Mortality among Patients Admitted to Strained Intensive Care Units.

Link to article at PubMed

Mortality among Patients Admitted to Strained Intensive Care Units.

Am J Respir Crit Care Med. 2013 Aug 30;

Authors: Gabler NB, Ratcliffe SJ, Wagner J, Asch DA, Rubenfeld GD, Angus DC, Halpern SD

Rationale: The aging population may strain intensive care unit (ICU) capacity and adversely affect patient outcomes. Existing fluctuations in demand for ICU care offer an opportunity to explore such relationships. Objectives: To determine whether transient increases in ICU strain influence patient mortality, and identify characteristics of ICUs that are resilient to surges in capacity strain. Methods: Retrospective cohort study of 264,401 patients admitted to 155 U.S. ICUs from 2001-2008. We used logistic regression to examine relationships of measures of ICU strain (census, average acuity, and proportion of new admissions) near the time of ICU admission with mortality. Measurements and Main Results: 36,465 (14%) patients died in the hospital. ICU census on the day of a patient's admission was associated with increased mortality (OR: 1.02 per SD-unit increase (95% CI: 1.00, 1.03)). This effect was greater among ICUs employing closed (OR: 1.07 (95% CI: 1.02, 1.12)) versus open (OR: 1.01 (95% CI: 0.99, 1.03)) physician staffing models (interaction p-value=0.02). The relationship between census and mortality was stronger when the census was comprised of higher acuity patients (interaction p-value<0.01). Averaging strain over the first three days of patients' ICU stays yielded similar results except that the proportion of new admissions was now also associated with mortality (OR: 1.04 for each 10% increase (95% CI: 1.02, 1.06)). Conclusions: Several sources of ICU strain are associated with small but potentially important increases in patient mortality, particularly in ICUs employing closed staffing models. Although closed ICUs may promote favorable outcomes under static conditions, they are susceptible to being overwhelmed by patient influxes.

PMID: 23992449 [PubMed - as supplied by publisher]

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