Introduction to Use of health impact metrics for programmatic decision making in global health

Abstract

Over the past twenty years, the international landscape for health programming in developing countries has changed dramatically, and global awareness of the consequences of poor health has grown. One result is the international commitment to the Millennium Development Goals (MDGs) that has put poverty reduction and health at the forefront of the global agenda. And, as new funding agencies and mechanisms (e.g., GFATM, GAVI, PEPFAR, PMI) appeared, attention focused more closely on the impact of their expenditures. Major donors - multilateral, bilateral and private - have embraced ‘results-based programming’. They ask whether they are getting ‘value for money’. And the commitment of national leaders to the MDGs confirms that they, as well as the donors, expect accountability for the significant expenditures now being made on health programs. Ultimately, what the global health community wants to know is which programs of service delivery can most efficiently improve health. Without strong evaluations designed to measure impact, decision-makers lack sufficient evidence to fund expansion of service delivery or behavior change programs, and doing so without data on impact might even be considered unethical [1]. But there are many constraints to measuring the impact of large, complex programs, and studies to evaluate impact are expensive and take time [2]. The global health community has instead relied almost exclusively on measurements of intervention coverage, behaviors, and levels of mortality and fertility from household surveys to assess progress. This approach has a long tradition, starting in the 1970s with the World Fertility and Contraceptive Prevalence Surveys, and continues today with the Demographic and Health Surveys and the Multiple Indicator Cluster Surveys, which are the main vehicle for measuring progress toward many of the MDGs. But from the point of implementing organizations, surveys do not provide timely information, and rarely report below regional or provincial level, when more specific data are often needed for program management. Surveys are also expensive and they leave a large gap - a black box - between program inputs and their outcomes and impact. Many implementing organizations are looking for new approaches to express the impact, equity and breadth of their programs. The papers in this Supplement provide a middle ground solution. They give us the opportunity to examine how two organizations that implement global health programs are addressing the need to assess performance, make strategic decisions about their programmatic priorities based on performance and goals, and at the same time be accountable to funders and national stakeholders. The papers provide details about how these program implementers are translating routinely-collected data on program outputs - either commodities distributed or services provided - into estimates of impact on health status, as expressed in disability-adjusted life years (DALYs) averted and on outcomes as expressed in changes in contraceptive prevalence and contribution to national indicators. The papers describe a range of organizational uses for data on impact, as well as analytic methods for examining equity in health status and program exposure that may be used to guide program development.