title: Provider risk factors for medication administration error alerts: analyses of a large-scale closed-loop medication administration system using RFID and barcode.
abstract: To determine the risk factors and rate of medication administration error (MAE) alerts by analyzing large-scale medication administration data and related error logs automatically recorded in a closed-loop medication administration system using radio-frequency identification and barcodes.
  
  
  
  The subject hospital adopted a closed-loop medication administration system. All medication administrations in the general wards were automatically recorded in real-time using radio-frequency identification, barcodes, and hand-held point-of-care devices. MAE alert logs recorded during a full 1 year of 2012. We evaluated risk factors for MAE alerts including administration time, order type, medication route, the number of medication doses administered, and factors associated with nurse practices by logistic regression analysis.
  
  
  
  A total of 2 874 539 medication dose records from 30 232 patients (882.6 patient-years) were included in 2012. We identified 35 082 MAE alerts (1.22% of total medication doses). The MAE alerts were significantly related to administration at non-standard time [odds ratio (OR) 1.559, 95% confidence interval (CI) 1.515-1.604], emergency order (OR 1.527, 95%CI 1.464-1.594), and the number of medication doses administered (OR 0.993, 95%CI 0.992-0.993). Medication route, nurse's employment duration, and working schedule were also significantly related.
  
  
  
  The MAE alert rate was 1.22% over the 1-year observation period in the hospital examined in this study. The MAE alerts were significantly related to administration time, order type, medication route, the number of medication doses administered, nurse's employment duration, and working schedule. The real-time closed-loop medication administration system contributed to improving patient safety by preventing potential MAEs. Copyright © 2016 John Wiley & Sons, Ltd.
authors.affiliation: Department of Biomedical Informatics, Ajou University School of Medicine, Suwon, Korea.|Center for Medical Informatics, Seoul National University Bundang Hospital, Seongnam, Korea.
authors.forename: Yeonsoo
authors.initials: Y
authors.lastname: Hwang
authors.affiliation: Department of Biomedical Informatics, Ajou University School of Medicine, Suwon, Korea.
authors.forename: Dukyong
authors.initials: D
authors.lastname: Yoon
authors.affiliation: Department of Biomedical Informatics, Ajou University School of Medicine, Suwon, Korea.
authors.forename: Eun Kyoung
authors.initials: EK
authors.lastname: Ahn
authors.affiliation: Center for Medical Informatics, Seoul National University Bundang Hospital, Seongnam, Korea.
authors.forename: Hee
authors.initials: H
authors.lastname: Hwang
authors.affiliation: Department of Biomedical Informatics, Ajou University School of Medicine, Suwon, Korea.
authors.forename: Rae Woong
authors.initials: RW
authors.lastname: Park
mesh_terms: D001330:Electronic Data Processing; D006801:Humans; D016015:Logistic Models; D050316:Medical Order Entry Systems; D008508:Medication Errors / Q000517:prevention & control / Q000706:statistics & numerical data*; D008510:Medication Systems, Hospital; D009726:Nurses / Q000458:organization & administration; D004364:Pharmaceutical Preparations / Q000008:administration & dosage*; D019095:Point-of-Care Systems; D057233:Radio Frequency Identification Device; D012307:Risk Factors; D013997:Time Factors; D014940:Work Schedule Tolerance
chemical_list: D004364:Pharmaceutical Preparations
keywords: closed-loop medication administration; medication error; patient safety; pharmacoepidemiology; point-of-care system; radio-frequency identification (RFID)