Sociodemographic Characteristics Predicting Digital Health Intervention Use After Acute Myocardial Infarction.

Lochan M Shah, Jie Ding, Erin M Spaulding, William E Yang, Matthias A Lee, Ryan Demo, Francoise A Marvel, Seth S Martin

Journal: Journal of cardiovascular translational research 2022;14(5):951-961

PMID: 33999374

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Abstract

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.

Address: Johns Hopkins University School of Medicine, Baltimore, MD, USA.; Digital Health Innovation Laboratory, Ciccarone Center for the Prevention of Cardiovascular Disease, Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA.; Johns Hopkins University School of Nursing, Baltimore, MD, USA.; Johns Hopkins Center for Mobile Technologies to Achieve Equity in Cardiovascular Health (mTECH), an AHA SFRN Center for Health Technology and Innovation, Baltimore, MD, USA.; Johns Hopkins University Whiting School of Engineering, Baltimore, MD, USA.; Johns Hopkins University School of Medicine, Baltimore, MD, USA. [email protected].; Digital Health Innovation Laboratory, Ciccarone Center for the Prevention of Cardiovascular Disease, Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA. [email protected].; Johns Hopkins Center for Mobile Technologies to Achieve Equity in Cardiovascular Health (mTECH), an AHA SFRN Center for Health Technology and Innovation, Baltimore, MD, USA. [email protected].; Johns Hopkins University Whiting School of Engineering, Baltimore, MD, USA. [email protected].

DOI: 10.1007/s12265-021-10098-9

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MeSH Terms: Adult, Age Factors, Aged, Aged, 80 and over, Attitude to Computers, Blood Pressure, Blood Pressure Monitoring, Ambulatory, Coronary Artery Bypass, Female, Health Knowledge, Attitudes, Practice, Humans, Male, Marital Status, Medication Adherence, Middle Aged, Myocardial Infarction, Patient Acceptance of Health Care, Patient Readmission, Prospective Studies, Race Factors, Secondary Prevention, Self Care, Sex Factors, Smartphone, Telemedicine, Time Factors, Treatment Outcome, United States