Effect of mortality rate on the performance of the Acute Physiology and Chronic Health Evaluation II: a simulation study.
OBJECTIVE
To evaluate the impact of case mix variation on the performance of the Acute Physiology and Chronic Health Evaluation (APACHE) II using measures of calibration and discrimination.


METHODS
APACHE II data were collected prospectively at the surgical intensive care unit of the University of Vermont on all adult admissions over an 8-yr period (excluding cardiac surgical patients, burn patients, and patients < 16 yrs of age). The original case mix was systematically varied to create 2,000 different case mixes ranging in mortality between 5% and 18% using a computer-intensive resampling algorithm. The area under the receiver operating characteristic curve and the Hosmer-Lemeshow C statistic were derived for each of the simulated case mixes with bootstrapping.


METHODS
The surgical intensive care unit at a 450-bed teaching hospital.


METHODS
A group of 6,806 adult surgical patients excluding cardiac surgical patients and burn patients.


RESULTS
Simulated data sets were created from a database of patients treated at a single institution to test the hypothesis that the performance of APACHE II is stable across a clinically reasonable range of mortality rates. The discrimination and calibration of APACHE II varied with case mix.


CONCLUSIONS
The discrimination of APACHE II is not independent of case mix. However, the variability of the Hosmer-Lemeshow statistic as a function of the case mix may simply reflect the limitations of this goodness of fit statistic to assess model calibration. Because the discrimination of APACHE II is a function of case mix, caution should be exercised when using APACHE II-based adjusted mortality rates to compare intensive care units with widely divergent case mixes.
Glance
L G
LG
University of Rochester School of Medicine, NY, USA. laurent_glance@urmc.rochester.edu
Osler
T M
TM
Papadakos
P
P
D018806:APACHE; D000328:Adult; D000465:Algorithms; D002138:Calibration; D003953:Diagnosis-Related Groups / Q000145:classification* / Q000706:statistics & numerical data; D016002:Discriminant Analysis; D017052:Hospital Mortality; D006785:Hospitals, University; D006801:Humans; D007362:Intensive Care Units / Q000706:statistics & numerical data; D016014:Linear Models; D017063:Outcome Assessment, Health Care; D011237:Predictive Value of Tests; D011379:Prognosis; D011446:Prospective Studies; D012372:ROC Curve; D012307:Risk Factors; D016019:Survival Analysis; D014707:Vermont / Q000453:epidemiology