Joanna Kasprzak
Chief Operating Officer
Joanna Kasprzak, Ph.D. in Bioinformatics, has led over 30 of Apzumi's successful Digital Health applications. She is always happy to share both medical and technical insights and advice for your project
Generative AI in medical documentation processing
The project was designed to transform the health claim processing workflow from a labor-intensive task into an automated, efficient system. The system digitizes documents, categorizes them, extracts key facts, and generates medical summaries and reports.
Category:Health & WellbeingInsurance
Overview
Project at a glance
Client:
ICR Sp. z o.o.
Industry:
Insurance
Market:
Poland
Engagement:
PoC
Scope:
Generative AI workflow
Team size:
2 Developers, QA, PM
Duration:
2 months
Partnership:
6 years (ongoing)
About the Problem
The business challenge
In the healthcare sector, the dispatch of health claims involves processing an extensive array of documents, including medical reports, examination results, lab tests, medical procedures, and billing information. Traditionally, this process has been manual, time-consuming, and prone to errors, leading to delays in claims processing and increased operational costs.
The project aimed to:
- leverage Generative AI and Optical Character Recognition (OCR) technologies
- automate the health claim dispatch process
- enhance efficiency, accuracy, and patient satisfaction.
Our Solution
What we delivered
Medatex is a leading insurance claim management solution used by over 50 insurance companies in Europe. The process involves handling claims based on legal, medical, and insurance standards, providing adjusters with analytical solutions for assessing the situation of the injured parties and the extent of their damages and enabling the automatic generation of documents, including templates for correspondence with the injured party or their representative, as well as decision templates. The goal of this pilot project was to automate the health claim dispatch process to assess potential gains in process efficiency and time savings.
The business objective: The pilot project's goal was to automate the health claim dispatch process to assess potential gains in process efficiency and time savings.
Key Features
Features under the hood
OCR implementation
Generative AI
API workflow
GDPR/HIPAA compliance
Timeline
How it all came together
2 weeks
Ideation
During the initial phase, we performed a business analysis and established a clear problem definition, including success criteria for the customer. Our analysts documented the current business process of claim management, highlighting the predominance of manual tasks. We detailed each step of the process, specifying the input and output, and also created a set of test data.
2,5 month
Proof of Concept
In this phase, we deployed various prototype solutions to assess top generative AI engines, aiming to choose the one that aligns with both customer needs and process requirements. We developed precise automated test cases to investigate the limits of accuracy and efficiency. We also established an automated system for processing documents and extracting facts. A thorough analysis of the outcomes was conducted alongside detailed statistical evaluations.
upcoming
MVP Development
The objective of the upcoming phase is to implement the solution on a small scale with actual cases, while also focusing on refining the model and improving cost efficiency. All data will continue to be reviewed through a human-assisted process.
Technical Overview
The engineering behind the project
The technological backbone of this project was a strategic combination of OpenAI and NVidia AI tools, chosen for their efficiency and cost-effectiveness. To digitize the documents, we employed a suite of OCR technologies, with Tesseract playing a pivotal role due to its versatility and wide adoption. Recognizing the diverse linguistic nuances present in medical documents, we also developed and deployed custom models specifically tailored to address language-specific challenges. This approach ensured not only the high fidelity of digitized text but also the nuanced understanding necessary for accurate categorization and information extraction in subsequent stages.
Projecttech stack
OpenAI
Artificial Intelligence API
Nvidia
Artificial Intelligence API
JavaScript
Frontend Development
Java
Backend Development
Python
Backend Development
Tesseract
OCR Integration
Projecttool stack
Jira
Project Management
Confluence
Documentation
Slack
Communication
Gallery
A visual deep dive
Contact
Reach out to our experts
Whatever stage you're at - an idea, a product that needs scaling, or a system that's stopped keeping up - start with a conversation. No pitch deck required, and no obligation on your side.
Sebastian Zarzycki
Chief Technology Officer
Sebastian Zarzycki, MSCS in Software Engineering, has over 18 years of experience in designing, architecting, implementing and overseeing software. He's involved in all key Apzumi projects.
