In the evolving healthcare scenario, mobile health (mHealth) technologies are emerging as pivotal tools in cardiac rehabilitation (CR). A recent systematic review and meta-analysis published in The Lancet Digital Health underscores the efficacy of home-based CR interventions delivered via mHealth technologies.
The findings highlight the growing role of mHealth in providing remote cardiac rehabilitation and improving outcomes for patients managing heart disease.
Key Findings
- Enhanced Physical Activity: The study analyzed data from multiple randomized controlled trials and found that mHealth interventions significantly increased moderate-to-vigorous physical activity (MVPA) among cardiac patients. This improvement is crucial, as increased physical activity is linked to better cardiovascular outcomes.
- Improved Adherence: Patients engaging with mHealth tools demonstrated higher adherence rates to prescribed exercise regimens compared to traditional center-based programs. Features like real-time feedback, goal setting, and remote monitoring contributed to sustained engagement.
- Comparable Clinical Outcomes: The analysis showed that mHealth-based CR programs had clinical results similar to traditional CR, including better blood pressure, cholesterol levels, and body weight.
Implications for Healthcare
The integration of mHealth technologies into CR programs offers a scalable solution to overcome barriers such as geographic limitations, scheduling conflicts, and resource constraints. By facilitating remote monitoring and personalized feedback, mHealth tools empower patients to take an active role in their recovery journey.
Moreover, the flexibility of mHealth interventions aligns with the growing demand for patient-centered care, allowing individuals to engage in rehabilitation activities at their convenience without compromising efficacy.
Future Directions
While the findings are promising, further research is needed to explore the long-term sustainability of mHealth interventions in CR. Areas of interest include the integration of artificial intelligence for personalized care plans, the use of gamification to enhance engagement, and strategies to ensure data security and patient privacy.
As healthcare continues to embrace digital transformation, mHealth stands out as a viable and effective modality to extend the reach and impact of cardiac rehabilitation programs.
Study Methodology and Data Analysis
This systematic review and meta-analysis followed the Cochrane Collaboration methodology and was reported per the PRISMA guidelines. The protocol was registered with PROSPERO (CRD42024544087). Eligible studies included randomized controlled trials (RCTs) of adult patients (≥18 years) who had undergone myocardial infarction, experienced angina pectoris, underwent coronary revascularization, or had stable chronic heart failure. These trials focused on phase II mHealth-based cardiac rehabilitation (mHealth HBCR), using non-invasive portable and wireless technologies (such as smartphones, wearable devices, mobile apps, and text messages). The comparison group consisted of usual care or center-based cardiac rehabilitation (CBCR).
Four databases—MEDLINE, CENTRAL, CINAHL, and Embase—were searched up to March 31, 2023, with no language restrictions. Trials focused on phase I or phase III cardiac rehabilitation, abstract-only publications, and non-English articles (without possible translation) were excluded. A comprehensive search strategy was developed, and all references were screened in Covidence software.
Data Extraction and Analysis
Two independent reviewers extracted data on study design, patient demographics, intervention components, and outcomes. For missing data, we contacted the corresponding authors. Risk of bias was assessed using the Cochrane risk of bias tool, which evaluates random sequence generation, allocation concealment, masking, and incomplete outcome data.
The primary outcome was aerobic exercise capacity, measured by VO2 peak or the 6-minute walk test (6MWT). Secondary outcomes included BMI, blood pressure, heart rate, lipid profile, and self-reported outcomes such as anxiety, depression, and quality of life. A random-effects meta-analysis was performed due to the clinical heterogeneity across studies. Statistical heterogeneity was assessed using the I² statistic, and subgroup analyses were planned for effect modifiers like exercise dose, patient case mix, and follow-up duration.
Quality of Evidence
The GRADE framework was used to assess the quality of evidence, considering factors like risk of bias, inconsistency, and imprecision. The evidence was rated as high, moderate, low, or very low, depending on the confidence in the results.
For a comprehensive understanding, access the full study here: The Lancet Digital Health.
