OUR
APPROACH
P3 Quality is a Virtual Solutions Center. We are Certified AI Professionals and Data Quality Experts who partner with our clients to deliver Quality First/Quality Forward Solutions.
P3 inspect, detect and correct data and process errors, inconsistencies and inaccuracies. Our solutions enhance quality, integrity and productivity!
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Quality Control Approaches:
​AI in RCM Analysis
Algorithms and Rules Quality Review
Regulatory Quality and Governance Toolkit
Inspecting, Detecting & Assessing Inconsistencies
Leveraging Data Analytics and Reporting
Establishing a Continuous Quality Improvement Program
Determining Performance Metrics
Additional Service Offerings
Assess Outsourced Vendor Performance
Evaluated Service Level Agreements (SLA)
SLA Metrics Review
OUR
METHODOLOGY
P3 Quality helps clients to address and resolve coding quality inconsistencies. P3 uses an end-to-end measure, monitor and monetize AI risks methodology.
We leverage quality control measures to help evaluate payer and provider best practices; to ensure AI coding, regulatory requirements and standards are followed and achieves optimal reimbursement results.
Quality Control Methods:
​Measure:
Prior Authorizations, Eligibility Verification, and daily patient data reviews.
​Monitor:
Real-Time Clinical Documentation Integrity (CDI), AI in Medical Coding (i.e., ICD-10, CPT & HCPCS) data integrity/charge integrity and reconciliation auditing.
​Monetize:
Claims Management, and Denials Management mitigation and remediation.
AI in REVENUE CYCLE MANAGEMENT (RCM)
What is AI in RCM exactly?
P3 Quality Eyes are on AI!​​​ AI in revenue cycle management (RCM) is a transformative force that harnesses advanced technologies like machine learning, natural language processing (NLP), and robotic process automation (RPA) to revolutionize and enhance the RCM Administrative and Claims management process.
​​AI in MEDICAL CODING
What about AI in Medical Coding?
​AI in medical coding refers to the use of machine learning algorithms, natural language processing (NLP), and automation tools that are used to analyze clinical documentation, extract relevant information, and assign accurate codes for billing purposes.
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Are you seeing a 95 to 97% accuracy rate when using AI Medical Coding software? If not, how are you identifying, addressing and correcting errors and inconsistencies?