Our
Approach
HUMAN CENTRIC AI:​
​P3 Quality™ is an Artificial Intelligence (AI) Tech company with specialities in AI in Revenue Cycle research, development, and issue resolution management, with a key focus on achieving customer success initiatives.
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OUR CORE VALUES:
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People, Processes & Principles
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Human Centric AI ​Solutions
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AI SOLUTIONS FOR RCM RISK MITIGATION:
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AI AuditME™ Product Design
AI-DRIVEN AUDIT SERVICES​​
Detect, Diagnose, Resolve & Improve
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AI Model Data Drift & Hallucinations​
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Automated Coding Abstraction & Validation
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Quality Assurance | Quality Control Inconsistencies
KEENLY FOCUSED ON: ​​
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Revenue Integrity, HIM, CDI & RCM Functions
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RCM Robotic Processing Automation (RPA)
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AI Needs Assessment | AI Gap Analysis
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Advancing Human In the Loop (HITL) Governance Models
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Building Frameworks
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Standardizing Broken Processes
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REDUCING AI DRIFT & HALLUCINATIONS:
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Executives are investing heavily in AI-driven technologies
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Still seeing high volumes of documentation, coding, and denial errors
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Rework consuming Return on Investment (ROI) gains
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You have questions? | We have Answers!
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P3 QUALITY is a WBE, nationally certified by the Women's Business Enterprise National Council (WBENC).
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Our
Methodology
AI AUDIT METHODOLOGY:
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​
WHAT IS HUMAN CENTRIC AI?
SMART COMPUTER TECHNOLOGY
Human-Centric AI is smart computer technology that works with people. It is a very helpful assistant. But humans are allowed to make the final decisions.
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HEALTH DEMOGRAPHICS VALIDATION​
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Verify accuracy
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Correct errors
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Decide next steps ​
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Review AI suggestions
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Trust human-in-the-loop decisions
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QUALITY/COMPLIANCE AUDIT RISKS
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AI flags the risk
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Humans should confirm applicability​​
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Humans should classify severity
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Keenly focused on reducing and avoiding risks
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EXPLAINABILITY AND AUDIT DEFENSIBILITY
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Human-centric AI should
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Show why the issue has been flagged
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Link findings to
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Policies/procedures
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Payer rules
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Historical baselines
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Identify AI-related inconsistencies
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Improve confidence levels
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AI | RCM | RPA AUTOMATION
DOCUMENTATION AND CODING
Inconsistent CDI Flag Errors
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​Upcoded/Undercoded E/M Levels​​​​
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Incorrect Procedural Hierarchies
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Misassigned Chronic Conditions
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AI ERRORS CREATE
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Quality/Compliance Exposure
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Payer Audit Risks
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Ethical/Legal Implications
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THIS STEMS FROM
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AI Drift and Hallucinations​
MONITOR AI DRIFT & HALLUCINATIONS​​
AI Algorithm errors erode trust between patients, providers, and payers:
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Coding Errors Increase
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Providers Lose Confidence in Automated Coding Systems
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Patients Dispute Bills
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RCM Leaders Distrust Their AI Investment
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MONETIZE KEY PERFORMANCE INDICATORS (KPIs):
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Accuracy Variance (AI model output)
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Coding/CDI Disagreement Rates
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Claim Denial Spikes tied to AI-Generated logic
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Charge Capture Changes > 10 YOY w/o Clinical Justification
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DNFB Increase Linked to AI Inconsistencies
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​Unexpected MUE, CCI, HCC, or DRG shifts
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Payer Rule Incompatibilities
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