Medication administration errors in nursing homes using an automated medication dispensing system

Patricia M L A van den Bemt*, Jetske C Idzinga, Hans Robertz, Dennis Groot Kormelink, Neske Pels

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

48 Citations (Scopus)

Abstract

OBJECTIVE To identify the frequency of medication administration errors as well as their potential risk factors in nursing homes using a distribution robot. DESIGN The study was a prospective, observational study conducted within three nursing homes in the Netherlands caring for 180 individuals. MEASUREMENTS Medication errors were measured using the disguised observation technique. Types of medication errors were described. The correlation between several potential risk factors and the occurrence of medication errors was studied to identify potential causes for the errors. RESULTS In total 2,025 medication administrations to 127 clients were observed. In these administrations 428 errors were observed (21.2%). The most frequently occurring types of errors were use of wrong administration techniques (especially incorrect crushing of medication and not supervising the intake of medication) and wrong time errors (administering the medication at least 1 h early or late).The potential risk factors female gender (odds ratio (OR) 1.39; 95% confidence interval (CI) 1.05-1.83), ATC medication class antibiotics (OR 11.11; 95% CI 2.66-46.50), medication crushed (OR 7.83; 95% CI 5.40-11.36), number of dosages/day/client (OR 1.03; 95% CI 1.01-1.05), nursing home 2 (OR 3.97; 95% CI 2.86-5.50), medication not supplied by distribution robot (OR 2.92; 95% CI 2.04-4.18), time classes "7-10 am" (OR 2.28; 95% CI 1.50-3.47) and "10 am-2 pm" (OR 1.96; 1.18-3.27) and day of the week "Wednesday" (OR 1.46; 95% CI 1.03-2.07) are associated with a higher risk of administration errors. CONCLUSIONS Medication administration in nursing homes is prone to many errors. This study indicates that the handling of the medication after removing it from the robot packaging may contribute to this high error frequency, which may be reduced by training of nurse attendants, by automated clinical decision support and by measures to reduce workload.

Original languageEnglish
Pages (from-to)486-492
Number of pages7
JournalJournal of the American Medical Informatics Association
Volume16
Issue number4
DOIs
Publication statusPublished - 25-Apr-2009
Externally publishedYes

Keywords

  • Aged
  • Aged, 80 and over
  • Decision Support Systems, Clinical
  • Female
  • Humans
  • Male
  • Medical Order Entry Systems
  • Medication Errors/statistics & numerical data
  • Medication Systems
  • Netherlands
  • Nursing Homes/organization & administration
  • Observation
  • Prospective Studies
  • Risk Factors
  • Robotics

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