Key result
Administrative models predict ~38% lower mortality than physiologic models in critically ill patients.
Why the study?
Do administrative and physiologic predictive models differ in determining risk-adjusted mortality rates in critically ill patients?
Population
556 critically ill patients from two intensive care units at academic medical centers in the United States.
Comparison
Administrative predictive model of mortality vs Physiologic predictive model of mortality
Design
Cohort
Authors
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Administrative models predict lower mortality than physiologic ones in critical illness; leaves open which better informs risk-adjusted metrics.
Observational (n=556)
Yes
Do administrative and physiologic predictive models differ in determining risk-adjusted mortality rates in critically ill patients?
Absolute Event Rate: 15.3% vs 24.6%
p-value: p=<0.001
Administrative and physiologic models for predicting mortality in critically ill patients yield significantly different estimates, particularly at higher mortality risks, highlighting the need for caution when interpreting risk-adjusted hospital metrics.
Schafer et al. (2012) conducted an observational in Critical illness (n=556). Administrative predictive model (UHC) vs. Physiologic predictive model (APACHE IV) was evaluated on Predicted mortality (p=<0.001). The administrative model predicted a significantly lower mortality rate of 15.3% compared to 24.6% for the physiologic model (p<0.001) in critically ill patients, with poor agreement between the two models as mortality increased.
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