Since the turn of the millennium, considerable progress has been made in developing an evidence base on which interventions are effective and feasible for improving mental health in low- and middle-income countries (LMICs). Such evidence provides a critical input to the formulation of plans and priorities to address the large and growing burden of mental, neurological, and substance use (MNS) disorders. However, for successful and sustainable scale-up of effective interventions and innovative service delivery strategies, decision makers require not only evidence of an intervention’s impact on health and other outcomes, such as equity or poverty, but also evidence of its cost and cost-effectiveness. Cost data provide information relevant to the financial planning and implementation of prioritized, evidence-based strategies; cost-effectiveness analysis indicates the relative efficiency or value for money associated with interventions or innovations. The application of economic evaluation to MNS disorders has largely focused on the assessment of a specific intervention’s costs and health outcomes, relative to some comparator, which may be treatment as usual, another innovation, or no intervention. Such assessments have often been conducted alongside clinical trials, enabling health economic researchers to add resource use questions to study protocols, generate estimates of each trial participant’s health care costs, and relate these costs to primary outcome measures in the form of cost-effectiveness ratios. We review this type of economic evidence over the course of this chapter, with a particular focus on studies that have been successfully carried out in LMICs. However, the number of completed studies remains small and insufficient to inform resource allocation decisions in all the national settings where cost-effectiveness information would be valuable, including the many countries where informal or traditional health care represents the predominant model of service availability. This paucity of economic evidence reflects the overall lack of resources and infrastructure for mental health services in LMICs, including research capacity. Partly to address the paucity of cost-effectiveness trials, as well as their intrinsic specificity to the setting in which they are conducted, a broader, modeling-based approach has also been used to build up economic evidence for international mental health policy and planning. This approach includes the earlier editions of the Disease Control Priorities (DCP) project and the World Health Organization’s (WHO) CHOosing Interventions that are Cost-Effective (CHOICE) project. Such model-based studies rely on existing data, as well as several analytical assumptions; these studies have adopted an epidemiological, population-based approach that identifies the expected costs and health impacts of delivering evidence-based interventions at scale in the population as a whole, whether a specific country or an entire region. We also review this form of economic evidence and comment on important gaps in the current evidence base, as well as the relative strengths and limitations of this approach. One important limitation of conventional cost-effectiveness analysis—whether garnered through trial-based or model-based approaches—is that it is restricted to consideration of the specific implementation costs and health-related outcomes of an intervention; it does not typically extend to the nonhealth or wider economic or social value of investing in mental health innovation and service scale-up. In particular, cost-effectiveness analysis in its conventional form has little to say about the equitable distribution of costs and health gains across different groups of the target population. Incorporation of such concerns into economic evaluation represents a major objective of extended cost-effectiveness analysis, which is explored and addressed specifically in chapter 13 in this volume (Chisholm, Johansson, and others 2015). In this chapter, we review the available cost-effectiveness evidence for the different levels and underpinning strategies of the mental health care system, with a focus on information generated in or for LMICs. Based on the overall analytical framework and priority intervention matrices developed for this volume, the remainder of the chapter is presented as follows. First, we consider the economic evidence for mental health prevention and protection at the population and community levels of the health and welfare system, including legislative, regulatory, and informational measures at the public policy level (population platform), as well as school-, workplace-, and community-based programs (community platform). We then examine the economic evidence relating to the identification and treatment of MNS disorders (health care platform), focusing on the relative cost-effectiveness or efficiency of treatment programs implemented in nonspecialized versus more specialized health care settings. Finally, we assess the financial costs and budgetary implications of implementing or scaling up a set of prioritized, cost-effective interventions. Our review is based on available, published literature. A systematic search of the literature for LMICs was undertaken in PubMed to find articles published since 2000 in English. The search combined terms for specific mental health interventions with economic terms such as “cost,” “cost-effectiveness,” or “quality-adjusted life year (QALY),” as well as the names of all LMICs and their respective regions (see annex 12A for a list of search terms used to identify relevant literature). Where little or no literature was found for LMICs on interventions of potential importance, this systematic search was augmented by selective searches of the literature available since 1995 for high-income countries (HICs); however, these results are not included in the figures or tables. Annex 12B provides the search statistics. Articles included in the review were graded using the checklist of Drummond and others (2005) to generate a quality score for each article, with most studies graded between 7 and 10. Annex 12C provides a list of studies that were used to generate the tables and figures presented in this chapter. It presents detailed information on the intervention characteristics and comparators, target population group, geographic location, methodology, results, and quality scores. All cost-effectiveness results are presented in 2012 US$ except where noted otherwise. Consistent with earlier iterations of DCP, reported regional estimates refer to the World Bank’s categorization of countries by income.
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