2400 Meadowbrook Parkway, Duluth, GA 30096 | +1 770-493-5588 Follow Us
Select Page

Optical character recognition used to automate review and identification process of patient medical charts


Client Background

The client is a leading healthcare technology company based out of the US.


  • Manual review of patient medical charts was becoming too time and labor-intensive and was prone to errors. 
  • The client needed to automate the manual coding process in order to have more consistent and accurate results. 


  • The client needed to extract data from unstructured and nonstandard document formats including paper, fax and digital. We implemented optical character recognition technology for patient data extraction from the scanned medical charts which helped pull out relevant medical information. 
  • Integrated multiple data sources to automate the query process. 
  • Ran the extracted medical data through the NLP engine and captured the sentiment of a particular record.  

Tools & Technologies

Python, Open NLP, LeadTools

Key benefits

  • Improved productivity by 40%. 
  • Increased output rate using NLP as compared to the manual coding rate. 
  • Accuracy rates of 95-98% in identifying medical conditions. 
  • Reduced overall administration costs. 
  • Easy access to information leading to expedited care for those in need (patient & doctor).  
Key Benefits - Automated Data Extraction - Healthcare



    Digital Product Engineering

    Cloud Services

    Data & Analytics

    Intelligent Automation

    Cyber Security

    Build Operate Transfer

    Talent Solutions


    Banking & Financial Services

    Communication, Media
    and Technology

    Energy and Utilities


    Life Sciences



    Transportation and Logistics

    Travel & Hospitality

    Innovation @ Work

    Blogs and Insights

    Research and Whitepapers

    Case Studies


    About Us


    Strategic Partnerships

    Office Locations

    News and Events

    The Foundation


    Open Positions

    Life @ Innova Solutions
    Candidate Resource Library

    Let's Connect