Patient Adherence to a Mobile Phone-Based Heart Failure Telemonitoring Program: A Longitudinal Mixed-Methods Study

Patrick Ware, Mala Dorai, Heather J Ross, Joseph A Cafazzo, Audrey Laporte, Chris Boodoo, Emily Seto, Patrick Ware, Mala Dorai, Heather J Ross, Joseph A Cafazzo, Audrey Laporte, Chris Boodoo, Emily Seto

Abstract

Background: Telemonitoring (TM) can improve heart failure (HF) outcomes by facilitating patient self-care and clinical decision support. However, these outcomes are only possible if patients consistently adhere to taking prescribed home readings.

Objective: The objectives of this study were to (1) quantify the degree to which patients adhered to taking prescribed home readings in the context of a mobile phone-based TM program and (2) explain longitudinal adherence rates based on the duration of program enrollment, patient characteristics, and patient perceptions of the TM program.

Methods: A mixed-methods explanatory sequential design was used to meet the 2 research objectives, and all explanatory methods were guided by the unified theory of acceptance and use of technology 2 (UTAUT2). Overall adherence rates were calculated as the proportion of days patients took weight, blood pressure, heart rate, and symptom readings over the total number of days they were enrolled in the program up to 1 year. Monthly adherence rates were also calculated as the proportion of days patients took the same 4 readings over each 30-day period following program enrollment. Next, simple and multivariate regressions were performed to determine the influence of time, age, sex, and disease severity on adherence rates. Additional explanatory methods included questionnaires at 6 and 12 months probing patients on the perceived benefits and ease of use of the TM program, an analysis of reasons for patients leaving the program, and semistructured interviews conducted with a purposeful sampling of patients (n=24) with a range of adherence rates and demographics.

Results: Overall average adherence was 73.6% (SD 25.0) with average adherence rates declining over time at a rate of 1.4% per month (P<.001). The multivariate regressions found no significant effect of sex and disease severity on adherence rates. When grouping patients' ages by decade, age was a significant predictor (P=.04) whereby older patients had higher adherence rates over time. Adherence rates were further explained by patients' perceptions with regard to the themes of (1) performance expectancy (improvements in HF management and peace of mind), (2) effort expectancy (ease of use and technical issues), (3) facilitating conditions (availability of technical support and automated adherence calls), (4) social influence (support from family, friends, and trusted clinicians), and (5) habit (degree to which taking readings became automatic).

Conclusions: The decline in adherence rates over time is consistent with findings from other studies. However, this study also found adherence to be the highest and most consistent over time in older age groups and progressively lower over time for younger age groups. These findings can inform the design and implementation of TM interventions that maximize patient adherence, which will enable a more accurate evaluation of impact and optimization of resources.

International registered report identifier (irrid): RR2-10.2196/resprot.9911.

Keywords: adherence; heart failure; mHealth; telemonitoring.

Conflict of interest statement

Conflicts of Interest: HR, JC, and ES are considered inventors of the Medly system under the intellectual property policies of the UHN and may benefit from future commercialization of the technology by UHN.

©Patrick Ware, Mala Dorai, Heather J Ross, Joseph A Cafazzo, Audrey Laporte, Chris Boodoo, Emily Seto. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 26.02.2019.

Figures

Figure 1
Figure 1
Screens of the Medly app showing the incomplete morning card with required readings, the symptoms questionnaire, and personalized self-care feedback after all 4 readings were taken and processed by the algorithm.
Figure 2
Figure 2
Average full adherence rates compared with adherence rates which include incomplete adherence over time.
Figure 3
Figure 3
Average adherence rates over time by age group showing higher adherence over time for older age groups.

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