Patient Demographics and Clinic Type Are Associated With Patient Engagement Within a Remote Monitoring Program

Abstract

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.

Keywords: health disparities; primary care; remote monitoring; telemedicine; underserved populations.

Fig. 1.

Transmission engagement over time. (a) Percentage of cohort, by race, who achieve data transmission engagement by week after remote monitoring initiation, where engagement is defined as a minimum of one transmission on 3 or more separate days per week. Week 1 is the first week after monitoring initiation; week 52 is the final week (after 1 year of monitoring). Non-Black includes participants identifying as White, Caucasian, Native American, Pacific Islander, Native Hawaiian, Alaskan Native, missing race data, or other. Non-Black represented by black line. Black represented by gray line. (b) Percentage of cohort, by clinic site, who achieve data transmission engagement by week after remote monitoring initiation. Academic clinic represented by black line, FQHC by dark gray line, and free clinics by light gray line. (c) Percentage of cohort, by gender, who achieve data transmission engagement by week after remote monitoring initiation. Female represented by black line. Male represented by gray line. (d) Percentage of cohort, by age group, who achieve data transmission engagement by week after remote monitoring initiation. Age 18 to 44 years represented by black line, ages 45 to 64 years by dark gray line, and age 65 years and older by light gray line. (e) Percentage of cohort, by self-reported income, who achieve data transmission engagement by week after remote monitoring initiation. Higher income (black line) is defined as an annual household income of $20,000 or more, and low income (gray line) is defined as <$20,000 per year. FQHC, federally qualified health center.