Parascript: How to Solve Extensive Data Processes and Streamline Information Flow

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While we have made huge steps in transferring information into processes of data analysis, there is still a huge reliance upon hard-to-process document-based information. One of the biggest culprits of this is the healthcare industry. For decades, they have been using this outdated, insecure method of managing patients' private information, which has led to multiple issues, such as data breaches. The restraints of paper-based forms and documents are further highlighted by the problems that arise throughout workflows: misplaced document-based information; slow delivery times as information has to be passed through multiple different parties. 

Simplifying Processes of Data Analysis

On this podcast, Greg Council, VP Marketing and Product Management at Parascript, joins us to discuss the processes of document-based information and why current systems are so outdated. He also outlines how we can best move to a more automated form of operating and what it means to view document processing from an insurance perspective. Listen and learn about:

  • Fundamentals of the healthcare and health insurance market 
  • Key challenges around claims-to-payment, also known as revenue cycle management, and the inclusion of documents in the workflow process
  • The impact of numerous parties being involved in a manual automation process
  • The role of NLP in converting complex document-based information into structured data
  • Auto-adjudication and its importance within an automated workflow
  • The implications of non-structured electronic data interchange (EDI) in terms of cost, time, and process
  • Practical advice on where to start with document automation    

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