title: Discretely Integrated Condition Event (DICE) Simulation for Pharmacoeconomics.
abstract: Several decision-analytic modeling techniques are in use for pharmacoeconomic analyses. Discretely integrated condition event (DICE) simulation is proposed as a unifying approach that has been deliberately designed to meet the modeling requirements in a straightforward transparent way, without forcing assumptions (e.g., only one transition per cycle) or unnecessary complexity. At the core of DICE are conditions that represent aspects that persist over time. They have levels that can change and many may coexist. Events reflect instantaneous occurrences that may modify some conditions or the timing of other events. The conditions are discretely integrated with events by updating their levels at those times. Profiles of determinant values allow for differences among patients in the predictors of the disease course. Any number of valuations (e.g., utility, cost, willingness-to-pay) of conditions and events can be applied concurrently in a single run. A DICE model is conveniently specified in a series of tables that follow a consistent format and the simulation can be implemented fully in MS Excel, facilitating review and validation. DICE incorporates both state-transition (Markov) models and non-resource-constrained discrete event simulation in a single formulation; it can be executed as a cohort or a microsimulation; and deterministically or stochastically.
authors.affiliation: McGill University, Montreal, Canada. jaime.caro@mcgill.ca.|Evidera, Boston, MA, USA. jaime.caro@mcgill.ca.|, 39 Bypass Rd, Lincoln, MA, 01773, USA. jaime.caro@mcgill.ca.
authors.forename: J Jaime
authors.identifier: 0000-0001-5470-3754
authors.initials: JJ
authors.lastname: Caro
mesh_terms: D003198:Computer Simulation; D003661:Decision Support Techniques; D017850:Economics, Pharmaceutical; D006801:Humans; D008390:Markov Chains; D008962:Models, Theoretical; D013997:Time Factors