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PharmacoEconomics

, Volume 30, Issue 6, pp 461–482 | Cite as

A Critical Review of Model-Based Economic Studies of Depression

Modelling Techniques, Model Structure and Data Sources
  • Hossein Haji Ali AfzaliEmail author
  • Jonathan Karnon
  • Jodi Gray
Review Article

Abstract

Depression is the most common mental health disorder and is recognized as a chronic disease characterized by multiple acute episodes/relapses. Although modelling techniques play an increasingly important role in the economic evaluation of depression interventions, comparatively little attention has been paid to issues around modelling studies with a focus on potential biases. This, however, is important as different modelling approaches, variations in model structure and input parameters may produce different results, and hence different policy decisions.

This paper presents a critical review of literature on recently published model-based cost-utility studies of depression. Taking depression as an illustrative example, through this review, we discuss a number of specific issues in relation to the use of decision-analytic models including the type of modelling techniques, structure of models and data sources.

The potential benefits and limitations of each modelling technique are discussed and factors influencing the choice of modelling techniques are addressed. This review found that model-based studies of depression used various simulation techniques. We note that a discrete-event simulation may be the preferred technique for the economic evaluation of depression due to the greater flexibility with respect to handling time compared with other individual-based modelling techniques.

Considering prognosis and management of depression, the structure of the reviewed models are discussed. We argue that a few reviewed models did not include some important structural aspects such as the possibility of relapse or the increased risk of suicide in patients with depression. Finally, the appropriateness of data sources used to estimate input parameters with a focus on transition probabilities is addressed. We argue that the above issues can potentially bias results and reduce the comparability of economic evaluations.

Keywords

Time Horizon Venlafaxine Depressive Episode Duloxetine Escitalopram 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

The authors have no conflicts of interest that are directly relevant to the content of this article. The opinions expressed in this article are those of the authors.

HH designed the study, performed the critical review of studies, and drafted the manuscript. JK revised the manuscript and contributed to the design, review of studies and discussion. JG undertook the search, and helped to revise the manuscript. All authors read and approved the final manuscript. HH is the guarantor for the overall content of this article, and HH and JK had the idea for the article.

This research would not have been possible without the financial support of the Australian Research Council and the South Australia Department of Health. The authors also thank Justin Beilby, Chris Holton, Adam Elshaug, Barbara Magin, David Banham, Michelle Noort, Wendy Sutton and Adair Garrett for their recommendations.

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Copyright information

© Springer International Publishing AG 2012

Authors and Affiliations

  • Hossein Haji Ali Afzali
    • 1
    Email author
  • Jonathan Karnon
    • 1
  • Jodi Gray
    • 1
  1. 1.Discipline of Public HealthThe University of AdelaideAdelaideAustralia

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