title: Monte Carlo simulation of the cost-effectiveness of sample size maintenance programs revealed the need to consider substitution sampling.
abstract: OBJECTIVE
  To assess the cost-effectiveness of sample size maintenance programs in a prospective cohort.
  
  
  METHODS
  The Living with Diabetes Study in Queensland, Australia is a longitudinal survey providing a comprehensive examination of health care utilization and disease progression among people with diabetes. Data from this study were used to compare the cost-effectiveness of a program incorporating substitution sampling with two alternative programs: "no follow-up" and "usual practice."
  
  
  RESULTS
  A program involving substitution sampling was shown to be the most effective with an additional 3,556 complete responses (compared with a "no follow-up" program) and an additional 2,099 complete responses (compared with "usual practice"). An incremental analysis through a Monte Carlo simulation found substitution sampling to be the most cost-effective option for maintaining sample size with an incremental cost-effective ratio of $54.87 (95% uncertainty interval $52.68-$57.25) compared with $87.58 ($77.89-$100.09) for "usual practice."
  
  
  CONCLUSIONS
  Based on the available data, a program involving substitution sampling is economically justified and should be considered in any approach with the aim of maintaining sample size. There is, however, a continuing need to evaluate the effectiveness of this option on other outcome measures, such as bias.
authors.affiliation: School of Population Health, The University of Queensland, Herston, Queensland 4006, Australia. michael.david@uqconnect.edu.au
authors.forename: Michael C
authors.initials: MC
authors.lastname: David
authors.forename: Mark
authors.initials: M
authors.lastname: Bensink
authors.forename: Hideki
authors.initials: H
authors.lastname: Higashi
authors.forename: Maria
authors.initials: M
authors.lastname: Donald
authors.forename: Rosa
authors.initials: R
authors.lastname: Alati
authors.forename: Robert S
authors.initials: RS
authors.lastname: Ware
mesh_terms: D003362:Cost-Benefit Analysis; D003663:Decision Trees; D003920:Diabetes Mellitus / Q000453:epidemiology; D018450:Disease Progression; D019538:Health Care Surveys / Q000191:economics* / Q000379:methods; D006296:Health Services / Q000706:statistics & numerical data; D006801:Humans; D009010:Monte Carlo Method; D010352:Patient Dropouts / Q000706:statistics & numerical data; D011446:Prospective Studies; D011793:Queensland / Q000453:epidemiology; D017010:Reminder Systems / Q000191:economics; D018401:Sample Size; D015983:Selection Bias