TY - JOUR
T1 - Design of a health-economic Markov model to assess cost-effectiveness and budget impact of the prevention and treatment of depressive disorder
AU - Lokkerbol, Joran
AU - Wijnen, Ben
AU - Ruhe, Henricus G.
AU - Spijker, Jan
AU - Morad, Arshia
AU - Schoevers, Robert
AU - de Boer, Marrit K.
AU - Cuijpers, Pim
AU - Smit, Filip
N1 - Funding Information: Development of DepMod was financially supported by The Netherlands Organisation for Health Research and Development (ZonMW), grant 50-50110-96-634. An earlier version was supported by the Netherlands? Ministry of Health (VWS). Joran Lokkerbol was supported by The Netherlands Organisation for Health Research and Development (ZonMw) Mental Healthcare Fellowship, grant #636320003. We acknowledge dr. Talitha Feenstra, prof. dr. Claudi Bockting, and the taskforce for the development of the Dutch Multidisciplinary Guideline for Depression for constructive comments on early drafts of this manuscript. Publisher Copyright: © 2020 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
PY - 2021
Y1 - 2021
N2 - Background/objective: To describe the design of ‘DepMod,’ a health-economic Markov model for assessing cost-effectiveness and budget impact of user-defined preventive interventions and treatments in depressive disorders. Methods: DepMod has an epidemiological layer describing how a cohort of people can transition between health states (sub-threshold depression, first episode of mild, moderate or severe depression (partial) remission, recurrence, death). Superimposed on the epidemiological layer, DepMod has an intervention layer consisting of a reference scenario and alternative scenario comparing the effectiveness and cost-effectiveness of a user-defined package of preventive interventions and psychological and pharmacological treatments of depression. Results are presented in terms of quality-adjusted life years (QALYs) gained and healthcare expenditure. Costs and effects can be modeled over 5 years and are subjected to probabilistic sensitivity analysis. Results: DepMod was used to assess the cost-effectiveness of scaling up preventive interventions for treating people with subclinical depression, which showed that there is an 82% probability that scaling up prevention is cost-effective given a willingness-to-pay threshold of €20,000 per QALY. Conclusion: DepMod is a Markov model that assesses the cost-utility and budget impact of different healthcare packages aimed at preventing and treating depression and is freely available for academic purposes upon request at the authors.
AB - Background/objective: To describe the design of ‘DepMod,’ a health-economic Markov model for assessing cost-effectiveness and budget impact of user-defined preventive interventions and treatments in depressive disorders. Methods: DepMod has an epidemiological layer describing how a cohort of people can transition between health states (sub-threshold depression, first episode of mild, moderate or severe depression (partial) remission, recurrence, death). Superimposed on the epidemiological layer, DepMod has an intervention layer consisting of a reference scenario and alternative scenario comparing the effectiveness and cost-effectiveness of a user-defined package of preventive interventions and psychological and pharmacological treatments of depression. Results are presented in terms of quality-adjusted life years (QALYs) gained and healthcare expenditure. Costs and effects can be modeled over 5 years and are subjected to probabilistic sensitivity analysis. Results: DepMod was used to assess the cost-effectiveness of scaling up preventive interventions for treating people with subclinical depression, which showed that there is an 82% probability that scaling up prevention is cost-effective given a willingness-to-pay threshold of €20,000 per QALY. Conclusion: DepMod is a Markov model that assesses the cost-utility and budget impact of different healthcare packages aimed at preventing and treating depression and is freely available for academic purposes upon request at the authors.
KW - Cost-effectiveness
KW - budget impact
KW - depression
KW - health-economic modeling
KW - major depressive disorder
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U2 - https://doi.org/10.1080/14737167.2021.1844566
DO - https://doi.org/10.1080/14737167.2021.1844566
M3 - Article
C2 - 33119427
SN - 1473-7167
VL - 21
SP - 1031
EP - 1042
JO - Expert Review of Pharmacoeconomics and Outcomes Research
JF - Expert Review of Pharmacoeconomics and Outcomes Research
IS - 5
ER -