Remote patient monitoring (RPM) promised to keep chronically ill patients at home while devices tracked vitals, reduce hospitalizations and leverage Medicare reimbursement to scale. Reality has exposed operational limits: data overload, workflow friction, patient adherence and staffing to monitor streams have limited clinical impact and return on investment, prompting vendors to pivot from pure devices toward integrated services.
Artificial intelligence is central to RPM’s next phase — using algorithms to triage alerts, filter noise and predict deterioration — but adoption is constrained by validation needs, interoperability with EHRs, bias and regulatory scrutiny. Health systems and payers now demand demonstrable outcomes and smoother clinician workflows; successful RPM deployments will pair validated AI analytics with managed services and clear reimbursement pathways.
