“Guilty until proven innocent”: the contested use of maternal mortality indicators in global health

Abstract

The MMR – maternal mortality ratio – has risen from obscurity to become a major global health indicator, even appearing as an indicator of progress towards the global Sustainable Development Goals. This has happened despite intractable challenges relating to the measurement of maternal mortality. Even after three decades of measurement innovation, maternal mortality data are widely presumed to be of poor quality, or, as one leading measurement expert has put it, ‘guilty until proven innocent’. This paper explores how and why leading epidemiologists, demographers and statisticians have devoted the better part of the last three decades to producing ever more sophisticated and expensive surveys and mathematical models of globally comparable MMR estimates. The development of better metrics is publicly justified by the need to know which interventions save lives and at what cost. We show, however, that measurement experts’ work has also been driven by the need to secure political priority for safe motherhood and by donors’ need to justify and monitor the results of investment flows. We explore the many effects and consequences of this measurement work, including the eclipsing of attention to strengthening much-needed national health information systems. We analyse this measurement work in relation to broader political and economic changes affecting the global health field, not least the incursion of neoliberal, business-oriented donors such as the World Bank and the Bill and Melinda Gates Foundation whose institutional structures have introduced new forms of administrative oversight and accountability that depend on indicators.

Introduction

“…| 3 2012; Merry and Conley 2011). Instead, we recognise that contemporary global health's need to capture information, link researchers and practitioners more eff ectively to one another, and to increase fi nancial resources has occasioned shi s within global health practice over the past decade away from gathering and analysing data for the purpose of redressing local inequalities and moved instead towards producing indicators to meet funders' needs (Adams 2013;Storeng and Béhague 2017). But where does that leave anthropology?…”

The construction of mental health as a technological problem in India

“…Studies show that: 'successful' health coverage from a top-down donor perspective can be experienced as ineffectual and meaningless by local actors (Uretsky, 2017); there are cultural differences in understanding effective 'health' interventions (Hales, 2016); and local actors may perform differently for international donors (Sullivan, 2017). The construction and production of health metrics has also been criticized for its depoliticizing effects (Storeng and Béhague, 2017) and, in the context of HIV/AIDS interventions in India, for inscribing and perpetuating assumed uniform identities for different social groups (Lorway, 2017).…”

Misdirection in the margins of malaria elimination methods

“…The drive to produce standardized, decontextualized numerical data discredits insights from experiential epistemologies and outsources large parts of national health systems to transnational consortia of experts (Lorway, 2017). Whilst the response to global donor's data demands has led to ever more sophisticated surveys, models and indicators, it has also eclipsed the building up of much needed national health information systems (Storeng & Béhague, 2017). At the same time, the move to accountability and performancebased financing has focused health care interventions on the production of measurable results as an end in and of themselves, sometimes at the expense of effective prevention measures (Fan, 2017).…”