Patient Demographics and Clinic Type Are Associated With Patient Engagement Within a Remote Monitoring Program
Autor: | Andrew D. Schreiner, Justin Marsden, Elizabeth B. Kirkland, Marc Heincelman, Patrick D. Mauldin, Samuel O. Schumann, Jingwen Zhang, William P. Moran |
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Rok vydání: | 2021 |
Předmět: |
Adult
Male Telemedicine 020205 medical informatics Patient demographics Health Informatics Patient engagement 02 engineering and technology Primary care Vulnerable Populations Underserved Population Health Information Management 0202 electrical engineering electronic engineering information engineering Humans Medicine Prospective Studies Aged Demography Glycated Hemoglobin business.industry food and beverages General Medicine Middle Aged equipment and supplies medicine.disease Monitoring program Health equity Diabetes Mellitus Type 2 Physiological monitoring Female Medical emergency Patient Participation business |
Zdroj: | Telemed J E Health |
ISSN: | 1556-3669 1530-5627 |
Popis: | Background: Remote physiological monitoring (RPM) is accessible, convenient, relatively inexpensive, and can improve clinical outcomes. Yet, it is unclear in which clinical setting or target population RPM is maximally effective. Objective: To determine whether patients' demographic characteristics or clinical settings are associated with data transmission and engagement. Methods: This is a prospective cohort study of adults enrolled in a diabetes RPM program for a minimum of 12 months as of April 2020. We developed a multivariable logistic regression model for engagement with age, gender, race, income, and primary care clinic type as variables and a second model to include first-order interactions for all demographic variables by time. The participants included 549 adults (mean age 53 years, 63% female, 54% Black, and 75% very low income) with baseline hemoglobin A1c ≥8.0% and enrolled in a statewide diabetes RPM program. The main measure was the transmission engagement over time, where engagement is defined as a minimum of three distinct days per week in which remote data are transmitted. Results: Significant predictors of transmission engagement included increasing age, academic clinic type, higher annual household income, and shorter time-in-program (p < 0.001 for each). Self-identified race and gender were not significantly associated with transmission engagement (p = 0.729 and 0.237, respectively). Conclusions: RPM appears to be an accessible tool for minority racial groups and for the aging population, yet engagement is impacted by primary care location setting and socioeconomic status. These results should inform implementation of future RPM studies, guide advocacy efforts, and highlight the need to focus efforts on maintaining engagement over time. |
Databáze: | OpenAIRE |
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