Case Studies
Transforming Healthcare Text into Structured Data
Estimated reading time: 2 minutes
Customer: Medical record management company
Challenge: Manual extraction of text data from source documents to software
Solution: Intelligent document processing
Challenge:
An Overly-Manual Extraction Process
Extracting information from scanned documents slows collaboration between healthcare providers, patients, and organizations like insurers. The customer’s software makes this easier, but heavy manual transcription is required to get the important text data out of source documents and into the software.
Solution:
Turning Text into Structured Data
Infinia IDP transforms all healthcare text data into a structured data model. Machine learning performs named entity recognition and classification for both machine readable and image-based text to automatically extract relevant information.
Value:
A Better Way to Extract Information
Machines are now able to process extraction tasks with high degrees of accuracy, leaving outliers for trained human reviewers.
Applying these techniques elsewhere
Infinia IDP can help streamline document processes across a variety of industries.
Related Case Studies
Streamlining Prescription Data Extraction Through Intelligent Document Processing
Infinia ML developed a solution to yield savings of $1.6M over three years with the power of automation.
How Infinia ML gave a healthcare disruptor the power to scale
Infinia ML developed machine learning models to extract text data from non-standardized documents.
Preventing Overpayments on Medical Claims
Infinia ML identified patterns related to patients that required coordination of benefits.
