title: Adjusting for comorbidities in cost of illness studies.
abstract: BACKGROUND
  Differences in cost of illness (COI) methodological approaches have led to disparate results. This analysis examines two sources of this variation: specification of comorbidities in the estimated cost models and assumed prevalence rates used for generating aggregate costs. The study provides guidance in determining which comorbidities are important to include and how to handle uncertainty in optimal model specification and prevalence rate assumptions.
  
  
  METHODS
  Comorbidities are categorized into four types. Type I comorbidities are those that increase the risk of the disease of interest; Type II comorbidities have no causal link to the disease of interest but are, nonetheless, highly correlated with that disease; Type III comorbidities are illnesses that the disease of interest may cause, and Type IV are comorbidities that have no causal link to the disease of interest and are only weakly correlated with that disease. Two-part models are used to estimate the direct costs of rheumatoid arthritis and diabetes mellitus using 2000-2007 Medical Expenditure Panel Survey data.
  
  
  RESULTS
  COI estimates are sensitive to the specification of comorbidities. The odds of incurring any expenses varies by 71% for diabetes mellitus and by 27% for rheumatoid arthritis, while conditional expenditures (e.g., expenditures among subjects incurring at least some expenditures) vary by 62% and 45%, respectively. Uncertainty in prevalence rates cause costs to vary. A sensitivity analysis estimated the COI for diabetes ranges from $131.7-$172.0 billion, while rheumatoid arthritis varies from $12.8-$26.2 billion.
  
  
  CONCLUSIONS
  The decision to include Type II and Type III comorbidities is crucial in COI studies. Alternative models should be included with and without the Type III comorbidities to gauge the range of cost effects of the disease. In generating costs, alternative values for prevalence rates should be used and a sensitivity analysis should be performed.
authors.affiliation: Stony Brook University, Stony Brook , New York, USA.
authors.forename: John A
authors.initials: JA
authors.lastname: Rizzo
authors.forename: Jie
authors.initials: J
authors.lastname: Chen
authors.forename: Candace L
authors.initials: CL
authors.lastname: Gunnarsson
authors.forename: Ahmad
authors.initials: A
authors.lastname: Naim
authors.forename: Jennifer H
authors.initials: JH
authors.lastname: Lofland
mesh_terms: D001172:Arthritis, Rheumatoid / Q000150:complications / Q000191:economics; D015897:Comorbidity; D017281:Cost of Illness; D048909:Diabetes Complications / Q000191:economics; D003920:Diabetes Mellitus / Q000191:economics; D019538:Health Care Surveys; D005102:Health Expenditures / Q000706:statistics & numerical data*; D006801:Humans; D017059:Models, Econometric; D015233:Models, Statistical; D015995:Prevalence; D012107:Research Design
keywords: Cost of illness; Diabetes mellitus; Rheumatoid arthritis