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Automated Medical Coding Pipeline

Manual medical coding runs a 10–20% error rate and bleeds $1B+ annually from non-compliant claims, in a market projected to reach $8.4B by 2033.

Under 7.66% error rate · 3× off the shelf AI baseline · shipped in 2 months
HOW THE SYSTEM WORKS
IN
Clinical note
unstructured patient documentation
DATA
CMS retrieval layer
3 official government sources
ICD-10-CM index
CMS guidelines
Payer references
STEP
Stage 1: Retrieve
70,000 codes → a shortlist of candidates
STEP
Stage 2: Classify
candidates → the one right code
CHECK
Compliance check
Medicaid & Medicare payer rules
OUT
ICD-10 code
7.66% error rate vs 10–20% industry
Every prediction is grounded in official government sources before it is checked for payer compliance.
Built
Two-stage retrieval pipeline grounded in three official CMS sources, with Medicaid and Medicare compliance rules built into the foundation of the system.
Approach
Step 1: find candidate codes from authoritative sources. Step 2: pick the right code under strict rules. Step 3: check compliance. Replaced a default large-language-model approach that capped below 70% accuracy.
Impact
Under 7.66% error rate · 3× off the shelf AI baseline · shipped in 2 months
Skills
PythonRAGVector DBLLMsICD-10CPTCMS Sources