title: The Charlson comorbidity index can be used prospectively to identify patients who will incur high future costs.
abstract: BACKGROUND
  Reducing health care costs requires the ability to identify patients most likely to incur high costs. Our objective was to evaluate the ability of the Charlson comorbidity score to predict the individuals who would incur high costs in the subsequent year and to contrast its predictive ability with other commonly used predictors.
  
  
  METHODS
  We contrasted the prior year Charlson comorbidity index, costs, Diagnostic Cost Group (DCG) and hospitalization as predictors of subsequent year costs from claims data of fund that provides comprehensive health benefits to a large union of health care workers. Total costs in the subsequent year was the principal outcome.
  
  
  RESULTS
  Of the 181,764 predominantly Black and Latino beneficiaries, 70% were adults (mean age 45.7 years; 62% women). As the comorbidity index increased, total yearly costs increased significantly (P<.001). At lower comorbidity, the costs were similar across different chronic diseases. Using regression to predict total costs, top 5th and 10th percentile of costs, the comorbidity index, prior costs and DCG achieved almost identical explained variance in both adults and children.
  
  
  CONCLUSIONS
  The comorbidity index predicted health costs in the subsequent year, performing as well as prior cost and DCG in identifying those in the top 5% or 10%. The comorbidity index can be used prospectively to identify patients who are likely to incur high costs.
  
  
  BACKGROUND
  ClinicalTrials.gov NCT01761253.
authors.affiliation: Center for Integrative Medicine, Weill Cornell Medical College, New York, NY, United States of America.
authors.forename: Mary
authors.initials: M
authors.lastname: Charlson
authors.affiliation: Department of Statistical Science, Cornell University, Ithaca, NY, United States of America.
authors.forename: Martin T
authors.initials: MT
authors.lastname: Wells
authors.affiliation: 1199SEIU Benefit and Pension Funds, New York, NY, United States of America.
authors.forename: Ralph
authors.initials: R
authors.lastname: Ullman
authors.affiliation: 1199SEIU Benefit and Pension Funds, New York, NY, United States of America.
authors.forename: Fionnuala
authors.initials: F
authors.lastname: King
authors.affiliation: 1199SEIU Benefit and Pension Funds, New York, NY, United States of America.
authors.forename: Celia
authors.initials: C
authors.lastname: Shmukler
mesh_terms: D000293:Adolescent; D002648:Child; D002675:Child, Preschool; D002908:Chronic Disease / Q000191:economics* / Q000453:epidemiology*; D015897:Comorbidity; D005260:Female; D017048:Health Care Costs / Q000639:trends*; D006760:Hospitalization / Q000191:economics; D006801:Humans; D007223:Infant; D008297:Male; D008875:Middle Aged; D018803:Models, Economic; D011446:Prospective Studies; D012044:Regression Analysis; D055815:Young Adult