Effect of ambient workload in the intensive care unit on mortality and time to discharge alive

Healthc Q. 2009:12 Spec No Patient:8-14. doi: 10.12927/hcq.2009.20961.

Abstract

The purpose of this study was to determine the relationship between ambient workload and outcomes of patients in the intensive care unit (ICU). Measures of workload evaluated for each patient on each day of ICU admission were the number of new admissions, ICU census, "code blue" patients not admitted and Acute Physiology and Chronic Health Evaluation (APACHE) II scores and Multiple Organ Dysfunction Scores (MODSs) for admitted patients. Patients were defined as the patient at risk (the "index" patient) and the other patients in the ICU at the same time (the "non-index" patients). Logistic regression (for hospital mortality) and Cox proportional hazards regression (for time to discharge alive) were used to investigate the association between workload and outcomes. In total, 1,705 patients were included. Higher MODSs of non-index patients on the last day of the ICU admission were associated with lower mortality (odds ratio [OR] 0.82 per MODS point, 95% CI 0.72-0.94). A higher number of code blues during the ICU stay was associated with higher mortality (OR 1.18 per event, 95% CI 1.01-1.37). A higher ICU census and MODS of the non-index patients on the day of ICU admission were associated with a shorter time to discharge alive (hazard rate [HR] 1.03 per patient, 95% CI: 1.01-1.06, and 1.07 per MODS point, 95% CI:1.01-1.15, respectively).The association between measures of ambient workload in the ICU and patient outcomes is variable.Future resource planning and studies of patient safety would benefit from a prospective analysis of these factors to define workload limits and tolerances.

MeSH terms

  • Aged
  • British Columbia
  • Databases, Factual
  • Female
  • Hospital Mortality / trends*
  • Humans
  • Intensive Care Units*
  • Male
  • Middle Aged
  • Nursing Staff, Hospital
  • Outcome Assessment, Health Care
  • Patient Discharge*
  • Proportional Hazards Models
  • Time Factors
  • Workload*