Transforming Government Document Management Through Digital Transformation in Healthcare

Overview

Redica Systems, a leader in regulatory intelligence and document processing, faced the challenge of unifying highly varied data to enable end-users to track and identify compliance issues. The company needed a cutting-edge data environment capable of handling large-scale, varied document ingestion, parsing, reconciliation, and classification, moving away from traditional manual methods to a more automated and scalable system.

Blue Orange Solution

Blue Orange developed a custom, high-throughput, fault-tolerant data lake to serve as the foundation for Redica Systems’ digital transformation. The solution entailed advanced automated ingestion jobs replacing manual data scrapers, integrating Natural Language Processing (NLP), Optical Character Recognition (OCR) tools like Tesseract and AWS textract for efficient, scalable complex document processing and workflow orchestration.

Full Story

Redica Systems’ journey to digital transformation in the healthcare sector was marked by the need to manage and process vast amounts of highly varied data from diverse public sources across the internet. The data ranged from structured feeds to semi-structured documents and unstructured images or scans. To address this, Blue Orange built a custom data ingestion and orchestration platform to serve as the robust backbone of their regulatory document intelligence product.

The challenges included 

• Ingesting data from various sources at varying frequencies
• Process different types of data, from JSON to text to low quality scans of documents
• Prevent expensive reprocessing of data
• Processing data quickly to alert customers downstream

Blue Orange’s approach leveraged OCR and NLP techniques to handle this diversity. The advanced data science methods were crucial for accurate document classification and efficient data parsing, ranging from simple string matching to more complex topic modeling and semantic natural language understanding techniques.

A flow diagram depicting the data ingestion, processing, and classification pipeline, showcasing the integration of OCR, NLP, and AWS technologies for a comprehensive view of the solution.

In addition, Blue Orange implemented an AWS event-based technology stack for workflow orchestration. This included using AWS Glue for data cataloging and S3 for storing processed data, ensuring that the system was not only powerful but also scalable. The automation of these processes was key to efficiently handling Redica Systems’ large and varied data volume.

Furthermore, Blue Orange played a pivotal role in upskilling Redica Systems’ existing data engineering team, equipping them with the knowledge and skills to leverage this modern AWS data architecture effectively.

Results

The transformation brought about by Blue Orange’s solution had a profound impact on Redica Systems’ operations:

• Automated solutions replaced manual processing, significantly reducing time and labor costs.
• Unstructured data was efficiently transformed into structured formats, making it more accessible and analyzable.
• The modern data lake approach streamlined document processing workflows, saving costs on storage and making information more readily available.
• The adoption of NLP and OCR technologies facilitated the conversion of text and image data into valuable analytical assets.
• Overall, the implementation led to improved accuracy, increased productivity, and substantial cost and time savings.

By leveraging Blue Orange’s expertise in AWS cloud infrastructure and advanced data processing techniques, Redica Systems significantly enhanced its operational efficiency, paving the way for scaling to additional strategic verticals and managing complex data more effectively.