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J Pediatr ; 163(4): 1039-44.e5, 2013 Oct.
Article in English | MEDLINE | ID: mdl-23623513

ABSTRACT

OBJECTIVE: To investigate the effect of out-of-hours and winter admissions, and unit size on risk adjusted mortality in pediatric intensive care. STUDY DESIGN: A national pediatric intensive care clinical audit provided data on over 86000 admissions to 29 pediatric intensive care units (2006-2011). Multivariate logistic regression modeled risk adjusted mortality prior to discharge with out-of-hours (night, weekend, public holiday) admissions, admissions per unit, winter admission, and potential confounders, overall and separately for emergency and planned admissions. RESULTS: Nearly one-half (47.1%) of admissions were out-of-hours (n = 40948) and 79.2% of those were emergencies. Mortality for all out-of-hours admissions was raised (OR 1.1; 95% CI 1.02-1.2; P = .013), accounted for by planned admissions (OR 1.99; 95% CI 1.67-2.37; P < .001) compared with a reduced risk for emergency admissions (OR 0.93; 95% CI 0.86-1.1; P = .07). Winter admissions were associated with increased risk. Unit size did not affect mortality. CONCLUSIONS: A child admitted to pediatric intensive care as an out-of-hours emergency is not at increased risk of dying compared with a weekday daytime admission, indicating pediatric intensive care units provide consistent quality of care around the clock. Excess mortality in planned out-of-hours admissions may be explained by admissions following complex operations where risk-adjustment models underestimate the true probability of mortality. In winter, a time of seasonally high bed occupancy, there was an increased mortality risk, an effect which requires further investigation. Despite the different characteristics of small units, the absence of any effect of unit size on mortality suggests that number of admissions per unit does not influence standards of care.


Subject(s)
After-Hours Care/statistics & numerical data , Hospital Mortality , Intensive Care Units, Pediatric/statistics & numerical data , Patient Admission/statistics & numerical data , Child , Child, Preschool , Female , Humans , Infant , Logistic Models , Male , Multivariate Analysis , Risk Factors , Seasons , Time Factors
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