22 (95% CI: 0.60–2.48), respectively). Being married was associated with high DHI use (OR 2.12; 95% CI 1.02–4.39). Our findings suggest that DHIs may have a role in achieving equity in cardiovascular health given similar use by age, sex, and race. The presence of a spouse, perhaps a proxy for enhanced caregiver support, may encourage DHI use. GRAPHICAL ABSTRACT: [Image: see text] SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12265-021-10098-9. |
format | Online Article Text |
id | pubmed-8127845 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-81278452021-05-18 Sociodemographic Characteristics Predicting Digital Health Intervention Use After Acute Myocardial Infarction Shah, Lochan M. Ding, Jie Spaulding, Erin M. Yang, William E. Lee, Matthias A. Demo, Ryan Marvel, Francoise A. Martin, Seth S. J Cardiovasc Transl Res Original Article Increasing evidence suggests that digital health interventions (DHIs) are an effective tool to reduce hospital readmissions by improving adherence to guideline-directed therapy. We investigated whether sociodemographic characteristics influence use of a DHI targeting 30-day readmission reduction after acute myocardial infarction (AMI). Covariates included age, sex, race, native versus loaner iPhone, access to a Bluetooth-enabled blood pressure monitor, and disease severity as marked by treatment with CABG. Age, sex, and race were not significantly associated with DHI use before or after covariate adjustment (fully adjusted OR 0.98 (95%CI: 0.95–1.01), 0.6 (95%CI: 0.29–1.25), and 1.22 (95% CI: 0.60–2.48), respectively). Being married was associated with high DHI use (OR 2.12; 95% CI 1.02–4.39). Our findings suggest that DHIs may have a role in achieving equity in cardiovascular health given similar use by age, sex, and race. The presence of a spouse, perhaps a proxy for enhanced caregiver support, may encourage DHI use. GRAPHICAL ABSTRACT: [Image: see text] SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12265-021-10098-9. Springer US 2021-05-17 2021 /pmc/articles/PMC8127845/ /pubmed/33999374 http://dx.doi.org/10.1007/s12265-021-10098-9 Text en © The Author(s), under exclusive licence to Springer Science+Business Media, LLC part of Springer Nature 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Original Article Shah, Lochan M. Ding, Jie Spaulding, Erin M. Yang, William E. Lee, Matthias A. Demo, Ryan Marvel, Francoise A. Martin, Seth S. Sociodemographic Characteristics Predicting Digital Health Intervention Use After Acute Myocardial Infarction |
title | Sociodemographic Characteristics Predicting Digital Health Intervention Use After Acute Myocardial Infarction |
title_full | Sociodemographic Characteristics Predicting Digital Health Intervention Use After Acute Myocardial Infarction |
title_fullStr | Sociodemographic Characteristics Predicting Digital Health Intervention Use After Acute Myocardial Infarction |
title_full_unstemmed | Sociodemographic Characteristics Predicting Digital Health Intervention Use After Acute Myocardial Infarction |
title_short | Sociodemographic Characteristics Predicting Digital Health Intervention Use After Acute Myocardial Infarction |
title_sort | sociodemographic characteristics predicting digital health intervention use after acute myocardial infarction |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8127845/ https://www.ncbi.nlm.nih.gov/pubmed/33999374 http://dx.doi.org/10.1007/s12265-021-10098-9 |
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