Computerized physician order entry in the cardiac intensive care unit: effects on prescription errors and workflow conditions

J Crit Care. 2014 Apr;29(2):188-93. doi: 10.1016/j.jcrc.2013.10.016. Epub 2013 Oct 29.

Abstract

Purposes: To evaluate the effects of a computerized physician order entry (CPOE) system in the cardiac intensive care unit by detecting prescription errors (PEs) and also to assess the impact on working conditions.

Methods: A longitudinal, prospective, before-after study was conducted during the periods before and after the implementation of the CPOE system. Clinical pharmacists were responsible for the registration, description and classification of PEs, and their causes and severity, according to an international taxonomy. Professionals were also surveyed for their opinion, concerns, and level of satisfaction.

Results: A total of 470 treatment orders containing 5729 prescriptions were evaluated. The CPOE resulted in a marked reduction in the number of PEs: error rate was 44.8% (819 errors among 1829 prescriptions) with handwritten orders and 0.8% (16 among 2094 prescriptions) at the final electronic phase (P < .001). Lapses were the main cause of error in both prescription methods. Most errors did not reach the patients. Errors related with the computerized system were scarce. Most users were satisfied with many aspects of this technology, although a higher workload was reported.

Conclusions: Computerized physician order entry in the cardiac intensive care unit proved to be a safe and effective strategy in reducing PEs and was globally well received by professionals.

Keywords: CPOE; Cardiac ICU; Clinical decision support systems; Prescription errors; Workflow.

Publication types

  • Comparative Study
  • Evaluation Study

MeSH terms

  • Controlled Before-After Studies
  • Drug Prescriptions / statistics & numerical data*
  • Humans
  • Intensive Care Units*
  • Medical Order Entry Systems / statistics & numerical data*
  • Medication Errors / prevention & control
  • Medication Errors / statistics & numerical data*
  • Prospective Studies
  • Spain
  • Workflow*