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Automated Data Extraction

Review and identification process of patient's medical charts are automated using optical character recognition

Challenges

  • A manual review of patient medical charts is a tedious process and is prone to errors.
  • The client needed to automate the manual coding process in order to have more consistent and accurate results

Solutions

  • The client needed to extract data from unstructured and nonstandard document formats including paper, fax and digital
  • Used Optical Character Recognition to extract data from the scanned medical charts and pulled 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 compared to the manual coding rate
  • Provided accuracy rates of 95-98% for identifying medical conditions
  • Reduced overall administration costs
  • Easy access to information expedites care for those in need (Patient & Doctor)