title: Discrete event simulation: the preferred technique for health economic evaluations?
abstract: OBJECTIVE
  To argue that discrete event simulation should be preferred to cohort Markov models for economic evaluations in health care.
  
  
  METHODS
  The basis for the modeling techniques is reviewed. For many health-care decisions, existing data are insufficient to fully inform them, necessitating the use of modeling to estimate the consequences that are relevant to decision-makers. These models must reflect what is known about the problem at a level of detail sufficient to inform the questions. Oversimplification will result in estimates that are not only inaccurate, but potentially misleading.
  
  
  RESULTS
  Markov cohort models, though currently popular, have so many limitations and inherent assumptions that they are inadequate to inform most health-care decisions. An event-based individual simulation offers an alternative much better suited to the problem. A properly designed discrete event simulation provides more accurate, relevant estimates without being computationally prohibitive. It does require more data and may be a challenge to convey transparently, but these are necessary trade-offs to provide meaningful and valid results.
  
  
  CONCLUSIONS
  In our opinion, discrete event simulation should be the preferred technique for health economic evaluations today.
authors.affiliation: Department of Epidemiology, Biostatistics and Occupational Health, Division of General Internal Medicine, McGill University, Montreal, QC, Canada. jaime.caro@mcgill.ca
authors.forename: Jaime J
authors.initials: JJ
authors.lastname: Caro
authors.forename: Jörgen
authors.initials: J
authors.lastname: Möller
authors.forename: Denis
authors.initials: D
authors.lastname: Getsios
mesh_terms: D003362:Cost-Benefit Analysis / Q000379:methods; D003661:Decision Support Techniques; D017048:Health Care Costs; D006291:Health Policy / Q000191:economics; D006801:Humans; D008390:Markov Chains; D018803:Models, Economic; D015233:Models, Statistical