Centre for Economic Evaluation and Machine Learning, Department of Public Mental Health, Trimbos Institute (Netherlands Institute of Mental Health and Addiction), Utrecht, The Netherlands.
Department of Clinical Epidemiology and Medical Technology Assessment, Maastricht University Medical Centre+, Maastricht, The Netherlands.
Expert Rev Pharmacoecon Outcomes Res. 2021 Oct;21(5):1031-1042. doi: 10.1080/14737167.2021.1844566. Epub 2020 Nov 23.
: 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.: 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.: 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.: 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.
描述“DepMod”的设计，这是一个健康经济学的 Markov 模型，用于评估针对抑郁障碍的用户定义的预防干预措施和治疗方案的成本效益和预算影响。DepMod 具有描述人群如何在健康状态之间（阈下抑郁、轻度、中度或重度抑郁（部分）缓解、复发、死亡）进行转变的流行病学层。在流行病学层之上，DepMod 具有干预层，由参考情景和替代情景组成，比较用户定义的预防干预措施和抑郁症的心理和药物治疗方案的有效性和成本效益。结果以获得的质量调整生命年（QALY）和医疗保健支出表示。成本和效果可以在 5 年内建模，并进行概率敏感性分析。DepMod 用于评估扩大预防干预措施治疗亚临床抑郁患者的成本效益，结果表明，在每 QALY 支付 20,000 欧元的意愿支付阈值下，扩大预防措施具有 82%的成本效益的可能性。DepMod 是一个 Markov 模型，评估了针对预防和治疗抑郁的不同医疗保健方案的成本效益和预算影响，可根据要求免费提供给学术界使用。
