Healthcare

Thirdwave RX

Automated medical claims processing and reimbursement optimization for pharmaceutical data operations

83%

Of raw claims automatically converted into a unified, rebate-eligible format

17%

Of raw claims automatically flagged for human review

3x

Productivity uplift across internal ops

Case Studies

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

Challenge

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.

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Outcomes We Deliver

Solution

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.

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Dalriada
Tech Stack

To developed an AI-powered NDC to HCPCS conversion platform, Blackthorn AI applied:

Python
Pandas
Docker
GitHub Actions
PostgreSQL
Azure
Tenzor
Roadmap

Project duration

01 Week

Discovery & Requirements Analysis

Defined project scope, reviewed legacy rule-based logic, gathered edge cases and anomalies from historical NDC-HCPCS mappings.

02 Week

Data Exploration & Preprocessing

Audited raw input datasets (TXT, CSV, XLSX), cleaned data, handled missing fields, standardized units and dosages.

03 Week

Format Normalization Engine

Developed automated parsers to identify and unify various NDC and HCPCS billing formats, enabling consistency in further model processing.

04 Week

Feature Engineering

Designed relevant features across drug strength, units, manufacturer codes; ranked feature importance for model interpretability.

05 Week

Model Training & Benchmarking

Trained and compared decision trees, random forests, and neural networks. Selected optimal architecture based on accuracy and speed.

06 Week

Validation & Feedback Loop

Built internal feedback collection interface for reviewers, integrated field-level validation and metrics logging.

07 Week

Web Integration & Reversal Detection Engine

Implemented historical analysis to flag and suggest corrections for duplicate or reversed claims entries.

08-12 Weeks

Final Optimization & Documentation

Performed end-to-end tests, cleaned codebase, wrote deployment and usage docs, and transferred project knowledge to internal teams.

Team Size

4 core specialists
1 x Technical Leader
1 x Data Scientist
1 x Data Engineer

Delivering Impact

17%

Of raw claims

Automatically flagged for human review

100%+

Accuracy

In NDC-to-HCPCS mapping

83%

Of raw claims

Automatically converted into a unified, rebate-eligible format

80%

Fewer errors

In claims conversion workflows

Faster

Integration of new NDC formats and drug types

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