The effect of implementing high-intensity intensive care unit staffing model on outcome of critically ill oncology patients*
Crit Care Med. 2009 Apr 20;
Authors: Hawari FI, Al Najjar TI, Zaru L, Al Fayoumee W, Salah SH, Mukhaimar MZ
OBJECTIVE:: Implementing high-intensity staffing model improves outcome in general intensive care units (ICUs). We studied the effect of implementing such a model on the outcome of critically ill medical patients in an oncology ICU. DESIGN:: We compared admission rates, ICU mortality rates (MRs), 28-day MRs, length of stay (LOS) for patients discharged alive, and bed turnover rates of medical patients admitted to the ICU in the year 2004 (before an intensivist model was established) with those in the years 2006 and 2007 (after the model was established). We allowed for 1 year of transition to implement the changes required including the transformation of the ICU to a closed ICU with daily multidisciplinary rounds led by an intensivist as described in the Leapfrog model. RESULTS:: ICU admissions increased from 236 patients (2004) to 388 (2006) and 446 (2007). There was no significant difference in the disease severity of illness when compared by Acute Physiology and Chronic Health Evaluation II scores, 20.6 (before) vs. 20.9 (after) (p = 0.386). ICU MR for the consecutive years decreased from 35.17% (95% confidence interval [CI]: 29.08-41.26) to 23.97% (95% CI: 19.72-28.22) and 22.87% (95% CI: 18.97-26.77), and 28-day MRs decreased from 47.69% (95% CI: 40.68-54.7) to 38.24% (95% CI: 32.91-43.58) and 29.84% (95% CI: 24.79-34.89). LOS (for patients who survived) decreased from a mean of 4.26 days (95% CI: 3.19-5.33) to 2.63 (95% CI: 2.4-2.86) and 2.63 (95% CI: 2.4-2.86). Bed turnover rates increased from 5.0 patient/bed (95% CI: 4.22-5.78) to 6.9 patient/bed (95% CI: 6.04-7.77) and 7.56 patient/bed (95% CI: 6.67-8.44). CONCLUSION:: Implementing a high-intensity staffing model is associated with significant improvements in MRs, LOS, and bed utilization of critically ill oncology patients.
PMID: 19384194 [PubMed - as supplied by publisher]