Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2012 Apr;38(4):178-83.
doi: 10.1016/s1553-7250(12)38023-9.

Detecting unapproved abbreviations in the electronic medical record

Affiliations

Detecting unapproved abbreviations in the electronic medical record

Andrew Capraro et al. Jt Comm J Qual Patient Saf. 2012 Apr.

Abstract

Background: At an emergency department (ED) in a tertiary care children's hospital with a level 1 pediatric trauma designation, unapproved abbreviations (UAAs) within electronic medical records (EMRs) were identified, and feedback was provided to providers regarding their types and use rates.

Methods: Existing EMRs, including the ED physicians' patient notes were used as templates to develop a UAA list and an abbreviation detector. The detector was validated against human-screened samples of electronic ED notes from 2003 and then applied to all existing data to generate baseline rates of UAA, before intervention/implementation. Next, the validated abbreviation detector was applied prospectively in screening all EMRs monthly during a six-month period.

Results: In validation, the abbreviation detector had a sensitivity of 89%, a specificity of 99.9%, and a positive predictive value of 89%. Some 475,613 EMRs were screened, with UAAs identified at a rate of 26.4 +/- 4 per 1,000 EMRs. The most common nonmedication UAA was "qd" [11.8/1,000 EMRs], and the most common medication UAA was "PCN" [4.2/1,000 EMRs]. A total of 27,282 patient notes from 74 physicians were screened between January 1, 2007, and June 30, 2007, and 392 monthly reports were generated. Aggregate UAA use decreased by 8% (95% confidence interval [CI]: 6%-14%) per month-from 19.3 to > 12.1/100 charts, for a 37.3% decrease in UAA use in the six-month period. The estimated monthly decrease per physician was 0.9/100 (95% CI: 0.86-0.94, p < .001.) After adjusting for secular trends, the decrease was 29% in the six-month study period (95% CI: 14%-44%, p < .0001).

Conclusions: Use of the abbreviation detector for surveillance of newly created EMRs, followed by consistent education and feedback, led to a significant decrease in UAA use in the study period.

PubMed Disclaimer

MeSH terms

LinkOut - more resources