OPP001_PredictiveChronicCareAI 📄 Overview A SaMD platform leveraging continuous biometric data from wearables (HRV, sleep, activity, glucose trends where applicable) combined with EHR data and behavioral input to predict exacerbations or progression of chronic conditions (e.g., pre-diabetes, hypertension, early-stage CHF) and deliver personalized, proactive interventions and coaching. Key technologies: 👤 Target users: 👍 Benefits Reduced hospitalizations and emergency visits • Improved patient adherence to lifestyle changes and medication • Delayed disease progression • Enhanced quality of life • Lower healthcare costs Use bullets or new lines. 👎 Challenges Interoperability with diverse EHR systems • Maintaining patient engagement over time • Regulatory clearance for predictive diagnostics • Establishing clear clinical utility and reimbursement pathways • Data privacy and security at scale 📋 Regulatory & Validation Likely Class II SaMD, requiring premarket submission (510(k)) due to diagnostic and monitoring capabilities. Robust clinical validation studies will be essential. Post-market surveillance for algorithm changes.