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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...

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Autores principales: Shah, Lochan M., Ding, Jie, Spaulding, Erin M., Yang, William E., Lee, Matthias A., Demo, Ryan, Marvel, Francoise A., Martin, Seth S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2021
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.
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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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