Core discrete event simulation model for the evaluation of health care technologies in major depressive disorder

  1. Vataire, A.-L. 2
  2. Aballéa, S. 2
  3. Antonanzas, F. 6
  4. Roijen, L.H.-V. 1
  5. Lam, R.W. 5
  6. McCrone, P. 3
  7. Persson, U. 4
  8. Toumi, M. 7
  1. 1 Erasmus University Rotterdam
    info

    Erasmus University Rotterdam

    Róterdam, Holanda

    ROR https://ror.org/057w15z03

  2. 2 Health Economics and Outcomes Research, Creativ-Ceutical, 215 rue du Faubourg Saint-Honoré, Paris 75008, France
  3. 3 King's College London
    info

    King's College London

    Londres, Reino Unido

    ROR https://ror.org/0220mzb33

  4. 4 Swedish Institute for Health Economics
    info

    Swedish Institute for Health Economics

    Lund, Suecia

    ROR https://ror.org/01nfdxd69

  5. 5 University of British Columbia
    info

    University of British Columbia

    Vancouver, Canadá

    ROR https://ror.org/03rmrcq20

  6. 6 Universidad de La Rioja
    info

    Universidad de La Rioja

    Logroño, España

    ROR https://ror.org/0553yr311

  7. 7 University of Lyon System
    info

    University of Lyon System

    Lyon, Francia

    ROR https://ror.org/01rk35k63

Revista:
Value in Health

ISSN: 1098-3015

Año de publicación: 2014

Volumen: 17

Número: 2

Páginas: 183-195

Tipo: Artículo

DOI: 10.1016/J.JVAL.2013.11.012 SCOPUS: 2-s2.0-84896385732 WoS: WOS:000333346600005 GOOGLE SCHOLAR

Otras publicaciones en: Value in Health

Repositorio institucional: lock_openAcceso abierto Editor

Resumen

Objective A review of existing economic models in major depressive disorder (MDD) highlighted the need for models with longer time horizons that also account for heterogeneity in treatment pathways between patients. A core discrete event simulation model was developed to estimate health and cost outcomes associated with alternative treatment strategies. Methods This model simulated short- and long-term clinical events (partial response, remission, relapse, recovery, and recurrence), adverse events, and treatment changes (titration, switch, addition, and discontinuation) over up to 5 years. Several treatment pathways were defined on the basis of fictitious antidepressants with three levels of efficacy, tolerability, and price (low, medium, and high) from first line to third line. The model was populated with input data from the literature for the UK setting. Model outputs include time in different health states, quality-adjusted life-years (QALYs), and costs from National Health Service and societal perspectives. The codes are open source. Results Predicted costs and QALYs from this model are within the range of results from previous economic evaluations. The largest cost components from the payer perspective were physician visits and hospitalizations. Key parameters driving the predicted costs and QALYs were utility values, effectiveness, and frequency of physician visits. Differences in QALYs and costs between two strategies with different effectiveness increased approximately twofold when the time horizon increased from 1 to 5 years. Conclusion The discrete event simulation model can provide a more comprehensive evaluation of different therapeutic options in MDD, compared with existing Markov models, and can be used to compare a wide range of health care technologies in various groups of patients with MDD. © 2014 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc.