Reliability of intensive care unit admitting and comorbid diagnoses, race, elements of Acute Physiology and Chronic Health Evaluation II score, and predicted probability of mortality in an electronic intensive care unit database

J Crit Care. 2009 Sep;24(3):401-7. doi: 10.1016/j.jcrc.2009.03.008. Epub 2009 Jul 3.


Background: Although reliability of severity of illness and predicted probability of hospital mortality have been assessed, interrater reliability of the abstraction of primary and other intensive care unit (ICU) admitting diagnoses and underlying comorbidities has not been studied.

Methods: Patient data from one ICU were originally abstracted and entered into an electronic database by an ICU nurse. A research assistant reabstracted patient demographics, ICU admitting diagnoses and underlying comorbidities, and elements of Acute Physiology and Chronic Health Evaluation II (APACHE II) score from 100 random patients of 474 admitted during 2005 using an identical electronic database. Chamberlain's percent positive agreement was used to compare diagnoses and comorbidities between the 2 data abstractors. A kappa statistic was calculated for demographic variables, Glasgow Coma Score, APACHE II chronic health points, and HIV status. Intraclass correlation was calculated for acute physiology points and predicted probability of hospital mortality.

Results: Percent positive agreement for ICU primary and other admitting diagnoses ranged from 0% (primary brain injury) to 71% (sepsis), and for underlying comorbidities, from 40% (coronary artery bypass graft) to 100% (HIV). Agreement as measured by kappa statistic was strong for race (0.81) and age points (0.95), moderate for chronic health points (0.50) and HIV (0.66), and poor for Glasgow Coma Score (0.36). Intraclass correlation showed a moderate-high agreement for acute physiology points (0.88) and predicted probability of hospital mortality (0.71).

Conclusion: Reliability for ICU diagnoses and elements of the APACHE II score is related to the objectivity of primary data in the medical charts.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Age Factors
  • Aged
  • Comorbidity
  • Diagnosis, Differential
  • Female
  • Hospital Mortality*
  • Humans
  • Information Systems / statistics & numerical data*
  • Intensive Care Units / statistics & numerical data*
  • Male
  • Middle Aged
  • Observer Variation
  • Patient Admission / statistics & numerical data*
  • Probability
  • Racial Groups*
  • Reproducibility of Results
  • Risk Factors