Contribution of a measure of disease complexity (COMPLEX) to prediction of outcome and charges among hospitalized patients.
Attention has been focused on the need to adjust hospital reimbursement and outcomes of hospital care for level of illness. Extant measures of disease severity, however, fail to consider the contribution of disease complexity. We developed an easily retrievable measure of disease complexity (COMPLEX) by modifying an existing severity system, computerized Disease Staging. The contribution of COMPLEX (the number of body systems affected with a Disease Staging score of 2 or more) to the prediction of outcome was assessed in two studies: (1) a population-based analysis of readmission and mortality after hospitalization and (2) an analysis of hospital charges among patients who were in an intensive-care unit. The amount of variation in mortality explained by factors included in the Health Care Financing Administration model was significantly improved when COMPLEX was added to the model (adjusted odds ratio per body system, 1.83; 95% confidence interval, 1.61 to 2.08). A significant association was also observed between COMPLEX score and hospital readmission after adjustment for age, sex, case-mix, and disease severity (adjusted odds ratio, 1.31; 95% confidence interval, 1.20 to 1.44). When COMPLEX was added to case-mix and disease severity in a model for predicting hospital charges, the percentage of variation in hospital charges explained by the model increased from 25% to 38%. These findings demonstrate the important contribution of disease complexity to the analysis of outcome of medical care and utilization of resources. Outcome or reimbursement models that do not incorporate disease complexity may negatively affect institutions with a high proportion of patients who have complex conditions.
Naessens
J M
JM
Section of Biostatistics, Mayo Clinic, Rochester, MN 55905.
Leibson
C L
CL
Krishan
I
I
Ballard
D J
DJ
D000368:Aged; D015897:Comorbidity; D003953:Diagnosis-Related Groups / Q000191:economics; D005249:Fees and Charges / Q000706:statistics & numerical data; D005260:Female; D006760:Hospitalization / Q000191:economics*; D006801:Humans; D007362:Intensive Care Units / Q000191:economics / Q000706:statistics & numerical data; D016015:Logistic Models; D008297:Male; D006278:Medicare; D008910:Minnesota / Q000453:epidemiology; D009026:Mortality; D010043:Outcome and Process Assessment, Health Care / Q000706:statistics & numerical data*; D010359:Patient Readmission / Q000706:statistics & numerical data; D011445:Prospective Payment System; D012044:Regression Analysis; D012720:Severity of Illness Index; D014481:United States