Mortality among patients admitted to intensive care units during weekday day shifts compared with "off" hours

Crit Care Med. 2007 Jan;35(1):3-11. doi: 10.1097/01.CCM.0000249832.36518.11.


Objective: To determine whether mortality rates among intensive care unit (ICU) patients differ according to the time of ICU admission, we compared the death rates for patients admitted during weekday day shifts and off hours (from 6:30 pm to 8:29 am the next day for night shifts, from Saturday 1:00 pm to Monday 8:29 am for weekends, and from 8:30 am to 8:29 am the following morning for public holidays).

Methods: Retrospective cohort study of data collected prospectively from 23 ICUs located in the Paris metropolitan region, France. Between January 2000 and December 2003, 51,643 patients were admitted to these ICUs. Patients were grouped according to their day and time of admission and compared using univariable and multivariable analyses.

Interventions: None.

Measurements and main results: Of the 51,643 patients admitted to ICUs, 33,857 (65.6%) were admitted during off hours. These latter patients were less critically ill than those admitted during day shifts, had fewer failed organs, required fewer support procedures, and their crude in-hospital mortality was lower (20.7 vs. 24.5%, p < .0001). After adjustment for initial disease severity, in-hospital mortality was not higher for off-hours admissions than weekday day admissions and even remained slightly lower (adjusted odds ratio, 0.93; 95% confidence interval, 0.87-0.98).

Conclusions: Admission during off hours is common. In our ICUs, off-hours admissions were not associated with higher mortality and might even be associated with a lower death rate.

Publication types

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

MeSH terms

  • Adult
  • Aged
  • Analysis of Variance
  • Cause of Death
  • Comorbidity
  • Female
  • Health Services Research
  • Holidays / statistics & numerical data
  • Hospital Mortality*
  • Humans
  • Intensive Care Units / organization & administration*
  • Length of Stay / statistics & numerical data
  • Logistic Models
  • Male
  • Medical Staff, Hospital / organization & administration
  • Middle Aged
  • Night Care / organization & administration*
  • Paris / epidemiology
  • Patient Admission / statistics & numerical data*
  • Personnel Staffing and Scheduling / organization & administration
  • Retrospective Studies
  • Risk Factors
  • Survival Rate
  • Time Factors