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Case Study

Banner Health Migrates Millions of Electronic Medical Records with Blue Prism

72 million Records handled in just two years
1.2 million Hours back to the business
43 Digital workers operating across 20 departments

Banner Health Migrate Electronic Medical Records (EMR) with Intelligent Automation and RPA

Banner Health serves over one million members through its network of 30 hospitals across Western US, making it one of the largest not-for-profit healthcare networks in America. Banner needed to migrate all its patient records from disparate systems into its document repository application. The task was virtually impossible to be performed manually by employees. So, Banner tasked their Blue Prism digital workforce to rapidly get the job done.


To boost operational efficiencies across Banner’s network, and to ensure patient record accuracy and consistency, the healthcare provider realized it needed to consolidate all medical records. Patient’s Electronic Medical Records (EMRs) from 30 separate legacy systems needed to be transferred into one document repository database. To manually migrate this data, one patient at a time, from 30 separate systems, was virtually impossible for human staff to do.


Since transferring all the patient EMRs was impractical for human workers, Banner turned to Blue Prism intelligent automation and deployed a digital worker called LEMR (consisting of 5 EMR bots). To migrate the records, LEMR retrieves each patient’s information, generates a patient chart, and then archives the required data to ensure continuous patient care across the network. Since deployment in December 2019, LEMR has handled over 72 million patient records, saving Banner over 1.2 million employee hours. That’s time that employees can spend providing superior patient services and care. What’s more, digital workers like LEMR have proven so effective that Banner now has deployed healthcare automation in 20 separate departments, including accounting, legacy EMR, imaging, clinical informatics support, and cardiology.

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