Patient safety in intensive care: results from the multinational Sentinel Events Evaluation (SEE) study

Intensive Care Med. 2006 Oct;32(10):1591-8. doi: 10.1007/s00134-006-0290-7. Epub 2006 Jul 28.


Objective: To assess on a multinational level the prevalence and corresponding factors of selected unintended events that compromise patient safety (sentinel events) in intensive care units (ICUs).

Design: An observational, 24-h cross-sectional study of incidents in five representative categories.

Setting: 205 ICUs worldwide

Measurements: Events were reported by intensive care unit staff members with the use of a structured questionnaire. Both ICU- and patient-related factors were assessed.

Results: In 1,913 adult patients a total of 584 events affecting 391 patients were reported. During 24 h multiple errors related to medication occurred in 136 patients; unplanned dislodgement or inappropriate disconnection of lines, catheters, and drains in 158; equipment failure in 112; loss, obstruction or leakage of artificial airway in 47; and inappropriate turn-off of alarms in 17. Per 100 patient days, 38.8 (95% confidence interval 34.7-42.9) events were observed. In a multiple logistic regression with ICU as a random component, the following were associated with elevated odds for experiencing a sentinel event: any organ failure (odds ratio 1.13, 95% confidence interval 1.00-1.28), a higher intensity in level of care (odds ratio 1.62, 95% confidence interval 1.18-2.22), and time of exposure (odds ratio 1.06, 95% confidence interval 1.04-1.08).

Conclusions: Sentinel events related to medication, indwelling lines, airway, and equipment failure in ICUs occur with considerable frequency. Although patient safety is recognised as a serious issue in many ICUs, there is an urgent need for development and implementation of strategies for prevention and early detection of errors.

Publication types

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

MeSH terms

  • Adolescent
  • Adult
  • Aged
  • Aged, 80 and over
  • Cross-Sectional Studies
  • Equipment Failure
  • Female
  • Humans
  • Intensive Care Units / standards*
  • Intensive Care Units / statistics & numerical data
  • Logistic Models
  • Male
  • Medical Errors / prevention & control
  • Medical Errors / statistics & numerical data*
  • Middle Aged
  • Population Surveillance
  • Safety Management*