title: Practical implications of differential discounting in cost-effectiveness analyses with varying numbers of cohorts.
abstract: OBJECTIVE
  To call attention to the influence of the number of birth-cohorts used in cost-effectiveness analysis (CEA) models on incremental cost-effectiveness ratios (ICERs) under differential discounting.
  
  
  METHODS
  The consequences of increasing the number of birth-cohorts are demonstrated using a CEA of cervical cancer prevention as an example. The cost-effectiveness of vaccinating 12-year-old girls against the human papillomavirus is estimated with the MISCAN microsimulation screening analysis model for 1, 10, 20, and 30 birth-cohorts. Costs and health effects are discounted with equal rates of 4% and alternatively with differential rates of 4% and 1.5% respectively. The effects of increasing the number of cohorts are shown by comparing the ICERs under equal and differential discounting.
  
  
  RESULTS
  The ICER decreases as the number of cohorts increases under differential discounting, but not under equal discounting.
  
  
  CONCLUSIONS
  The variation of ICERs with the number of cohorts under differential discounting prompts questions regarding the appropriate specification of CEA models and interpretation of their results. In particular, it raises concerns that arbitrary variation in study specification leads to arbitrary variation in results. Such variations could lead to erroneous policy decisions. These findings are relevant to CEA guidance authorities, CEA practitioners, and decision makers. Our results do not imply a problem with differential discounting per se, yet they highlight the need for practical guidance for its use.
authors.affiliation: Department of Public Health, Erasmus University Medical Centre, Rotterdam, The Netherlands. j.omahony@erasmusmc.nl
authors.forename: James F
authors.initials: JF
authors.lastname: O'Mahony
authors.forename: Inge M C M
authors.initials: IM
authors.lastname: de Kok
authors.forename: Joost
authors.initials: J
authors.lastname: van Rosmalen
authors.forename: J Dik F
authors.initials: JD
authors.lastname: Habbema
authors.forename: Werner
authors.initials: W
authors.lastname: Brouwer
authors.forename: Marjolein
authors.initials: M
authors.lastname: van Ballegooijen
mesh_terms: D000293:Adolescent; D000328:Adult; D000367:Age Factors; D000368:Aged; D002648:Child; D015988:Cohort Effect; D003362:Cost-Benefit Analysis / Q000191:economics / Q000379:methods; D005260:Female; D006801:Humans; D008875:Middle Aged; D015233:Models, Statistical; D053918:Papillomavirus Vaccines / Q000191:economics* / Q000627:therapeutic use; D002583:Uterine Cervical Neoplasms / Q000191:economics* / Q000453:epidemiology* / Q000517:prevention & control; D055815:Young Adult
chemical_list: D053918:Papillomavirus Vaccines