Effectiveness of a continuous quality improvement program aiming to reduce unplanned extubation: a prospective study

Intensive Care Med. 1996 Nov;22(11):1269-71. doi: 10.1007/BF01709348.

Abstract

Objective: To evaluate the effectiveness of a continuous quality improvement (CQI) program in reducing the incidence of unplanned endotracheal extubation.

Design: Prospective study over a 9-month period.

Setting: Adult intensive care units (ICUs including coronary care unit, medical ICU, surgical ICU, and cardiovascular surgical ICU) in a university-affiliated medical center.

Patients: 831 consecutive mechanically ventilated patients.

Interventions: CQI program focusing on standardization of procedures, improvement of communication, and identification and management of high-risk patients.

Measurements and results: With the implementation of this CQI program, the overall incidence density of unplanned extubation (defined as number of new unplanned extubations per mechanical ventilation patient-days) significantly decreased from 2.6% in the first trimester to 1.5% in the second trimester and 1.2% in the third trimester (p = 0.01). This reduction was essentially the result of a decrease in unplanned extubation in orally intubated patients (incidence density 4.6, 1.7 and 1.0% for three trimesters, respectively; p < 0.0001). Unplanned extubation in nasally intubated patients remained largely unaffected (1.2, 1.4, and 1.4% for three trimesters, respectively; p = 0.92).

Conclusions: The implementation of a concerted CQI program is effective in reducing the overall incidence of unplanned endotracheal extubation.

MeSH terms

  • Critical Care / standards
  • Equipment Failure
  • Female
  • Humans
  • Intensive Care Units / standards*
  • Intubation, Intratracheal / instrumentation
  • Intubation, Intratracheal / statistics & numerical data*
  • Linear Models
  • Male
  • Middle Aged
  • Patient Care Planning / standards
  • Patient Care Team
  • Prospective Studies
  • Respiration, Artificial / instrumentation
  • Respiration, Artificial / statistics & numerical data*
  • Risk Factors
  • Total Quality Management*