

Our
Approach
​AI in Revenue Cycle Management, quality, and compliance solutions that you can trust!
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We aim to minimize errors while working simultaneously to enhance quality and regulatory compliance.
We are proud to be certified by the Women's Business Enterprise National Council (WBENC).
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​We have ISO 9001-certified Internal Auditors who utilize Proprietary Protocols to advance end-to-end AI in RCM, leading practice quality and compliance solutions.
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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 Risks and Inconsistencies
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Automate Customized Quality/Compliance Solutions
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Design AI-powered Compliance Dashboards
AI TASK PRIORITIZATION
& WORKFLOWS
PRE AI ADOPTION
Manual task queues, static worklists, inconsistent prioritization
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NOW & FUTURE STATE: ​
​​​​Predictive Worklists:
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AI flags and sorts claims, coding tasks by likelihood of risk, or compliance exposure.
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Autonomous Task Routing:
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AI assigns tasks to staff based on complexity, productivity, and domain expertise.
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Dynamic SLA Monitoring:
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AI reorders task priorities based on payer deadlines, authorization risk, or expected revenue.
CHARGE CAPTURE & CODING WORKFLOWS
PRE AI ADOPTION
Coders review, analyze, and manually assign CPT/ICD codes from chart notes
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NOW & FUTURE STATE:
AI-Powered Computer-Assisted Coding (CAC):
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Suggests optimal codes with confidence and flags inconsistencies for coder review.
Coding Error Prevention:
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AI detects and flags Pre-bill edits, medical codes, E/M levels, and modifier outliers.
CDI Optimization:
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​AI identifies documentation gaps for CPT, ICD, and DRG optimization, ensuring the integrity of quality and compliance.
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PERFORMANCE MONITORING & ​QUALITY CONTROL​
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PRE AI ADOPTION
Static KPIs, Excel dashboards, retrospective audits
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NOW & FUTURE STATE:
Real-Time AI Dashboards:
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AI detects trends in reimbursement changes, denials, or workflow bottlenecks.
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Exception-Based QA:
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AI flags high-risk anomalous outpatient visits or inpatient stays for human review, which helps to reduce audit fatigue.
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Algorithmic Integrity Checks:
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AI tracks itself—continuously monitoring algorithm performance issues, AI/Data errors, and various types of bias.
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