8. Remote Patient Monitoring & Predictive Analytics

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8. Remote Patient Monitoring & Predictive Analytics    

Remote patient monitoring (RPM) platforms combine wearable sensors, connected medical devices (blood pressure cuffs, pulse oximeters, glucometers, ECG patches), and predictive machine-learning models to track chronic-disease and post-acute patients outside the hospital, flagging clinicians when a patient's vital signs trend toward deterioration so care teams can intervene before an ER visit or readmission becomes necessary. This overlaps with "hospital-at-home" programs, where AI-driven monitoring allows patients who would otherwise be admitted to instead recover safely at home under continuous virtual observation. These platforms are sold to health systems and payers on a per-patient-per-month (PPPM) basis, usually layered on top of separate device/hardware costs, and are almost never offered directly to individual consumers or with a public price list — engagement always starts with a sales conversation and a pilot program sized to the health system's patient population and reimbursement model (Medicare's RPM billing codes, for instance, shape how these programs are typically structured and paid for).