Reducing prescribing errors through creatinine clearance alert redesign

Am J Med. 2015 Oct;128(10):1117-25. doi: 10.1016/j.amjmed.2015.05.033. Epub 2015 Jun 16.


Background: Literature has shown that computerized creatinine clearance alerts reduce errors during prescribing, and applying human factors principles may further reduce errors. Our objective was to apply human factors principles to creatinine clearance alert design and assess whether the redesigned alerts increase usability and reduce prescribing errors compared with the original alerts.

Methods: Twenty Veterans Affairs (VA) outpatient providers (14 physicians, 2 nurse practitioners, and 4 clinical pharmacists) completed 2 usability sessions in a counterbalanced study to evaluate original and redesigned alerts. Each session consisted of fictional patient scenarios with 3 medications that warranted prescribing changes because of renal impairment, each associated with creatinine clearance alerts. Quantitative and qualitative data were collected to assess alert usability and the occurrence of prescribing errors.

Results: There were 43% fewer prescribing errors with the redesigned alerts compared with the original alerts (P = .001). Compared with the original alerts, redesigned alerts significantly reduced prescribing errors for allopurinol and ibuprofen (85% vs 40% and 65% vs 25%, P = .012 and P = .008, respectively), but not for spironolactone (85% vs 65%). Nine providers (45%) voiced confusion about why the alert was appearing when they encountered the original alert design. When laboratory links were presented on the redesigned alert, laboratory information was accessed 3.5 times more frequently.

Conclusions: Although prescribing errors were high with both alert designs, the redesigned alerts significantly improved prescribing outcomes. This investigation provides some of the first evidence on how alerts may be designed to support safer prescribing for patients with renal impairment.

Keywords: Electronic health records; Evaluation; Health information technology; Patient safety; Renal disease.

Publication types

  • Evaluation Study
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Adult
  • Attitude of Health Personnel
  • Biomarkers / metabolism
  • Creatinine / metabolism*
  • Decision Support Systems, Clinical*
  • Ergonomics
  • Female
  • Humans
  • Male
  • Medical Order Entry Systems*
  • Medication Errors / prevention & control*
  • Medication Errors / statistics & numerical data
  • Middle Aged
  • Patient Safety
  • Reminder Systems*
  • Renal Insufficiency / diagnosis*
  • Renal Insufficiency / metabolism


  • Biomarkers
  • Creatinine