Automating data collection from medical journals to develop intelligent insights using NLP and RPA

Automating data collection from medical journals to develop intelligent insights using NLP and RPA Banner

Client Profile.

The client is a healthcare firm based out of Georgia, USA, providing precision intelligence services to life science companies. With deep disease and therapy expertise, the company uses custom market research and data analysis from published journals, editorial boards or presentations by physicians at conferences to solve critical medical questions for their customers.

Business Need.

The company extracts information related to researcher’s name, location, institutes or research organization, etc. from published papers and journals to provide strategic insights to life science companies by collating it in a structured format. In order to speed up the process of information gathering and dissemination with high accuracy, the company was looking to partner with a firm which could deliver:

  • Automated data collection for at least 2/3rd of webpages for specific journals on treatments related to oncology, hematology, urology, gynecology, etc.
  • Auto-routing of captured data to relevant categories in database while removing  repetitive entries.


The current processes of manual data collection from various research papers posed challenges such as:

HitechDigital’s Solution.

An automated workflow was designed to collect data from multiple sources and enter it into a predefined format. The process would include:

  • Collection of data from webpages and medical publications specified by the client using NLP algorithm developed by HitechDigital’s automation specialist
  • Deployment of RPA bots – embedded with NLP algorithm to enable formatting of data and collating it with existing database
  • Removal and merger of duplicate entries and addition of entries for new physicians to help client get an exhaustive set of information
  • An intuitive data summary dashboard to track performance
Data Collection Automated Workflow


Business Impact.

Reduced human intervention
Increased data accuracy
Savings on 6-7 FTEs
Optimized process efficiency
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