title: A cost-benefit simulation model of coverage for bariatric surgery among full-time employees.
abstract: OBJECTIVE
  To use a simulation model to estimate the costs and benefits of bariatric surgery among full-time employees.
  
  
  METHODS
  Multivariate regression analysis of nationally representative survey data sets to estimate the costs of obesity and a simulation model of the number of years until breakeven under alternate assumptions about the costs and benefits of bariatric surgery.
  
  
  METHODS
  We used a 2-part model to estimate medical costs of obesity based on the 2000-2001 Medical Expenditure Panel Survey. We estimated work loss with a negative binomial regression based on the 2002 National Health Interview Survey. Using these results, we simulated the expected number of years required for a bariatric surgery procedure to become cost saving.
  
  
  RESULTS
  Nine percent of the full-time US workforce, or 29% of the obese workforce, is eligible for bariatric surgery. Obese workers eligible for bariatric surgery have 5.1 (P < .01) additional days of work loss and USD 2230 (in 2004 dollars) (P < .01) higher annual medical costs than persons of normal weight.
  
  
  CONCLUSIONS
  Although the cost implications of bariatric surgery among full-time employees depend on many factors, the simulations reveal that 5 or more years of follow-up are most likely required for these operations to become cost saving unless the employee bears a significant fraction of the total costs of the surgery.
authors.affiliation: RTI International, PO Box 12194, 3040 Cornwallis Road, Research Triangle Park, NC 27709-2194, USA. finkelse@rti.org
authors.forename: Eric A
authors.initials: EA
authors.lastname: Finkelstein
authors.forename: Derek S
authors.initials: DS
authors.lastname: Brown
mesh_terms: D000293:Adolescent; D000328:Adult; D050110:Bariatric Surgery / Q000191:economics*; D003362:Cost-Benefit Analysis / Q000379:methods*; D005260:Female; D006264:Health Benefit Plans, Employee; D006801:Humans; D019458:Insurance Coverage; D008297:Male; D008875:Middle Aged; D017059:Models, Econometric; D015999:Multivariate Analysis; D012044:Regression Analysis; D014481:United States