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The Copy & Paste Problem in EHR Patient Documentation

Skyrocketing rates of physician burnout and provider frustration with the time required to enter records into the EHR have driven the widespread use of copy and paste when entering patient information into electronic health records.

Back in 2017, a study published by the Journal of the American Medical Association reviewed thousands of EHR records and found that only a small minority of them were manually entered – but more than 80 percent of the notes were imported or copied from elsewhere.

The team analyzed 23,630 inpatient progress notes written by 460 caregivers who were direct care hospitalists, residents and medical students.

Researchers found that 46 percent of notes were copied, 36 percent were imported, and just 18 percent of the text was entered manually.

Accuracy, security and patient safety are all put in peril when copying and pasting from one patient note into another. Additionally, inaccurate and incomplete records can result in delayed or denied reimbursements for the practice.

The ECRI Institute published its “Health IT Safe Practices: Toolkit for the Safe Use of Copy and Paste” guidelines in 2016 in an effort to educate the medical community about best practices for utilizing copy and paste in EHR documentation.

According to the 58-pages of the ECRI Institute’s guidelines, adopting safer copy-and-paste practices would require each practice to implement a series of cumbersome steps, including establishing new levels of staff training and oversight, flagging pasted material for easy identification, distinguishing between appropriate and inappropriate times to copy/paste, and more.

It’s clear that putting the new processes into action could undermine any speed improvements derived from copying and pasting.

Fortunately, there is a better way to enter patient notes.

NoteSwift (founded by a practicing physician) has developed an A.I.-driven EHR Transcriptionist – Samantha – that simplifies patient note entry and eliminates the need to copy data.

Samantha takes the physician’s narrative input (either typed manually, or from any medical speech recognition tool) and intelligently parses the information to identify structured data elements, assign required codes, and present the complete patient note to the user for verification. Samantha then enters the entire patient note into the correct menus, fields, and check-boxes of the EHR automatically, saving time, virtually eliminating clicks, and ultimately helping to reduce physician burnout.

With Samantha, the increased speed encompasses all aspects of the patient note, including entering narrative text and structured data, navigating from screen to screen, looking up complaints, and completing and sending prescriptions and lab orders.

Want to see Samantha in action? Contact us to schedule a live demonstration for your practice.