RADV - Risk Adjusted Diagnostic Validation

Clinical excellence begins with diagnostic accuracy. Risk Adjusted Diagnostic Validation (RADV) ensures therapeutic optimization is built on accurate diagnoses by leveraging independent AI-powered assessments against comprehensive clinical knowledge systems.

Any attempt at therapeutic optimization begins with the correct diagnosisor diagnoses. RADV assessment is a process in which clinical data (including proposed primary and secondary diagnoses) are evaluated against an independent evaluation of the knowledge system in clinical decision support mode.

The process is iterative. If the system requires additional information for clarification,questions are returned for further consideration. The system then returns an appropriate differential diagnosis for consideration.

The report will either return a 'Reasonable' conclusion (when theindependent assessment supports the proposed diagnosis) or 'Conflicted' (when
other diagnoses may be a better fit for the data). Failure to address an RADV report deviating significantly from the diagnosis submitted will result in an automatic Suboptimal ORDS score. This ensures clinical assessments are built on accurate diagnostic foundations before any therapeutic recommendations are made.

Optimal, Reasonable, Defensible, Suboptimal (ORDS) Scoring - The Therapeutic Optimization Framework

ORDS scoring is designed as a simple-to-understand reporting mechanism supported by an extensive evidence-based knowledge set that provides a transparent assessment of proposed clinical treatment plans. Unlike simple threshold-based notifications, which can lead to alert fatigue, our proprietary ORDS methodology systematically evaluates care patterns against peer-reviewed literature.

ORDS scoring is continuously updated to remain relevant as medicalknowledge evolves. Updating the scoring system is simple and does not require service interruptions. ORDS scoring also accounts for complex variationsrequired in patients with more than a single diagnosis.

The Ontological-Agentic AI system analyzes patient health profiles, medical history, and available lab and imaging data to compare proposed treatment plans with evidence-based medical literature and authoritative guidelines (e.g., the American Heart Association (AHA)). It returns an ORDS score with a complete rationale and supporting evidence. If additional data might affect final scoring, the system will present a series of questions for clarification.

Additional questions might follow based on the received answers. The goal is to provide fully transparent assessment criteria based solely on therapeutic optimization in line with medical best practices.

Four-Level ORDS Classification:

Optimal: Care aligns perfectly with evidence-based best practices for the individual's specific profile

Reasonable: Care falls within acceptable clinical standards (particularly in situations without clear consensus)

Defensible: Care meets minimum acceptable standards based upon resource limitations

Suboptimal: Care patterns indicate significant deviations from literature recommendations.

Opportunities for alternative care plans are included with Suboptimal score reports

ORDS scoring is notfixed. Based upon outcomes analysis of operational data sets, the boundaries of
each class are expected to adjust over time.

Applied Across Six Clinical Categories:

Wellness and preventive care
Health status and vital trends
Prevention of disease progression
Engagement and adherence
Therapeutic optimization
Quality of life metrics

The 3 R's Intervention Protocol: We deliver "the Right information, to the Right person, at the Right time" through intelligent triage. If one or more of the covered processes (prevention, diagnosis, disease management, medication adherence, engagement,etc.) are exhibiting suboptimal patterns, 3 R's triage is performed on each to determine the best care team member to engage and the appropriate timing of intervention triage to maximize efficient use of resources with the least disruption of routine workflow.

Triage Levels

Emergent: Immediate referral to clinical backup
Urgent: Response required within 24 hours
Routine: Intervention scheduled within 5 business days
Non-critical opportunities: Care enhancements added to monthly summary

This evidence-based classification and workflow system ensures your team receives nuanced, literature-backed clinical insights that consider the full complexity of each resident's situation, not just generic alerts. The ORDS framework solves the fundamental challenge facing Value-Based Care; it provides the quantifiable evidence and systematic workflow metrics necessary to demonstrate outcomes, justify interventions, and prove ROI.

Additional Details

Measurable Outcomes Through Continuous Quality Improvement(CQI):

Reduced hospital admissions through early intervention (critical for value-based arrangements)

Improved medication adherence and therapeutic outcomes (better health at lower cost)
Enhanced resident satisfaction and peace of mind (quality of life metrics matter)
Operational predictability with fewer medical emergencies (sustainable operations)
Competitive differentiation as a leader in proactive wellness management
Continuous care quality improvement validated by third-party analysis
Data-driven insights for ongoing service enhancement
Documentation and evidence required for value-based care contracting

Our collaboration with the American Heart Association can provide participating client organizations with:

Participation in groundbreaking outcomes research
Access to cutting-edge cardiovascular health management protocols
Third-party validation of care quality improvements
Thought leadership positioning in the senior care industry
The credibility and documentation needed for value-based care arrangements
De-identified Outcomes Analysis: Ongoing outcome validation and CQI assessment, measuring

Clinical notification accuracy and appropriateness:
Care team performance metrics
Identification of service enhancement opportunities
Population health trends and intervention effectiveness
The Force Multiplier Effect
Technology-enhanced nursing model: 1000s of residents monitored simultaneously through automated data collection from Bluetooth-enabled devices (BP monitors, pulse oximeters, glucometers, weight scales, Smart pillbox & thermometers)
AI-powered assessments combine objective device data with subjective digital questionnaire responses
Intelligent triage notifications stratified by severity (Critical/Urgent/Routine/Informational)
Literature-backed clinical rationale for every recommendation
Focused care delivery where nurses receive prioritized alerts and can conduct personalized, informed interventions

Our Agentic AI - Ontological solution synthesizes resident health profiles, medical history, connected device data, and medication adherence data, combined with digital questionnaire responses. The system uses this information to deliver evidence-based clinical insights to nursing staff, supported by peer-reviewed medical literature, enabling precise risk stratification and appropriate care escalation.

Simplified Complex Care Management: Helps maintain independence longer by collecting data from Bluetooth-connected biometric devices, including Blood Pressure Monitors, Weight Scales, Pulse Oximeters, Glucometers, Body Temperature Thermometers, and a Bluetooth Smart Pill Box, with data analyzed by our Ontological Knowledge System provides nurses with actionable assessments that reference peer-reviewed medical literature

Reduced Hospital Visits: Through both consistent monitoring and profile-specific therapeutic optimization across multiple chronic conditions

Empowered Healthcare Participation: Comprehensive education about how medications work, why timing matters, and the health consequences of missed doses

Reduced Medication Errors: Intelligent systems explicitly designed for polypharmacy management and drug interaction prevention

Improved Clinical Communication: Digital questionnaires help identify symptoms and concerns ross multiple conditions more effectively

Research-Backed Clinical Interventions: Leverage evidence-based protocols specific to complex comorbidity management to prevent health crises and optimize treatment effectiveness

Jan's Story: Eight Part Narrative

The Case for Distributed Care

Jan's Story - PowerPoint

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