A Mobile Health Intervention to Improve Self-Care in Patients With Heart Failure: Pilot Randomized Control Trial

Abstract

BackgroundHeart failure (HF) is a progressive chronic disease affecting 6.5 million Americans and over 15 million individuals globally. Patients with HF are required to engage in complex self-care behaviors. Although the advancements in medicine have enabled people with HF to live longer, they often have poor health-related quality of life and experience severe and frequent symptoms that limit several aspects of their lives. Mobile phone apps have not only created new and interactive ways of communication between patients and health care providers but also provide a platform to enhance adherence to self-care management.ObjectiveThe aim of this pilot study was to test the feasibility of a newly developed mobile app (HeartMapp) in improving self-care behaviors and quality of life of patients with HF and to calculate effect sizes for sample size calculation for a larger study.MethodsThis was a pilot feasibility randomized controlled trial. Participants were enrolled in the hospital before discharge and followed at home for 30 days. The intervention group used HeartMapp (n=9), whereas the control group (n=9) received HF education. These apps were downloaded onto their mobile phones for daily use.ResultsA total of 72% (13/18) participants completed the study; the mean age of the participants was 53 (SD 4.02) years, 56% (10/18) were females, 61% (11/18) lived alone, 33% (6/18) were African Americans, and 61% (11/18) used mobile phone to get health information. The mean engagement with HeartMapp was 78%. Results were promising with a trend that participants in the HeartMapp group had a significant mean score change on self-care management (8.7 vs 2.3; t3.38=11, P=.01), self-care confidence (6.7 vs 1.8; t2.53=11, P=.28), and HF knowledge (3 vs −0.66; t2.37=11, P=.04. Depression improved among both groups, more so in the control group (−1.14 vs −5.17; t1.97=11, P=.07). Quality of life declined among both groups, more so in the control group (2.14 vs 9.0; t−1.43=11, P=.18).ConclusionsThe trends demonstrated in this pilot feasibility study warrant further exploration on the use of HeartMapp to improve HF outcomes.Trial RegistrationPilot study, no funding from National agencies, hence not registered.

Mobile Phone Apps to Support Heart Failure Self-Care Management: Integrative Review

“…Ten of the 18 studies included in this review had small sample sizes of 40 or fewer participants (8 studies assessed usability of the mobile system for refinement or further development of an algorithm [31-40]), 4 studies had sample sizes of 41 to 99 [41-44], and 4 studies had 100 or more participants (but fewer than 200) [45-48]. Four of the 18 studies reviewed were pilot RCTs [32,34,42,44], and only 2 RCTs had 100 or more participants [47,48]. Total sample from all 18 studies was 847 participants.…”

“…Recently, a usability study among minorities in the VA population (n=61) reported moderate program satisfaction scores (mean 6.84 [SD 0.46]) and improved self-efficacy and quality of life [42]. Another comprehensive app established usability and improved self-management and quality of life in a pilot RCT [10,32]. Providing HF education via MP3 player showed reduced readmission rates [41].…”

“…Seven of the included studies assessed self-management, of which 3 studies used the Self-Care of Heart Failure Index (SCHFI) [32,35,48], 2 studies used the European Heart Failure Self-Care Behavior Scale (EHFScBS) [42,44], 1 study used the Heart Failure Somatic Awareness Scale (HFSAS) [37], and 1 study used the personalized self-management system created within the mobile app [33]; all 7 of these studies reported improved self-management. Quality of life was measured by most studies, of which 5 used Minnesota Living With Heart Failure Questionnaire (MLHFQ) [31,34,39,42,48], 2 studies used the Kansas City Cardiomyopathy Questionnaire (KCCQ) [32,44], and 2 studies used the Short Form–36 (SF-36) [42,44]. All of the studies reported in general a trend for significant improvement in quality of life.…”

Prediction of Heart Disease Using Machine Learning Algorithms

“…CVD counteractive action measures are perceived as a basic focus by social insurance associations around the world. [4]. L.Sathish Kumar and A. Padmapriya has given a paper named Prediction for similarities of disease by using ID3 algorithm in television and mobile phone.…”

Lived Experiences and Technological Literacy of Heart Failure Patients and Clinicians at a Cardiac Care Centre in Uganda

“…diagnosed with this condition to enjoy an improved quality of life [8,9]. Accordingly, digital health interventions have recently been developed to simplify the process of managing and tracking the symptoms of HF [10][11][12][13][14][15][16][17][18][19]. One such intervention, which was developed alongside HF patients and clinicians living in Canada, has been shown to improve patient self-care and quality of life amongst Canadian HF patients [19,20].…”