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AI Machine Learning (ML) in RCM

        Artificial Intelligence (AI) IN RCM   
     MEASURe | MONITOR | MONETIZE

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Our
Approach

P3 Quality is an Artificial Intelligence (AI) Tech company. We evaluate AI Automation tools, systems, and services for vendors, providers, and hospitals.  

 

In Revenue Cycle Management (RCM), AI performs tasks that leverage healthcare data to meet revenue benchmarks;  AuditMe™ Q-Check verifies whether those actions can be trusted.

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ARTIFICIAL INTELLIGENCE (AI) EXPERTISE 

As an Independent ISO 9001-Certified Internal Audit expert and Risk Mitigation Advisor. We inspect inconsistencies in AI-related governance and remediation! We assess AI trends, inefficiencies, pattern-recognition issues, and process failures.

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AI CORE ISSUES

  • Drifting Off a Cliff​​​​

  • Hallucinating Errors 
  • Misfiring Prompts 

 

P3 SOLUTIONS:​​

  • People, Processes & Principles 

  • Human-in-the-Loop Oversight

  • Diagnosing AI Issues

  • Identify/Prioritize inconsistencies & inefficiencies

  • Measure ROI & Capture Success Trends/Metrics

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TRUSTED & UNBIASED TOOL CHEST​​​

  • ISO 9001, CMS, MAC, HIPAA, PHI, TPA, etc

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RISK REMEDIATION SERVICES

  • AI AuditME™ Q-Check

  • Governance Remediation Frameworks​​​

 

P3 QUALITY Dual Certifications WBE / WBENC and a Georgia (SBSD) Certified Small Woman-Owned Business.

Our
Methodology

AI AUDITME™ 

Q-Check Methodology: Corporate, Accountable, Responsible,

and Ethical Use of AI:

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​​​​ISO-9001 ALIGNED STRATEGIES:

  1. Corporate Governance and Disclosure 

  2. Transparency 

  3. Risk Mitigation and Internal Controls 

  4. Regulatory Oversight | Quality | Compliance 

  5. AI Third-Party Systems and Data Risks​ 

P3 FOCUS | AI PERFORMANCE GAPS

HUMAN-CENTRIC AI

We are Human-Centric AI Smart Specialists

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EVALUATING AI LLMs OR AGENTIC ERRORS​

  • AI/Automated Task Flaws

    • Data Input/Output Issues​​

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THE QUALITY/COMPLIANCE RISK IMPACT

  • Flaging AI Model risks

    • Drift​​

    • Hallucinations

    • Misfires

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AI DEFENSIBILITY 

  • Identifying/Explaining AI System Spikes

    • Algorithmic Failures 

    • ​Risk Exposure 
    • Rework

 

TYPICAL BARRIERS

  • Selective Transparency​​​​​​​​

  • AI Dependency/Trustworthiness

  • Budgetary Constraints

AuditME™ FRAMEWORK

 

AI-RCM GOVERNANCE REMEDIATION 

Automate and Regulate Checks/Balances

  • Coding/CDI Governance ​​​​​

  • Risk Exposure 

  • Compliance

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ETHICAL OVERSIGHT

  • Human-In-The-Loop (HITL) Supervision

  • Algorithmic Bias Audits & Monitoring 

  • Transparent AI & Explainability Guidelines

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STANDARD OPERATING PROCEDURES​​

Build SOP Strategies:

  • Up-to-Date SOP Manual Review or Dev

  • Human Sign Off on Patterns/Process Risks

  • AI-Driven Transparency and Accountability Reporting 

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RESPONSIBLE AI: 

  • An Internal Authority Must be Assigned as the AI Standard Bearer

    1. Set an AI Quality Bar​

    2. AI Policy Framework Ownership

    3. Bridge Operational /AI Ethics Gaps

    4. Champion Governance Across All AI Driven Functional Areas

    5. Schedule Regular Measure, and Monitor  Audit Activities

  • Implement AI Impact Assessment Requirements 

  • Codify Core AI Development Standards

  • Establish Third-Party Data & Systems Remediation Accountability​​​​

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AI-RCM RELATED ISSUES

  • Patient Access/Registration 

  • Eligibility/Benefits Verification 

  • Prior Authorization Systems 

  • Clinical Documentation Integrity (CDI)

  • Computer-Assisted Coding (CAC) 

  • Charge Capture Systems 

  • Charge Description Master/CDM Logic

  • Denial Prediction Systems

  • Denial Management Systems

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MEASURE | MONITOR | MONETIZE

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