Our
Approach
WHO WE ARE:​
​P3 Quality™ is a HealthTech company specializing in designing AI AuditME™ Methods. We work with healthcare leaders and organizations to develop AI-driven revenue cycle management (RCM) Mitigation and Optimization (MO) Frameworks, as well as provide Consulting Services.
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P3 Core Values | People, Processes & Principles
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WHAT WE DO:​
P3 Core Focus | AI in RCM Audits
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RCM Consulting (Revenue Integrity, CDI & HIM)
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AI Audits, Mitigation & Optimization
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​DNFB Automation, Mitigation & Optimization
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​​The P3 Quality™ Quotient = Quality First | Quality Forward ​​​​​
​​​​We are proud to be certified nationally by the Women's Business Enterprise National Council (WBENC).
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Our
Methodology
METHODS:
AI in RCM and Responsible AI AuditME™ Frameworks:
Compliant, Accountable, Responsible, and Ethical Use of AI:
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NAIC-Aligned Standards:
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Governance
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Transparency
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Accountability & Responsibility
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Data Quality, Privacy & Protections
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Testing & Validation
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Security & Risk Mitigation
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Third-Party BAA & Vendor Risks
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Consumer Protections
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Ongoing Audits, Monitoring & Maintenance​
CDI & CODING AUTOMATION
AI ENHANCEMENTS & WORKFLOWS
AI/ML-CDI Assistant Performance
CDI Automation Auto-Suggests
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Are the Alternate ICD-10 codes for greater specificity selected by AI accurate?
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Why are CPT Codes for documented procedures missing when automated, but showing up as billed?
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Ethical Use of AI/ML ​
Are the AI Automatic Flags working properly?
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For Diagnosis?
(e.g., ICD-10 Codes)
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Medically Necessity Alerts?
(payer LCD/NCD policies)
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Clinical Documentation?
(H&P, CPT Codes, Charge Notes, etc.)​
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CHARGE CORRECTION
AI AUTOMATION RULES
Charge Errors
When CDI Automation Flags an Issue that requires Correction, is the root cause of the inconsistency reviewed? Was it an AI or a human error?
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When Routed to the CDI/Coding Team
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Are AI documentation/coding inconsistencies verified, validated, and discussed with the vendor? ​
AI ​QUALITY CONTROL​​
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HOW IS PERFORMANCE MEASURED?
Algorithms, Data Integrity & KPIs
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WHO IS MONITORING?
AI Dashboards:
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How well is AI performing?
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Quality Checks:
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What are the AI performance metrics?
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Algorithm Integrity Checks:
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Who is tracking and trending the output? (e.g., algorithmic performance, AI Data errors, AI inconsistencies, and other various types of findings).
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