Our
Approach
P3 | People, Processes & Principles
The Quality Quotient | Quality First | Quality Forward
​P3 Quality is a unique type of HealthTech Company that offers specialized consulting services, helping healthcare leaders and organizations identify AI-driven revenue cycle management (RCM) spin vs. AI Return on Investment (ROI) opportunity wins.
P3 AI patent-pending, proprietary technology analyzes AI's Performance. Is AI delivering on ROI results as promised?
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Performance Outcomes
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AI in RCM Assessment Wrap Up
We are proud to be certified nationally by the Women's Business Enterprise National Council (WBENC).
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​Our Principal and Managing Consultant is ISO:9001 certified as an Internal Auditor and has been working with AI in RCM technology products for over fifteen years.
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Our
Methodology
Revenue Cycle Management (RCM), Revenue Integrity (RI), and Payment Integrity (PI) are all critical elements of the healthcare finance, claims processing, and artificial intelligence (AI) life cycle. All are playing an increasingly crucial role in the medical coding, documentation, billing, and revenue management process.
P3 recommends establishing Compliant, Accountable, Responsible, and Ethical AI in RCM Best Practices:
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Quality/Compliance Program Elements:
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Oversight
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Standards/Procedures
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Education Training
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Effective Lines of Communication
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Responding to Detected Offenses
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Implement Consistent Audit & Monitoring Protocols
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Enforce Quality and Compliance Standards
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Additional Service Offerings:
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Address Manual Audit, Reporting Inconsistencies and Risks
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Automate Customized Quality/Compliance Solutions
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Design AI-Powered Performance Dashboards
CDI AUTOMATION
ENHANCEMENTS & WORKFLOWS
AI/ML-Based CDI Assistant
CDI Automation Auto-Suggests
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Alternate ICD-10 codes for greater specificity
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Missing CPT Codes for documented procedures that are showing up as billed.
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Epic's System Uses AI/ML ​
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Diagnosis Mismatches
(e.g. Missing ICD-10 Codes)
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Medically Necessity Alerts
(based on payer LCD/NCD policies)
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Clinical Documentation Gaps
(Missing H&P, CPT Codes, Charges, etc.)​
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CHARGE CORRECTION & AUTOMATION RULES
Correcting Charge Errors
When CDI Automation Flags an Issue that requires Correction
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Accept the Suggested Fix
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e.g., replace the ICD-10 /CPT code, add a modifier
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Route to CDI/Coding Team
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If documentation requires provider clarification
CDI Override Alert:
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If the documentation supports the charge as-is
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AI PERFORMANCE MONITORING & ​QUALITY CONTROL​
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AI ADOPTION OPPORTUNITIES
Static KPIs, Quality, and Algorithms
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NOW & FUTURE STATE:
Real-Time AI Dashboards:
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How AI performs when detecting and flagging documentation, coding, and charges errors, as well as identifying workflow bottlenecks.
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Quality Checks:
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What is the AI performance metric for flagging outpatient visits or inpatient stays? Do they require human review? What are the volumes?
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Algorithmic Integrity Checks:
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If AI is tracking and monitoring itself continuously?
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Who is assessing the accuracy of what AI is detecting, flagging, capturing, and reporting? (e.g., algorithmic performance, AI Data errors, AI tracking inconsistencies, and various other types of findings).
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