AI Remote Patient Monitoring and Triage

The AI Hospital at Home category focuses on expanding clinical care beyond traditional hospital settings through the use of advanced remote patient monitoring (RPM) technologies. These systems continuously collect patient data from wearable and in-home devices and upload it directly into electronic health records (EHR). Clinicians, especially nurses, can remotely monitor numerous patients at once, identifying early signs of deterioration to intervene proactively and prevent emergency visits or hospital readmissions. This model enables hospitals to discharge patients earlier while ensuring ongoing care, freeing up beds for more critical cases. One of the main challenges with AI Hospital at Home solutions is ensuring reliable data collection, particularly when patients or their caregivers are responsible for operating devices. Early RPM technologies that relied on manual input often faced usability issues, resulting in inaccurate or incomplete data. However, advances in automation and AI-driven devices are minimizing patient involvement, improving the reliability of data collection through continuous monitoring, fostering greater trust in remote care models.

The Inpatient Risk Monitoring category focuses on AI-powered solutions that continuously track patient data within healthcare facilities to detect early signs of deterioration and prevent adverse events. These platforms aggregate data from EHRs, bedside monitors, lab results, and clinical notes, providing clinicians with real-time insights directly within their workflows. The goal is to enable timely interventions, reduce hospital-acquired conditions, and improve patient outcomes. Key use cases include sepsis detection, fall risk management, and ICU decision support. These tools adapt to individual patient needs by learning from clinician feedback, refining predictions over time for greater precision. By integrating with existing hospital protocols and workflows, inpatient risk monitoring solutions optimize care delivery, reduce readmissions, and enhance operational efficiency, ultimately supporting safer and more effective inpatient care.

Virtual Nursing focuses on utilizing technology and clinicl staff to support and extend the capabilities of existing nursing staff in healthcare settings. Capabilities here include using artificial intelligence and video monitoring to assist with routine patient interactions and monitoring, as well as remote patient monitoring with nursing support and the ability to escalate to local providers.