Capture Every Dollar You've Earned Through Accurate Clinical Coding
Revenue leakage from undercoding costs agencies millions annually. Our AI reviews documentation to identify missed opportunities—turning oversight into income.
Key Metrics
The Challenge
Patient-Driven Groupings Model (PDGM) reimbursement depends on accurate clinical coding. Many agencies experience significant revenue leakage due to undercoding, missed comorbidities, and incomplete documentation. This isn't just a coding problem—it's a business sustainability issue.
Pain Points We Eliminate
- Average $200-500 underpayment per episode due to coding gaps
- Clinical staff lack time to review every OASIS assessment
- Inconsistent coding practices across team members
- Revenue cycle delays from documentation corrections
How We Solve It
Our AI analyzes OASIS assessments and clinical documentation to identify clinical groupings that may be under-documented or missed entirely. It provides specific, actionable recommendations to capture appropriate reimbursement while maintaining full compliance.
Document Analysis
Deep analysis of OASIS responses and clinical notes for coding opportunities
Revenue Impact
Each recommendation includes estimated revenue impact for prioritization
Compliance First
All suggestions validated against CMS guidelines and medical necessity
Specific Guidance
Exact documentation elements needed to support each coding change
How It Works
From assessment to revenue capture in four simple steps
Submit Assessment
Send OASIS data and clinical documentation securely
AI Analysis
Model identifies clinical grouping opportunities and documentation gaps
Recommendations
Receive prioritized suggestions with specific documentation guidance
Capture Revenue
Clinical staff review and implement appropriate coding updates
Use Cases
Optimize revenue across your entire workflow
Pre-Submission Review
Analyze OASIS before RAP submission to maximize first-pass accuracy
Retrospective Analysis
Review historical cases to identify systematic coding opportunities
Quality Improvement
Training insights to improve documentation practices organization-wide
Frequently Asked Questions
PDGM Optimization AI — what care teams ask most
Is there an AI agent for PDGM optimization?
Yes. Care Intelligence Engine’s PDGM Optimization is an AI agent that analyzes OASIS assessments and clinical documentation to find missed comorbidities and under-documented clinical groupings, helping home health agencies capture appropriate reimbursement under the Patient-Driven Groupings Model.
What is PDGM Optimization AI?
It is an AI model that analyzes OASIS assessments and clinical documentation to find missed comorbidities and under-documented clinical groupings, so home health agencies capture the reimbursement they have earned under the Patient-Driven Groupings Model.
How much additional revenue can PDGM Optimization capture?
Agencies typically capture an average of $400+ in additional appropriate reimbursement per episode by correcting undercoding and missed comorbidities, while reducing LUPA occurrences by around 15%.
Is PDGM Optimization compliant with CMS rules?
Yes. Every recommendation is validated against CMS guidelines and medical necessity, so agencies capture appropriate revenue without adding compliance risk.
Does it work before claim submission?
Yes. It supports pre-submission review of OASIS data to maximize first-pass accuracy, as well as retrospective analysis of historical cases to find systematic coding opportunities.
Ready to Capture Lost Revenue?
See how PDGM Optimization can help your organization maximize reimbursement while maintaining compliance.