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Automated Claims Processing & Reimbursement
Automated medical claims processing and reimbursement optimization for pharmaceutical data operations
Reduction in time spent on manual NDC–HCPCS code conversion
Fewer errors in claims conversion workflows
Productivity uplift across internal ops
AI-powered NDC to HCPCS conversion platform for faster, smarter rebate submission.
Healthcare
Industry
USA
Location
AI/ML Engineering, MLOps & Model Deployment, Cloud Infrastructure
Services
$30,000 – $50,000
Budget
The healthcare data analytics company, faced high operational overhead due to manual conversion of NDC (National Drug Codes) to HCPCS (Healthcare Common Procedure Coding System) codes for rebate processing.
See what we can do for youSolution
We delivered a custom machine learning–powered engine that converts NDCs to HCPCS codes with high accuracy, detects billing anomalies, and ensures clean, deduplicated claims through built-in validation and reversal logic.
Let’s talk about what’s possible
To developed an AI-powered NDC to HCPCS conversion platform, Blackthorn AI applied:
Project duration
01 Week
Defined project scope, reviewed legacy rule-based logic, gathered edge cases and anomalies from historical NDC-HCPCS mappings.
02 Week
Audited raw input datasets (TXT, CSV, XLSX), cleaned data, handled missing fields, standardized units and dosages.
03 Week
Developed automated parsers to identify and unify various NDC and HCPCS billing formats, enabling consistency in further model processing.
04 Week
Designed relevant features across drug strength, units, manufacturer codes; ranked feature importance for model interpretability.
05 Week
Trained and compared decision trees, random forests, and neural networks. Selected optimal architecture based on accuracy and speed.
06 Week
Built internal feedback collection interface for reviewers, integrated field-level validation and metrics logging.
07 Week
Implemented historical analysis to flag and suggest corrections for duplicate or reversed claims entries.
08-12 Weeks
Performed end-to-end tests, cleaned codebase, wrote deployment and usage docs, and transferred project knowledge to internal teams.
Team Size
Delivering Impact
10×
ReductionIn time spent on manual NDC–HCPCS code conversion
3x
ProductivityUplift across internal op
100%+
AccuracyIn NDC-to-HCPCS mapping
80%
Fewer errorsIn claims conversion workflows
2×
FasterIntegration of new NDC formats and drug types
