Academic journal article Bulletin of the World Health Organization

Identifying Implementation Bottlenecks for Maternal and Newborn Health Interventions in Rural Districts of the United Republic of Tanzania

Academic journal article Bulletin of the World Health Organization

Identifying Implementation Bottlenecks for Maternal and Newborn Health Interventions in Rural Districts of the United Republic of Tanzania

Article excerpt

Identification des goulots d'etranglement entravant les interventions de sante maternelle et neonatale dans des districts ruraux de Republique-Unie de Tanzanie

Identificacion de obstaculos en la ejecucion de intervenciones de salud maternal y neonatal en distritos rurales de la Republica Unida de Tanzania.

Introduction

Although maternal and newborn mortality has been substantially reduced worldwide in recent years, progress has been uneven. In sub-Saharan Africa, few countries are on track to meet Millennium Development Goals (MDGs) 4 and 5 on child mortality and maternal heath, respectively. (1,2) Weak health systems have failed to achieve effective coverage of key interventions--they have been unable to reach mothers and newborns with interventions that were implemented as intended, with a potential impact on mortality. (3) A bottleneck has been defined as "that component of a system that limits the overall performance or capacity of the system." (4) Consequently, unless bottlenecks are targeted, efforts to strengthen health systems will have little effect. (4) Since identifying bottlenecks in health service delivery can help in setting priorities, it is an important area of research in maternal and newborn health and in attempts to strengthen district health systems. (1,5) Bottlenecks in implementation can be due to limited access, for geographical, financial or sociocultural reasons. Poor readiness of health-care facilities due to, for example, a lack of human resources, drugs or equipment and suboptimal clinical practice, such as failure to adhere to evidence-based clinical guidelines can also cause bottlenecks. (4,6-9)

Previously, monitoring improvements in maternal health focused primarily on the service use: for example, the proportion of mothers attending antenatal care or giving birth in a health facility. Although these are important indicators, they do not reflect the content or quality of the care provided or the extent to which key interventions are implemented as intended. (3) Currently, this measurement gap is one element in the discussions on universal health coverage that are taking place as part of the post-MDG agenda, in which the importance of quality-of-care indicators for assessing population coverage is emphasized. (10,11)

In 1978, Tanahashi described a way of both measuring health service coverage and identifying bottlenecks in implementation. (12) Since then, his approach has been used and modified by the United Nations Childrens Fund and the World Bank. (13) Although the coverage measures in Tanahashi's model both reflect quality of care and reveal implementation bottlenecks, there are limitations. First, the model focuses initially on health service capacity rather than output. Second, the assessments require high-quality data from health management information systems, which are rarely available in low-income settings, particularly for intrapartum interventions and subnational analyses. (14-16) These limitations could be overcome by linking household and health facility data, (14) as has been done previously for malaria care. (17,18)

Our objectives were to estimate the effective coverage of key maternal and newborn health interventions in rural parts of the United Republic of Tanzania and to identify bottlenecks in implementation.

Methods

We used data from an observational, cross-sectional study that was performed in Tandahimba and Newala districts in south-eastern United Republic of Tanzania. (19) Each district has a population of approximately 200 000 people and is characterized by high maternal and newborn mortality: in 2004-2007, the estimated maternal mortality ratio was 712 per 100 000 live births (20) and the estimated neonatal mortality rate was 31 per 1000 live births. (21) Data were collected as part of the EQUIP (Expanded Quality Management Using Information Power) project, which was a collaborative, quality improvement intervention for maternal and newborn care implemented in health facilities and communities in Tandahimba between November 2011 and April 2014. …

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