title: Budget impact analysis of thrombolysis for stroke in Spain: a discrete event simulation model.
abstract: OBJECTIVE
  Thrombolysis within the first 3 hours after the onset of symptoms of a stroke has been shown to be a cost-effective treatment because treated patients are 30% more likely than nontreated patients to have no residual disability. The objective of this study was to calculate by means of a discrete event simulation model the budget impact of thrombolysis in Spain.
  
  
  METHODS
  The budget impact analysis was based on stroke incidence rates and the estimation of the prevalence of stroke-related disability in Spain and its translation to hospital and social costs. A discrete event simulation model was constructed to represent the flow of patients with stroke in Spain.
  
  
  RESULTS
  If 10% of patients with stroke from 2000 to 2015 would receive thrombolytic treatment, the prevalence of dependent patients in 2015 would decrease from 149,953 to 145,922. For the first 6 years, the cost of intervention would surpass the savings. Nevertheless, the number of cases in which patient dependency was avoided would steadily increase, and after 2006 the cost savings would be greater, with a widening difference between the cost of intervention and the cost of nonintervention, until 2015.
  
  
  CONCLUSIONS
  The impact of thrombolysis on society's health and social budget indicates a net benefit after 6 years, and the improvement in health grows continuously. The validation of the model demonstrates the adequacy of the discrete event simulation approach in representing the epidemiology of stroke to calculate the budget impact.
authors.affiliation: Clinical Management Unit, Hospital Alto Deba, Mondragón, Spain. javier.marmedina@osakidetza.net
authors.forename: Javier
authors.initials: J
authors.lastname: Mar
authors.forename: Arantzazu
authors.initials: A
authors.lastname: Arrospide
authors.forename: Mercè
authors.initials: M
authors.lastname: Comas
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D017281:Cost of Illness; D003362:Cost-Benefit Analysis; D005260:Female; D006801:Humans; D015994:Incidence; D008297:Male; D008390:Markov Chains; D008875:Middle Aged; D017059:Models, Econometric; D015995:Prevalence; D013030:Spain / Q000453:epidemiology; D020521:Stroke / Q000188:drug therapy / Q000191:economics* / Q000453:epidemiology; D015912:Thrombolytic Therapy / Q000191:economics*; D013997:Time Factors; D055815:Young Adult