Epic Beaker and Epic Bugsy Will Improve Efficiency for NHRMC Laboratory, Promote Antibiotic Stewardship

September 08, 2020
lab pic stock

NHRMC is transitioning to the Epic Beaker laboratory information system, a change that will integrate processes and communication within the NHRMC lab, the healthcare system, and Epic. Beaker and Epic Bugsy will replace NHRMC’s hospital-based clinical laboratory, anatomic pathology, infection prevention and control information systems.

The new systems will foster efficiency, collaboration and accuracy. Users will see:

  • More automated processes
  • Increased efficiency
  • Improved turnaround time
  • Fewer opportunities for error
  • Positive patient identification

Training is underway via PowerPoint, CBL and video presentations for affected employees, and the change will be implemented during the next Epic update on September 12.

Transitioning to Beaker also gives NHRMC the ability to feed, visualize, share and mine data, providing increased transparency into the laboratory, and activating more tools for the end user.

Here’s a look at the software being replaced:


What’s Going?

What’s Coming?

Allscripts Lab (ALAB)

Epic Beaker CP (Clinical Lab)

Sunquest CoPath

Epic Beaker AP (Pathology)

Mobile Care Phlebotomy (MCP)






The transition supports NHRMC’s dedication to providing the best care possible to our patients and to give our staff the equipment and training to provide excellent care.

The implementation supports NHRMC’s ACO and Population Health initiatives, standardizes medication algorithms, and improves test utilization and blood management.

In the big picture, the investment in Epic Beaker illustrates NHRMC’s dedication to Access, Value and Health Equity.


  • Supports laboratory outreach efforts with community providers and other health care organizations


  • Integration with EMR
  • Quality improvements (tracking, patient identification)
  • Efficiency gains (consolidated reporting, images, filing)
  • Quarterly enhancements

Health Equity:

  • Analytics for clinical decision support
  • Identification of disparities, personalized medicine
  • Medication and test utilization algorithms