Researchers are comparing direct observation of labor and delivery practices to women’s reports to develop better measures to track the quality of maternal health care.
Every year, hundreds of thousands of women die of causes related to pregnancy and childbirth. Almost all of these deaths occur in developing countries, and most are preventable.
At the global level, the proportion of births attended by skilled health personnel and the proportion of births delivered in health facilities are proxies for the quality of care received by women during labor and delivery. These indicators are routinely tracked and reported by national and international agencies and, given the difficulties in measuring maternal mortality, have become the most widely used indicators for measuring progress against maternal health goals. Yet, neither of these indicators is strongly and consistently associated with levels of or trends in maternal mortality.
There has been a growing call for a greater focus on the direct measurement and monitoring of the content and quality of care of maternal health services. However, the vast majority of indicators proposed as measures of the quality of maternal health care have not been tested. This includes the “skilled birth attendant” indicator, which has never been sufficiently validated.
This Population Council study is assessing the validity of women’s reports of skilled attendance at birth and the validity of women’s reports of selected aspects of maternal and newborn care during the intrapartum and early postpartum periods, which may hold promise as indicators of the quality of routine obstetric and immediate postnatal service provision.
To validate women’s self-reports, exit interviews with recently delivered women in health facilities will be compared to third-party observations of the care provided during their labor and delivery services. The study is being carried out in health facilities in Kenya and Mexico.
The aim of the study is to improve monitoring of the quality of maternal health care through identifying, developing, and validating a set of indicators. The results will inform the recommendation of indicators for global and local monitoring that have the potential for valid and reliable measurement and for integration into routine population-based and facility-based data collection systems.