Mortality rate and length of stay of patients admitted to the intensive care unit in July

Crit Care Med. 2004 May;32(5):1161-5. doi: 10.1097/01.ccm.0000126151.56590.99.


Objective: At the beginning of each academic year in July, inexperienced residents and fellows begin to care for patients. This inexperience can lead to poor patient outcome, especially in patients admitted to the intensive care unit (ICU). The objective of this study was to determine the impact of July ICU admission on patient outcome.

Design: Retrospective, cohort study.

Setting: Academic, tertiary medical center.

Patients: Patients admitted to the ICU from October 1994 through September 2002.

Interventions: None.

Measurements and main results: Demographics, Acute Physiology and Chronic Health Evaluation (APACHE) III score and predicted mortality, admission source, admission date, intensity of treatment, ICU length of stay (LOS), and hospital mortality of 29,084 patients were obtained. The actual and predicted weighted ICU LOS and their ratio were calculated. Logistic regression analysis was used to compare the hospital mortality rate of patients admitted to the ICU in July with those admitted during the rest of the year, with adjustment for potentially confounding variables. The patients' mean age was 62.3 +/- 17.6 yrs; 57.3% were male and 95.5% white. Both the customized predicted and observed hospital mortality rates of the entire cohort were 8.2%. The majority (76.7%) of the patients were discharged home, and 15.1% were discharged to other facilities. When adjusted for potentially confounding variables, ICU admission in July was not associated with higher hospital mortality rate compared with any other month. There were no significant differences in the discharge location of patients between July and any one of the other months. There were no statistically significant differences in the weighted ICU LOS ratio between July and any of the other months.

Conclusions: ICU admission in July is not associated with increased hospital mortality rate or ICU length of stay.

MeSH terms

  • Academic Medical Centers
  • Adult
  • Age Distribution
  • Aged
  • Confounding Factors, Epidemiologic
  • Female
  • Health Services Research
  • Hospital Mortality*
  • Humans
  • Intensive Care Units / statistics & numerical data*
  • Length of Stay / statistics & numerical data*
  • Logistic Models
  • Male
  • Medical Staff, Hospital / education
  • Medical Staff, Hospital / supply & distribution
  • Middle Aged
  • Minnesota
  • Patient Admission / statistics & numerical data*
  • Predictive Value of Tests
  • Prognosis
  • Quality of Health Care / statistics & numerical data
  • Retrospective Studies
  • Risk Factors
  • Seasons*
  • Survival Rate