[Medication errors related to computerized physician order entry at the hospital: Record and analysis over a period of 4 years]

Ann Pharm Fr. 2016 Jan;74(1):61-70. doi: 10.1016/j.pharma.2015.06.001. Epub 2015 Aug 15.
[Article in French]

Abstract

Objectives: Computerized physician order entry (CPOE) can generate medication errors. It is necessary to identify them and analyse their causes in order to secure the medication use system.

Methods: Errors were recorded during the pharmaceutical analysis of prescriptions over a period of 4 years on 425 beds. A code frame was provided. Errors were classified according to type, causes and time of detection. The most often drug implicated and the error correction rate were studied. Deep causes were determined and contributing factors were listed.

Results: Among 99,536 prescriptions analyzed, 2636 errors were detected (2.65 errors per 100 orders analyzed). The most common error was omission (31.49%). The most represented cause was redundancy requirement (11.34%). Antibacterials were most commonly involved (224 errors). Exactly 65.9% of the prescriptions were modified by physicians. Three root causes were identified: (1) configuration issues; (2) misuse; (3) design problem. Three types of contributing factors have also been detailed: economic, human and technical factors.

Conclusions: Identifying root causes has targeted three types of improvement actions: (1) software settings; (2) training of users; (3) requests for improvements. Contributing factors have to be identified to control the generated risk. Some errors related to CPOE may lead to serious side effects for the patient. That is why it is necessary to identify these errors and analyze them in order to implement improvement actions and prevention to secure the prescription.

Keywords: Analyse pharmaceutique; Computerization; Computerized physician order entry; Erreur médicamenteuse; Informatisation; Medication error; Pharmaceutical analysis; Prescription; Sécurisation.

MeSH terms

  • Drug Prescriptions / statistics & numerical data
  • Drug-Related Side Effects and Adverse Reactions
  • France / epidemiology
  • Hospitals / statistics & numerical data
  • Humans
  • Medical Order Entry Systems*
  • Medical Records Systems, Computerized
  • Medication Errors / prevention & control
  • Medication Errors / statistics & numerical data*