Visiba Red Robin: AI-Powered Healthcare Triage System

Product Brief: Visiba Red Robin

Overview

Visiba provides advanced, AI-powered solutions for healthcare settings, focusing on patient triage and clinical workflow optimization. At the core of their offering is Red Robin, an automated anamnesis and triage system, designed to enhance efficiency, improve patient outcomes, and reduce costs in healthcare systems.

Core Features and Capabilities

1. Patient Triage System
   • Collects demographic and symptom data via free text input from patients.
   • Utilizes a probabilistic Bayesian model to analyze responses and determine potential diagnoses dynamically.
   • Does not rely on static pathways, adjusting probabilities in real-time based on patient answers.
   • Patients can submit multiple presenting complaints for comprehensive assessments.
2. AI-Powered Technology
   • Natural Language Processing (NLP): Maps patient input to approximately 1,000 nodes representing symptoms, diagnoses, or risk factors.
   • Dynamic Questioning: Adapts questions to refine diagnostic probabilities and triage levels, typically asking about 18 tailored questions per session.
   • Probabilistic Graphical Network: Integrates symptoms, diagnoses, and risk factors for accurate decision-making.
3. Seamless Integration
   • Quick plug-and-play setup with customer systems such as EHRs, telephony platforms, and web portals.
   • Modular architecture allows for customization to suit diverse healthcare environments.
   • Uses a limited number of API endpoints to streamline integration.
4. Regulatory Compliance and Data Protection
   • Class 2A MDR-certified product for safe deployment in healthcare settings.
   • Avoids storing identifiable patient data, ensuring compliance with stringent data protection regulations.
   • Patient authentication is managed entirely by customer systems.
5. Triage and Navigation Outputs
   • Provides an urgency level (scaled 1-8) and a list of differential diagnoses with probabilities.
   • Supports rules-based logic for care navigation, directing patients to appropriate services via API calls or self-service URLs.
   • Includes safety features for escalation, such as handling repeat callers.
6. UX and Patient Interaction
   • Allows patients to indicate uncertainty in responses for more accurate triage.
   • Collects time and trend data, including recurrence for chronic symptoms like headaches, to understand condition progression.
7. Clinical Decision Support
   • Offers detailed patient summaries to clinicians, including suggested diagnoses and explanations.
   • Visualizes diagnostic probabilities using a color-coded scale (e.g., dark blue to yellow for likelihood).
   • Real-time clinician feedback refines system accuracy and ensures transparency in decision-making.
8. Deployment and Scalability
   • Kubernetes-based platform enables deployment on containerized solutions like OpenShift.
   • Supports telephony integration, exemplified in partnerships like Adastra in the UK.
   • Optimized for translation and market-specific adaptations, typically requiring 3-6 months for new regions.

Market Applications

1. Acute and Primary Care
   • Focuses on triage for new or acute symptoms rather than chronic conditions.
   • Piloted in Sweden for social services and elderly home care, reducing professional intervention requirements.
2. Pre-Service Triage
   • Piloted in NHS England for pre-service triage to streamline patient navigation and reduce healthcare system burdens (e.g., 50% reduction in GP appointments).
3. Future Expansions
   • Chronic care pathways and mental health triage are under exploration.
   • Plans for follow-up triage to integrate previous episodes and patient histories.
4. Global Reach
   • Deployed in Nordic countries, with entry into the UK healthcare system via the NHS.
   • Exploring U.S. market entry, pending FDA approval and exclusivity agreements.

Technology and Infrastructure

• Built on a probabilistic graphical network for dynamic assessments.
• Uses AI-powered image analysis for assisting in diagnoses.
• Collaborates with Red Hat and IBM to explore insurance-driven opportunities.
• Operates on Kubernetes for flexibility and scalability.

Outcomes and Benefits

• Efficiency Gains: Demonstrated reduction in system costs and healthcare appointments.
• Enhanced Patient Flow: Improves navigation through healthcare pathways.
• AI-Driven Transparency: Emphasizes explainable AI to foster clinician trust.
• Scalable and Adaptable: Modular design allows quick adaptation to market-specific needs and future use cases.

Vision and Roadmap

Visiba aims to become a versatile, global triage platform that adapts to diverse healthcare pathways. Current plans include:

• Expanding chronic care and mental health applications.
• Enhancing follow-up session capabilities.
• Extending global reach within 24 months with necessary regulatory adaptations.
• Strengthening partnerships in insurance-driven and global markets.

Conclusion

Visiba’s Red Robin is a cutting-edge AI solution for healthcare, designed to optimize triage, enhance patient outcomes, and streamline clinical workflows. Its focus on transparency, compliance, and adaptability positions it as a leader in the evolving healthcare technology landscape.