The “ComPAS” trial combined treatment model for acute malnutrition: study protocol for the economic evaluation

Acute malnutrition is currently divided into severe (SAM) and moderate (MAM), based on level of wasting. SAM and MAM currently have separate treatment protocols and products, managed by separate international agencies. For SAM, the dose of treatment is allocated by the child’s weight. A combined and simplified protocol for SAM and MAM, with a standardised dose of ready-to-use therapeutic food (RUTF), is being trialled for non-inferior recovery rates and may be more cost-effective than the current standard protocols for treating SAM and MAM.

This paper describes the protocol for the economic evaluation of the ComPAS trial, a cluster-randomised controlled, non-inferiority trial² that took place between May 2017 and July 2018. It compared a novel combined protocol for treating uncomplicated acute malnutrition to the current standard protocol in children age 6 to 59 months in South Sudan and Kenya. This study will calculate the total economic costs of both protocols from a societal perspective, using accounting data, interviews and survey questionnaires. The incremental cost of implementing the combined protocol will be estimated and all costs and outcomes will be presented as a cost-consequence analysis. Incremental cost-effectiveness ratio will be calculated for primary and secondary outcome, if statistically significant.

The authors hypothesise that implementing the combined protocol will be cost-effective due to streamlined logistics at clinic level, reduced length of treatment (especially for MAM) and reduced dosages of RUTF. The findings of this economic evaluation will be important for policy-makers, especially given the hypothesised non-inferiority of the main health outcomes. The publication of this protocol aims to improve rigour of conduct and transparency of data collection and analysis. It is also intended to promote inclusion of economic evaluation in other nutrition intervention studies, especially for MAM, and improve comparability with other studies.

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