State-of-the-art artificial intelligence (AI) technologies in the virtual care arena are pioneering a shift from reactive to responsive, and ultimately, to predictive healthcare.
Given the ongoing nursing shortages and heightened pressure on hospital resources, it’s more important than ever to create alternative care solutions rather than additional medical encounters. Collette Health is doubling down on turning this vision into a reality, combining virtual care with AI, machine learning (ML), and natural language processing (NLP) to craft an ecosystem in which continuous engagement and anticipatory interventions become the bedrock of patient care.
From Reactive to Proactive Healthcare
In traditional healthcare settings, nurses and other staff members can only respond to patient concerns as they arise, often requiring a reactive approach. They respond to call buttons, sometimes without knowing the specific reason for the call. When multiple calls come in, they find it a challenge to prioritize them effectively.
But virtual bedside access via persistent two-way audio and video communication streamlines the observation process and allows for more prompt and accurate responses. Collette Health has pioneered a system where a single observer can effectively monitor and manage the needs of 10 patients at a time.
Taking prevention, a step further is the integration of ML technologies that preemptively identify potential issues, such as alerting observers when high-risk patients attempt to get out of bed, thereby preventing falls or other adverse events before they happen.
Presence Detection and Continuous Engagement
Ensuring that all observers are genuinely engaged with their patients is a challenge, especially as virtual care extends the geographical boundaries within which care can be provided. This dilemma highlights a pressing question: How can healthcare providers guarantee that clinicians, whether in another part of the hospital or out of state, are actively monitoring their patients?
Enter Collette Health’s presence detection, which uses AI to foster attentiveness and improve patient outcomes. It alerts observers who look away from their screens for an extended period, nudging them back to attention with escalating visual and audio notifications. This tool not only safeguards patients but also gives hospitals the confidence that their teams are staying vigilant.
But the innovation doesn’t stop there. Advanced features such as motion detection technology, adaptable full-field night vision, and observer-controlled cameras are paving the way for a more proactive approach to patient care. Observers can now anticipate and prevent potential incidents, transforming from reactive spectators to active guardians.
Patient Surveillance Analytics
The fusion of AI and ML is also revolutionizing patient surveillance analytics, offering unprecedented leaps in personalized healthcare. These technologies harness real-time insights from a patient's medical stay that include event interventions, observer utilization, and compliance metrics to ensure each patient receives timely care.
Consider the potential: AI and ML can proactively address mental health needs by analyzing patterns in reported mood or sleep, confirming that each patient receives attention to the smallest details.
Moreover, in high-acuity settings, NLP becomes a powerful ally, facilitating real-time translations and interpretations for over 70 languages, including ASL. This ensures immediate and inclusive responses to every concern, enhancing safety and elevating the overall healthcare experience, one patient at a time.
Bridging the Gap to Predictive Healthcare
The industry has barely scratched the surface of these technologies. What is clear is that this new wave of AI tools is unlocking the potential of personalization, the ability to preemptively respond to events, and to help unburden our workforce. In this new era, tasks like admissions and discharge, patient education, note-taking by virtual scribes, and even shift-in-break coverage can be automated, reducing staff burnout and setting healthcare workers up for success.
These advances in virtual care transcend innovation; they are helping us craft deeper, more intuitive bonds between patients and caregivers. Hyper-personalization also extends beyond treating current conditions to anticipating and mitigating future health challenges. Hospitals are not just raising the bar in patient care; they are ensuring every interaction is meaningful, and every patient feels understood and valued while receiving the best possible care.