The influence of missing components of the Acute Physiology Score of APACHE III on the measurement of ICU performance

Bekele Afessa, Mark T. Keegan, Ognjen Gajic, Rolf D. Hubmayr, Steve G. Peters

Research output: Contribution to journalArticle

30 Citations (Scopus)

Abstract

Objective: To determine the impact of missing Acute Physiology Score (APS) values on risk-adjusted mortality. Design: Retrospective review of prospectively collected Acute Physiology and Chronic Health Evaluation (APACHE) III database. Setting: The intensive care units (ICUs) of an academic medical center. Patients: 38,411 patients admitted to ICU between October 1994 and December 2003. Measurements and results: Data were collected on ICU type, missing first ICU day APS values, predicted and observed hospital mortality, standardized mortality ratio (SMR), 95% confidence interval (CI), odds ratio (OR). The overall observed and predicted hospital mortality rates were 8.7% and 10.8%, respectively, with SMR of 0.806 (95% CI 0.779-0.834). Complete data were available in 829 (2.2%). Vital signs were missing in almost none and serum albumin and bilirubin in over 80% of the patients. The number of missing variables was higher in less sick and surgical ICU patients. Logistic regression analysis showed that the risk of dying in the hospital was significantly associated with the number of missing APS variables (OR 1.058, 95% CI 1.027-1.090) when adjusted for the severity of illness. The risk of death was also associated with the type of missing variables. Conclusions: Since missing APS values may lead to underestimation of the predicted mortality rates, the number and type of missing variables should be taken into consideration when assessing the performance of an ICU. Unless data collection is standardized, future prognostic models should use variables that are routinely measured in most critically ill patients without sacrificing statistical precision.

Original languageEnglish (US)
Pages (from-to)1537-1543
Number of pages7
JournalIntensive Care Medicine
Volume31
Issue number11
DOIs
StatePublished - Nov 2005

Fingerprint

APACHE
Intensive Care Units
Mortality
Confidence Intervals
Hospital Mortality
Odds Ratio
Vital Signs
Critical Care
Bilirubin
Critical Illness
Serum Albumin
Logistic Models
Regression Analysis
Databases

Keywords

  • Acute Physiology and Chronic Health Evaluation
  • Intensive care unit
  • Joint Commission on Accreditation of Healthcare Organizations
  • Mortality
  • Quality of healthcare
  • Severity of illness index

ASJC Scopus subject areas

  • Critical Care and Intensive Care Medicine

Cite this

The influence of missing components of the Acute Physiology Score of APACHE III on the measurement of ICU performance. / Afessa, Bekele; Keegan, Mark T.; Gajic, Ognjen; Hubmayr, Rolf D.; Peters, Steve G.

In: Intensive Care Medicine, Vol. 31, No. 11, 11.2005, p. 1537-1543.

Research output: Contribution to journalArticle

Afessa, Bekele ; Keegan, Mark T. ; Gajic, Ognjen ; Hubmayr, Rolf D. ; Peters, Steve G. / The influence of missing components of the Acute Physiology Score of APACHE III on the measurement of ICU performance. In: Intensive Care Medicine. 2005 ; Vol. 31, No. 11. pp. 1537-1543.
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abstract = "Objective: To determine the impact of missing Acute Physiology Score (APS) values on risk-adjusted mortality. Design: Retrospective review of prospectively collected Acute Physiology and Chronic Health Evaluation (APACHE) III database. Setting: The intensive care units (ICUs) of an academic medical center. Patients: 38,411 patients admitted to ICU between October 1994 and December 2003. Measurements and results: Data were collected on ICU type, missing first ICU day APS values, predicted and observed hospital mortality, standardized mortality ratio (SMR), 95{\%} confidence interval (CI), odds ratio (OR). The overall observed and predicted hospital mortality rates were 8.7{\%} and 10.8{\%}, respectively, with SMR of 0.806 (95{\%} CI 0.779-0.834). Complete data were available in 829 (2.2{\%}). Vital signs were missing in almost none and serum albumin and bilirubin in over 80{\%} of the patients. The number of missing variables was higher in less sick and surgical ICU patients. Logistic regression analysis showed that the risk of dying in the hospital was significantly associated with the number of missing APS variables (OR 1.058, 95{\%} CI 1.027-1.090) when adjusted for the severity of illness. The risk of death was also associated with the type of missing variables. Conclusions: Since missing APS values may lead to underestimation of the predicted mortality rates, the number and type of missing variables should be taken into consideration when assessing the performance of an ICU. Unless data collection is standardized, future prognostic models should use variables that are routinely measured in most critically ill patients without sacrificing statistical precision.",
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