How to Combat EMR Copy and Paste Errors

An article recently published in Perspectives in Health Information Management cites both the prevalence and risk of copied or carried-forward information in electronic medical records.

Studies have shown the majority of physicians copy and paste text within EMRs to save time:

  • A 2013 study showed notes entered by 82 percent of residents and 74 percent of attending physicians contain at least 20 percent copied text.[1]
  • A 2010 study found 78 percent of sign-out notes and 54 percent of progress notes contained copied text.[2]
  • A 2008 survey found 90 percent of physicians used the copy/paste functionality in daily electronic progress notes, and 71 percent felt inconsistencies and outdated information were more common in copied and pasted notes.[3]

Copying and pasting patient information within EMRs can have serious clinical consequences. Outdated, inaccurate or false information can be propagated, the notes' authorship can become obscured and the notes can become unnecessarily long, making the relevant information harder to find, all of which can compromise patient safety.

To combat the issue, hospitals should consider taking the following steps:

  • Define EMR content standards.
  • Promote proper clinical documentation practices and adopt a zero-tolerance policy for unethical documentation practices.
  • Create a data entry workflow that does not require clinicians to enter the same information multiple places, removing the temptation to cut and paste.
  • Require source attribution for all copied text.

More Articles on EMRs:

How Massachusetts General Successfully Incentivizes Physicians to Use EMRs
Do EMRs Turn Doctor Visits Into Impersonal Interactions?
EHR Company athenahealth Tracks Disease in Lieu of CDC Services



1Thornton, J. Daryl, et al. “Prevalence of Copied Information by Attendings and Residents in Critical Care Progress Notes.”Critical Care Medicine41 (2013): 4.

Wrenn, Jesse O., et al. “Quantifying Clinical Narrative Redundancy in an Electronic Health Record.”Journal of the American Medical Informatics Association17, no. 1 (2010): 50.

Wrenn, Jesse O., et al. “Quantifying Clinical Narrative Redundancy in an Electronic Health Record.”Journal of the American Medical Informatics Association17, no. 1 (2010): 50.

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