Implementation strategies to build mental health-care capacity in Malawi: a health-economic evaluation

Abstract

Background: Depression is a major contributor to morbidity and mortality in sub-Saharan Africa. Due to low system capacity, three in four patients with depression in sub-Saharan Africa go untreated. Despite this, little attention has been paid to the cost-effectiveness of implementation strategies to scale up evidence-based depression treatment in the region. In this study, we investigate the cost-effectiveness of two different implementation strategies to integrate the Friendship Bench approach and measurement-based care in non-communicable disease clinics in Malawi.

Methods: The two implementation strategies tested in this study are part of a trial, in which ten clinics were randomly assigned (1:1) to a basic implementation package consisting of an internal coordinator acting as a champion (IC-only group) or to an enhanced package that complemented the basic package with quarterly external supervision, and audit and feedback of intervention delivery (IC + ES group). We included material costs, training costs, costs related to project-wide meetings, transportation and medication costs, time costs related to internal champion activities and depression screening or treatment, and costs of external supervision visits if applicable. Outcomes included the number of patients screened with the patient health questionnaire 2 (PHQ-2), cases of remitted depression at 3 and 12 months, and disability-adjusted life-years (DALYs) averted. We compared the cost-effectiveness of both packages to the status quo (ie, no intervention) using a micro-costing-informed decision-tree model.

Findings: Relative to the status quo, IC + ES would be on average US$10 387 ($1349-$17 365) more expensive than IC-only but more effective in achieving remission and averting DALYs. The cost per additional remission would also be lower with IC + ES than IC-only at 3 months ($119 vs $223) and 12 months ($210 for IC + ES; IC-only dominated by the status quo at 12 months). Neither package would be cost-effective under the willingness-to-pay threshold of $65 per DALY averted currently used by the Malawian Ministry of Health. However, the IC + ES package would be cost-effective in relation to the commonly used threshold of three times per-capita gross domestic product per DALY averted.

Interpretation: Investing in supporting champions might be an appropriate use of resources. Although not currently cost-effective by Malawian willingness-to-pay standards compared with the status quo, the IC + ES package would probably be a cost-effective way to build mental health-care capacity in resource-constrained settings in which decision makers use higher willingness-to-pay thresholds.

Funding: National Institute of Mental Health.

Figure 1:. Clinical care flow for treatment-naive clinic visits

The diagram describes the clinical care workflow for patients who have not previously started treatment for depression (ie, they represent new visits for treatment-naive patients with depression attending the non-communicable disease clinic and exclude return visits). IC-only represents the treatment package consisting of internal champions only, whereas IC + ES represents the treatment package consisting of internal champions plus external supervision. The decision node (depicted by a black square) represents the decision (ie, controllable factor) to implement depression screening and treatment using either implementation package (IC-only or IC + ES). Event nodes (black circles) indicate the presence of alternatives that can occur by chance (eg, the probability that a patient screens positive on the PHQ-2 or the probability that the PHQ-9 is administered after a positive PHQ-2, as per protocol). PHQ=Patient Health Questionnaire.

Figure 2:. Cost inputs and outcomes by scenario

The figure shows the cost and outcome-related inputs that were used for each of the scenarios modelled (ie, status quo, IC-only, and IC + ES). Material costs, training costs, costs related to project-wide meetings and internal champion activities, and transportation costs (as well as external supervision costs in the IC + ES alternative) were considered to be fixed costs (ie, cost associated with the scale-up to the selected 14 districts, independent of the number of patients seen). Treatment costs (which do depend on the number of patients seen) were calculated by summing the costs accrued by the cohort while moving through different alternatives of the clinical care decision tree depicted in figure 1. IC-only represents the treatment package consisting of internal champions only, whereas IC + ES represents the treatment package consisting of internal champions plus external supervision. Outcomes were also calculated using the clinical care decision tree depicted in figure 1. NCD=non-communicable disease. DALY=disability-adjusted life-year.

Figure 3:. Cost-effectiveness acceptability curves for outcomes of interest

Cost-effectiveness acceptability curves are constructed using the net monetary benefit approach. For each of the 1000 simulations, the net monetary benefit is calculated for a range of willingness-to-pay thresholds. Then, the percentage of simulations with a positive net monetary benefit under each threshold (ie, cost-effective in relation to each threshold) is calculated, allowing for a direct comparison of the cost-effectiveness of IC-only and IC + ES alternatives in relation to the status quo. IC-only represents the implementation package consisting of internal champions only, whereas IC + ES represents the implementation package consisting of internal champions plus external supervision. For the incremental costs per DALY averted, the vertical lines represent different willingness-to-pay thresholds: $65 (used by the Ministry of Health in Malawi) and one to three times per-capita GDP (which is commonly used in the LMIC cost-effectiveness literature). One time Malawian per-capita GDP in 2019 was $584·4, two times was $1168·8, and three times was $1753·2. GDP=gross domestic product. GDPPC=GDP per capita. LMIC=low-income and middle-income countries.