SIMulation of Medication Error induced by Clinical Trial drug labeling: the SIMME-CT study

Int J Qual Health Care. 2016 Jun;28(3):311-5. doi: 10.1093/intqhc/mzw025. Epub 2016 Mar 13.

Abstract

Objective: To assess the impact of investigational drug labels on the risk of medication error in drug dispensing.

Design: A simulation-based learning program focusing on investigational drug dispensing was conducted.

Setting: The study was undertaken in an Investigational Drugs Dispensing Unit of a University Hospital of Lyon, France.

Participants: Sixty-three pharmacy workers (pharmacists, residents, technicians or students) were enrolled.

Intervention: Ten risk factors were selected concerning label information or the risk of confusion with another clinical trial. Each risk factor was scored independently out of 5: the higher the score, the greater the risk of error. From 400 labels analyzed, two groups were selected for the dispensing simulation: 27 labels with high risk (score ≥3) and 27 with low risk (score ≤2). Each question in the learning program was displayed as a simulated clinical trial prescription.

Main outcome measure: Medication error was defined as at least one erroneous answer (i.e. error in drug dispensing). For each question, response times were collected.

Results: High-risk investigational drug labels correlated with medication error and slower response time. Error rates were significantly 5.5-fold higher for high-risk series. Error frequency was not significantly affected by occupational category or experience in clinical trials.

Conclusions: SIMME-CT is the first simulation-based learning tool to focus on investigational drug labels as a risk factor for medication error. SIMME-CT was also used as a training tool for staff involved in clinical research, to develop medication error risk awareness and to validate competence in continuing medical education.

Keywords: investigational drugs; medication error; simulation.

MeSH terms

  • Computer Simulation
  • Drug Labeling / statistics & numerical data*
  • Drugs, Investigational / administration & dosage*
  • France
  • Hospitals, University
  • Humans
  • Medication Errors / statistics & numerical data*
  • Medication Systems, Hospital / organization & administration*
  • Medication Systems, Hospital / standards
  • Medication Systems, Hospital / statistics & numerical data*
  • Pharmacists / statistics & numerical data
  • Pharmacy Residencies / statistics & numerical data
  • Pharmacy Technicians / statistics & numerical data
  • Risk Factors
  • Students, Pharmacy / statistics & numerical data
  • Time Factors

Substances

  • Drugs, Investigational