Economic threshold analysis of delivering a task-sharing treatment for common mental disorders at scale: the Friendship Bench, Zimbabwe.

Andrew Healey ORCID logo; RuthVerhey; Iris Mosweu ORCID logo; JanetBoadu; Dixon Chibanda ORCID logo; CharmaineChitiyo; BradWagenaar; Hugo Senra ORCID logo; EphraimChiriseri; SandraMboweni; +1 more... RicardoAraya; (2021) Economic threshold analysis of delivering a task-sharing treatment for common mental disorders at scale: the Friendship Bench, Zimbabwe. Evidence-based mental health, 25 (2). pp. 47-53. ISSN 1362-0347 DOI: 10.1136/ebmental-2021-300317
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BACKGROUND: Task-sharing treatment approaches offer a pragmatic approach to treating common mental disorders in low-income and middle-income countries (LMICs). The Friendship Bench (FB), developed in Zimbabwe with increasing adoption in other LMICs, is one example of this type of treatment model using lay health workers (LHWs) to deliver treatment. OBJECTIVE: To consider the level of treatment coverage required for a recent scale-up of the FB in Zimbabwe to be considered cost-effective. METHODS: A modelling-based deterministic threshold analysis conducted within a 'cost-utility' framework using a recommended cost-effectiveness threshold. FINDINGS: The FB would need to treat an additional 3413 service users (10 per active LHW per year) for its scale-up to be considered cost-effective. This assumes a level of treatment effect observed under clinical trial conditions. The associated incremental cost-effectiveness ratio was $191 per year lived with disability avoided, assuming treatment coverage levels reported during 2020. The required treatment coverage for a cost-effective outcome is within the level of treatment coverage observed during 2020 and remained so even when assuming significantly compromised levels of treatment effect. CONCLUSIONS: The economic case for a scaled-up delivery of the FB appears convincing in principle and its adoption at scale in LMIC settings should be given serious consideration. CLINICAL IMPLICATIONS: Further evidence on the types of scale-up strategies that are likely to offer an effective and cost-effective means of sustaining required levels of treatment coverage will help focus efforts on approaches to scale-up that optimise resources invested in task-sharing programmes.



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