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      Increased mortality associated with after-hours and weekend admission to the intensive care unit: a retrospective analysis.

      The Medical journal of Australia
      Adult, After-Hours Care, organization & administration, Analysis of Variance, Australia, Circadian Rhythm, Cohort Studies, Female, Hospital Mortality, trends, Humans, Intensive Care, Intensive Care Units, utilization, Logistic Models, Male, Medical Staff, Hospital, Middle Aged, Multivariate Analysis, New Zealand, Night Care, Patient Admission, statistics & numerical data, Physician's Practice Patterns, standards, Retrospective Studies, Risk Assessment, Statistics, Nonparametric, Time Factors

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          Abstract

          To study variation in mortality associated with time and day of admission to the intensive care unit (ICU). Retrospective cohort analysis using the Australian and New Zealand Intensive Care Society Adult Patient Database. 245,057 admissions to 41 Australian ICUs from January 2000 to December 2008. Observed mortality and standardised mortality ratio (SMR) based on Acute Physiology and Chronic Health Evaluation III, 10th iteration (APACHE III-j) scores. Subgroup analysis was performed on the basis of elective surgical or emergency admission to ICU. 48% of patients were admitted after hours (18:00-05:59) and 20% of patients were admitted on weekends (Saturday and Sunday). Patients admitted after hours had a 17% hospital mortality rate compared with 14% of patients admitted in hours (P < 0.001); and SMRs of 0.92 (95% CI, 0.91-0.93) and 0.83 (95% CI, 0.83-0.84), respectively. Weekend admissions had a 20% hospital mortality rate compared with 14% on weekdays (P < 0.001), with SMRs of 0.95 (95% CI, 0.94-0.97) and 0.92 (95% CI, 0.92-0.93), respectively. Variation in outcome with time of admission to ICU was accounted for predominantly by elective surgical patients. Patients admitted to ICUs in Australia after hours and on weekends have a higher observed and risk-adjusted mortality than patients admitted at other times. Further research is required to determine the causes and relationship to resource availability and staffing.

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