Cost Effectiveness of Digital Interventions for Generalised Anxiety Disorder: A Model-Based Analysis

数字干预治疗广泛性焦虑症的成本效益分析:基于模型的分析

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Abstract

BACKGROUND: Digital interventions (DIs) are increasingly being used in mental health care, despite limited evidence regarding their value for money. This study aimed to evaluate the cost effectiveness of DIs for generalised anxiety disorder (GAD), in comparison with alternative care options, from the perspective of the UK health care system. METHODS: An open-source decision analytic cohort model was used to extrapolate the results of a network meta-analysis over a patient's lifetime and estimate the costs and outcomes (quality-adjusted life-years) of DIs and their comparators. The net monetary benefit (NMB) and probability of cost effectiveness was estimated for each comparator, and we conducted a Value of Information analysis to evaluate the scale and drivers of uncertainty. RESULTS: DIs were associated with lower NMB compared with medication and with group therapy, but greater NMB compared with non-therapeutic controls and with usual care. DIs that were supported by a clinician, an assistant or a lay person had higher delivery costs than purely patient-self-directed DIs, yielding a greater NMB when opportunity cost was above £3000/QALY. There was considerable uncertainty in the findings driven largely by uncertainty in the estimated treatment effects. The value of further research to establish the effectiveness of DIs for GAD was substantial, at least £12.9 billion. CONCLUSIONS: The high uncertainty about these results does not allow for recommendations based on the cost effectiveness of DIs. However, the analysis highlights areas for future research, and demonstrates that apparent cost savings associated with DIs can be offset by reduced effectiveness.

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