An Open-Source Value Model for MDD
According to the National Alliance on Mental Illness, over 17 million Americans had at least one major depressive disorder (MDD) episode in the past year, and the COVID-19 pandemic has only highlighted the unmet need for access to depression treatment. Conventional cost-effectiveness models for assessing the value of treatments for MDD typically do not prioritize factors and outcomes important to patients nor feature, in their primary analysis, the societal perspectives relevant to this highly prevalent condition. In addition, current approaches may not fully address the decision-making needs of payers, employers and clinicians. As a laboratory for testing new methods and approaches to value assessment, IVI launched a multi-year initiative to build and test an open-source value assessment prototype model to facilitate evaluation of health interventions indicated for MDD.
Continuous Multi-Stakeholder Engagement
Work on this first-of-its-kind MDD model will test a novel approach in building value assessment tools, whereby a multi-stakeholder Advisory Group (AG) is engaged, from the outset and throughout the conceptualization and development process. The Advisory Group is comprised of diverse stakeholders, including patients, employers, payers, clinicians, researchers, and model developers. Their insights will help inform the model’s scope, development, validation, and application. Such an endeavor will also allow IVI to test how such an engagement approach can improve the credibility and relevance of the models.
IVI Principles for Model Development
IVI’s approach to building a prototype value assessment model to evaluate treatments for major depressive disorder emphasizes four key principles.
Patient-Centered. IVI is focused on rigorously incorporating patient-identified preferences and outcomes of importance into the model. Patients and patient advocacy organizations are primary and involved advisors to the project in addition to other stakeholders.
Collaborative. Defining the scope, inputs and purpose of the prototype model is informed by collaboration with an Advisory Group composed of diverse stakeholders, including patients, employers, payers, clinicians, researchers, and model developers.
Dynamic and Exploratory. In building this model, IVI is also considering alternative approaches to value assessment, like alternatives to QALY and multi-criteria decision analysis (MCDA), and novel elements of value. IVI is also exploring the ability to evaluate both pharmacological and non-pharmacological interventions for major depressive disorder.
Transparent. IVI will ensure an open and transparent process through preliminary publication and public comment periods related to the model protocol and draft model prototype, as well as open-source hosting of the model and all technical documentation and code on GitHub.
Get Involved
To learn more about this effort or inquire about how to get involved in this initiative, complete the contact form below or e-mail Erica Malik at erica.malik@thevalueinitiative.org.

There’s an enormous amount of interest among decision makers whether they’re payers or employers at really understanding value and the cost benefit balance.
Selected References
The following is a partial list of some of the literature on open-source value models and major depressive disorder.
Open-Source Models
- Jansen, J.P., Incerti, D. & Linthicum, M. Developing Open-Source Models for the US Health System: Practical Experiences and Challenges to Date with the Open-Source Value Project. PharmacoEconomics 37, 1313–1320 (2019). https://doi.org/10.1007/s40273-019-00827-z
- Incerti, D., Curtis, J.R., Shafrin, J. et al. A Flexible Open-Source Decision Model for Value Assessment of Biologic Treatment for Rheumatoid Arthritis. PharmacoEconomics 37, 829–843 (2019). https://doi.org/10.1007/s40273-018-00765-2
Major Depressive Disorder
- Armstrong EP, Skrepnek GH, Haim Erder M. Cost-utility comparison of escitalopram and sertraline in the treatment of major depressive disorder. Current Medical Research and Opinion. 2007;23(2):251–8. doi:10.1185/030079907×159498. https://pubmed.ncbi.nlm.nih.gov/17288678/
- Birnbaum, H. G., Kessler, R. C., Kelley, D., Ben-Hamadi, R., Joish, V.N., & Greenberg, P. E. (2010). Employer burden of mild, moderate, and severe major depressive disorder: Mental health services utilization and costs, and work performance. Depression and Anxiety, 27, 78–89. https://pubmed.ncbi.nlm.nih.gov/19569060/
- Ceskova E, Silhan P. Novel treatment options in depression and psychosis. Neuropsychiatric Disease and Treatment. 2018;14:741-747. Published 2018 Mar 13. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5856289/
- Greenberg, P. E., Fournier, A.-A., Sisitsky, T., Pike, C. T., & Kessler, R. C. (2015). The economic burden of adults with major depressive disorder in the United States (2005 and 2010). The Journal of Clinical Psychiatry, 76(2), 155–162. https://pubmed.ncbi.nlm.nih.gov/25742202/
- Hasin DS, Sarvet AL, Meyers JL, Saha TD, Ruan WJ, Stohl M, Grant BF. (2018). Epidemiology of adult DSM-5 major depressive disorder and its specifiers in the United States. Journal of the American Medical Association: Psychiatry, 75(4), 336-346. https://jamanetwork.com/journals/jamapsychiatry/fullarticle/2671413
- Kolovos S, Bosmans JE, Riper H, Chevreul K, Coupé VMH, van Tulder MW. Model-Based Economic Evaluation of Treatments for Depression: A Systematic Literature Review. PharmacoEconomics Open. 2017;1(3):149-165.https://pubmed.ncbi.nlm.nih.gov/29441493/
- Mrazek DA, Hornberger JC, Altar CA, Degtiar I. A review of the clinical, economic, and societal burden of treatment-resistant depression: 1996–2013. Psychiatric Services. 2014 Aug;65(8):977-87 https://pubmed.ncbi.nlm.nih.gov/24789696/
- NAMI: Overview of Major Depression https://www.nami.org/About-Mental-Illness/Mental-Health-Conditions/Depression/Overview
- National Institute of Mental Health (NIMH). Major Depression 2017 [Available from: https://www.nimh.nih.gov/health/statistics/major-depression.shtml.]
- Prukkanone, Benjamas et al. Cost-Effectiveness Analysis for Antidepressants and Cognitive Behavioral Therapy for Major Depression in Thailand. Value in Health, Volume 15, Issue 1, S3 – S8 https://pubmed.ncbi.nlm.nih.gov/22265064/
- Ramsey SD, Wilke RJ, Briggs AH, et al. Good research practices for cost-effectiveness analysis alongside clinical trials: the ISPOR RCT-CEA Task Force Report. Value Health. 2005; 8(5):521-533. https://pubmed.ncbi.nlm.nih.gov/16176491/
- Sanders GD, Maciejewski ML, Basu A. Overview of Cost-effectiveness Analysis. Journal of the American Medical Association. 2019;321(14):1400–1401. https://pubmed.ncbi.nlm.nih.gov/30855638/
- Sobocki P, Ekman M, Agren H, Jonsson B, Rehnberg C. Model to assess the cost-effectiveness of new treatments for depression. International Journal of Technology Assessment in Health Care. 2006;22(4):469–77. https://pubmed.ncbi.nlm.nih.gov/16984680/
- Gibson, Teresa et al. “Cost burden of treatment resistance in patients with depression.” American Journal of Managed Care, 16.5 (2010): 370-377. https://www.ajmc.com/journals/issue/2010/2010-05-vol16-n05/ajmc_10may_gibson_370to377