Wearable Health Technology in Pharmacy-Led Remote Patient Monitoring

Abstract

Background: Community and hospital pharmacists increasingly coordinate remote patient monitoring (RPM) programs that use wearable health technology to capture real-time physiological signals (e.g., heart rate, rhythm, blood pressure, glucose, oxygen saturation) and translate them into timely medication and lifestyle interventions. Despite rapid diffusion, questions remain about clinical effectiveness, workflow integration, equity, data quality, and privacy. Objective: To synthesize current knowledge on pharmacy-led RPM with wearables, propose a rigorous evaluation framework, and describe a pragmatic protocol that can be implemented in routine pharmacy practice to assess clinical, human-factors, and implementation outcomes. Methods: We outline a mixed-methods, clusterrandomized pragmatic trial comparing usual pharmacist care with a pharmacist-managed RPM service augmented by validated wearables and a rules-based alerting system. Adult patients with hypertension, type 2 diabetes, and/or heart failure are enrolled through participating pharmacies. Primary outcomes include mean change in systolic blood pressure (SBP), HbA1c, 30-day all-cause emergency department (ED) visits, and medication adherence (proportion of days covered, PDC). Secondary outcomes include patient activation, device usability, clinician workload, and equity indicators. Quantitative analyses use intention-to-treat mixed-effects models; qualitative analyses use thematic analysis of interviews and field notes. A detailed operating protocol covers recruitment, onboarding, calibration, alert thresholds, triage, documentation, data governance, and safety oversight. Results (illustrative): The protocol anticipates a clinically meaningful SBP reduction of ~5–7 mmHg, a 0.3–0.5% HbA1c decrease, a relative 15–25% reduction in 30-day ED visits for chronic-condition subsets, and a 6–10 percentage-point improvement in PDC, with high usability scores and acceptable pharmacist workload after a short learning curve. We also expect disparities to narrow when language-appropriate education and lowcost device options are offered. Conclusion: Pharmacy-led RPM with wearables is a feasible, safe, and potentially impactful model for chronic disease management. Success depends on device validation and calibration workflows, human-in-the-loop clinical triage, privacy-preserving data pipelines, reimbursement alignment, and attention to digital inclusion. The proposed methodology and protocol provide an actionable blueprint for real-world evaluation and scale-up.