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. 2012 Oct;47(5):2060-80.
doi: 10.1111/j.1475-6773.2012.01402.x. Epub 2012 Mar 30.

Hospital-level variation in the use of intensive care

Christopher W Seymour  1 , Theodore J Iwashyna, William J Ehlenbach, Hannah Wunsch, Colin R Cooke
Affiliations

Hospital-level variation in the use of intensive care

Christopher W Seymour et al. Health Serv Res. 2012 Oct.

Erratum in

  • Health Serv Res. 2013 Apr;48(2 Pt 1):681

Abstract

Objective: To determine the extent to which hospitals vary in the use of intensive care, and the proportion of variation attributable to differences in hospital practice that is independent of known patient and hospital factors.

Data source: Hospital discharge data in the State Inpatient Database for Maryland and Washington States in 2006.

Study design: Cross-sectional analysis of 90 short-term, acute care hospitals with critical care capabilities. DATA COLLECTION/METHODS: We quantified the proportion of variation in intensive care use attributable to hospitals using intraclass correlation coefficients derived from mixed-effects logistic regression models after successive adjustment for known patient and hospital factors.

Principal findings: The proportion of hospitalized patients admitted to an intensive care unit (ICU) across hospitals ranged from 3 to 55 percent (median 12 percent; IQR: 9, 17 percent). After adjustment for patient factors, 19.7 percent (95 percent CI: 15.1, 24.4) of total variation in ICU use across hospitals was attributable to hospitals. When observed hospital characteristics were added, the proportion of total variation in intensive care use attributable to unmeasured hospital factors decreased by 26-14.6 percent (95 percent CI: 11, 18.3 percent).

Conclusions: Wide variability exists in the use of intensive care across hospitals, not attributable to known patient or hospital factors, and may be a target to improve efficiency and quality of critical care.

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Figures

Figure 1
Figure 1
Hospital and Patient Accrual
Figure 2
Figure 2
Rates of ICU Use Ranked across Hospitals (N = 90) with 95 Percent Confidence Intervals. (Estimates are derived from Model 2, adjusted to the modal value of categorical covariates and centered mean value of continuous covariates. That is, these estimates are both risk- and reliability-adjusted.)
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