Predicted probabilities of hospital death as a measure of admission severity of illness.
This paper evaluates a new method for assessing hospital admission severity of illness based on disease-specific models (logistic regression) of the probability of in-hospital mortality. Results for the 26 disease groups in MDC 4--Diseases of the Respiratory System, MDC 5--Diseases of the Circulatory System, and MDC 6--Diseases of the Digestive System are presented using data on all 1991 admissions from 111 hospitals throughout the United States. These disease models are empirically derived using clinical findings from laboratory, radiology, pathology, diagnostic procedures, patient history and physical exam, as well as patient age and sex. Each predictive algorithm is presented, and the strong predictive performance of these models is indicated by the average C statistic of .870. A predicted probability of death is calculated for each hospital patient in the study sample, and these probabilities comprise a continuous variable that indicates admission severity of illness.
Steen
P M
PM
Applied Research Division, MediQual Systems, Inc., Worcester, MA.
Brewster
A C
AC
Bradbury
R C
RC
Estabrook
E
E
Young
J A
JA
D000465:Algorithms; D002318:Cardiovascular Diseases / Q000145:classification; D004066:Digestive System Diseases / Q000145:classification; D005260:Female; D017052:Hospital Mortality; D006801:Humans; D016015:Logistic Models; D008297:Male; D010361:Patients / Q000145:classification / Q000706:statistics & numerical data; D011336:Probability; D011379:Prognosis; D015203:Reproducibility of Results; D012140:Respiratory Tract Diseases / Q000145:classification; D012720:Severity of Illness Index; D014481:United States / Q000453:epidemiology