Penn Medicine


Reducing Epic Data Entry Time


Many physicians at Penn Medicine describe their work as 80% clerical and 20% clinical.

Inefficient Electronic Health Record (EHR) data entry processes detract from patient care, waste precious clinical time and resources, and prevent clinicians from operating at the top of their license.

Through a series of pilots, we’re testing interventions to reduce the time providers spend on Epic data entry.  


Our first pilot focused on improving progress note preparation for new patient visits at the Abramson Cancer Center at the Perelman Center for Advanced Medicine.

When a new patient is referred to Penn Medicine, their outside records are sent, typically via fax, to Penn Medicine where clinicians review them and record the relevant information in Epic.  

The current state (depicted below) requires that staff members manually enter information - often word-for-word - from outside records into Epic.   This process takes anywhere from 30 minutes to 1 hour and 15 minutes per new patient.

We set up a fake back-end to test our assumption that converting outside records into editable text would reduce physician data entry time for new patients.   

Over a 3-week period, members of our team manually converted faxed records into editable text for staff members at an oncology clinic in the Abramson Cancer Center.


Our intervention reduced data entry time for new patient progress notes from a span of 30 minutes to 1 hour and 15 minutes per patient to a span of only 10 to 40 minutes.

Staff involved with the pilot reported significant time savings, increased legibility of records, and increased satisfaction with the process.

 “This is a giant step forward. My team and I have seen a significant reduction in time spent on patient notes during this pilot. If it continues to progress, I can see this increasing patient throughput.”  Lynn Schuchter, Division Chief for Hematology Oncology

Building on the success of this work, we implemented eFax and text recognition technology to make the process more efficient while retaining the benefits of editable text.  We are currently working to fully operationalize the new process and experiment with increasing new patient throughput.  



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