AI Clinical Documentation Validation Agent
Automating Clinical Documentation Validation with AI
Prioritize high-risk cases before they become denials
The agent ingests encounter data from the EHR and applies clinical rules to identify denial-prone diagnoses like sepsis, acute respiratory failure, and malnutrition—scoring each case for validation risk and financial impact so CDI teams focus where it matters most.
Extract evidence and generate compliant queries
AI maps clinical indicators to organization-approved criteria (KDIGO for AKI, Berlin for ARDS, ASPEN/GLIM for malnutrition) and drafts non-leading provider queries that follow AHIMA/ACDIS standards—citing specific findings, their location in the record, and all clinically plausible options including “unable to determine.”
Draft defensible appeals with embedded citations
When denials occur, the system reconstructs the clinical storyline, references official coding guidelines and facility-approved criteria, and generates appeal letters that enumerate relevant indicators with timestamps and documentation sources—ready for physician advisor review.
How Cassidy automates this using AI
Step 1: Trigger on case submission or discharge
The Workflow activates when a new encounter is flagged for CDI review or when a patient is discharged—pulling H&P notes, progress notes, labs, vitals, imaging, and medication records from the EHR.
Step 2: Score and prioritize for validation risk
Cassidy analyzes the encounter against high-risk diagnosis patterns (sepsis, AKI, malnutrition, respiratory failure) and calculates potential DRG shift, SOI/ROM impact, and PSI/HAC exposure to surface the cases most likely to result in denials.
Step 3: Extract clinical indicators and map to criteria
The Knowledge Base contains your organization-approved clinical criteria sets. Cassidy extracts relevant indicators—SOFA elements, creatinine trends, weight loss percentages, ABG values—and maps them to the appropriate criteria with timestamps and source documentation.
Step 4: Generate compliant provider queries
Cassidy drafts non-leading queries that cite clinical indicators and their exact location in the record, present all reasonable diagnostic options, and include an “unable to determine” choice—following AHIMA/ACDIS compliant query practices.
Step 5: Visualize coding impact and flag gaps
Before claim submission, Cassidy shows expected MS-DRG assignment, MCC/CC capture, and HCC/RAF impact based on current documentation versus clarified documentation—highlighting missing linkage, unspecified acuity, or NCD/LCD compliance gaps.
Step 6: Draft denial appeals with evidence citations
When a denial is received, Cassidy reconstructs the clinical narrative, references coding guidelines and payer-specific criteria (addressing conflicts like Sepsis-2 vs. Sepsis-3), and generates an appeal letter with embedded citations and contract language for physician advisor review.
Step 7: Route for Human-in-the-Loop approval
All queries and appeals pass through CDI specialists or physician advisors before reaching providers or payers—maintaining a complete audit trail of prompts, responses, and cited evidence for compliance and continuous improvement.
Implement it inside your company
- Hands-on onboarding and support
- Self-paced training for your team
- Dedicated implementation experts
- Ongoing use case discovery
- ROI tracking & analytics dashboards
- Proven playbooks to get started fast
