Aim: Remote patient management (RPM) effectively aids cardiovascular risk management, but its large-scale implementation remains challenging. Panel management may facilitate implementation by using comprehensive data to identify patients at risk of cardiovascular diseases and tai
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Aim: Remote patient management (RPM) effectively aids cardiovascular risk management, but its large-scale implementation remains challenging. Panel management may facilitate implementation by using comprehensive data to identify patients at risk of cardiovascular diseases and tailor interventions. This study evaluated the implementation strategies and clinical outcomes of a multi-component RPM intervention ‘Connect@Heart’. Methods: We conducted a mixed-methods study over six months in four primary care practices in the Netherlands, evaluating two patient groups: (i) patients with a BMI < 25 received a blood pressure monitor alone (BP Box), and (ii) patients with a BMI > 25 or cardiovascular disease received a combination of a BP monitor, a scale, and an activity tracker (Lifestyle Box). Baseline and six-month follow-up assessments were performed using linear mixed-effects models, and implementation outcomes were evaluated using the RE-AIM framework. Results: Our approach achieved high enrolment, with 189 out of 200 initially interested patients (94%) participating. The intervention was associated with a significant reduction in BP levels within both groups (BP Box systolic BP from 139 ± 21 mmHg at baseline to 132 ± 18 mmHg at follow-up, p < 0.001 and Lifestyle Box 142 ± 16 mmHg to 131 ± 14 mmHg at follow-up, p < 0.001), especially for those with uncontrolled hypertension. After six months, 66% of patients performed measurements weekly. All participating practices continued using the intervention post-study. Conclusion: This study demonstrates that proactively identifying patient panels at risk for CVD and tailoring multi-component RPM interventions to patient panels are promising implementation strategies for reaching favourable clinical outcomes at scale.