The nature and causes of unintended events reported at 10 internal medicine departments

J Patient Saf. 2011 Dec;7(4):224-31. doi: 10.1097/PTS.0b013e3182388f97.


Objective: This study aimed to examine the nature and causes of unintended events (UEs) at internal medicine departments (IMD).

Methods: An observational study was conducted at 10 IMDs in 8 Dutch hospitals. The study period per participating department was 5 to 14 weeks. During this period, staff were asked to report all UEs concerning patient safety. To identify underlying root causes, experienced researchers analyzed the reports using a standardized root cause analysis method called PRISMA medical.

Results: Hospital staff reported 625 UEs. Medication-related UEs were the most reported events (42%). Of all reported UEs, 12% involved the collaboration between the IMD and other departments within the hospital.On the basis of the 625 UEs, 920 root causes were identified. The mean (SD) number of root causes per incident was 1.47 (0.68). Human root causes were related to 83.2% of the UEs, organizational root causes were related to 15.7%, technical root causes were related to 7%, and other root causes were related to 8.6% of the UEs.More than half of the reported UEs reached the patient (62%), with suboptimal care as the most frequently occurring consequence (44.7%). Physical injury occurred in 10.3% of the UEs.

Conclusions: Hospital staff reporting UEs seems to be a good method for gaining insight into the types of UEs that occur at hospital departments. Although many UEs had human causes, identifying technical and organizational causes is important for the development of successful improvement strategies considering their contribution to human error. Important targets for these strategies are the medication process and collaboration within the hospital.

Publication types

  • Evaluation Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Hospital Departments / statistics & numerical data*
  • Humans
  • Internal Medicine / statistics & numerical data*
  • Medical Errors / prevention & control*
  • Middle Aged
  • Models, Organizational
  • Netherlands
  • Organizational Culture
  • Patient Safety / statistics & numerical data*
  • Patient Satisfaction / statistics & numerical data*
  • Risk Factors
  • Risk Management / methods*
  • Risk Management / organization & administration
  • Root Cause Analysis
  • Statistics as Topic