Vandana Tripathi | October 2015
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Presentation at the Global Maternal Newborn Health Conference, October 21, 2015

Background: There is global recognition that quality of care (QoC) must improve to achieve further reductions in maternal and newborn mortality. There is a need for valid, reliable, and efficient labor & delivery (L&D) quality assessment tools. Observation-based measures of obstetric care quality are infrequently used and often lengthy and difficult to administer. This study developed and validated two measures to address these gaps. The study focused on the intrapartum and immediate postpartum periods when most maternal and newborn deaths occur and quality may have the greatest impact.

Methodology: A group of global maternal and newborn care (MNC) experts participated in a modified Delphi process to identify key dimensions of L&D care quality. Experts rated >130 items used to assess L&D care in a series of facility Maternal and Newborn Quality of Care Surveys. Potential QoC indices were developed from highly-rated indicators. Face, content, and criterion validation of these indices used data from 1,145 deliveries observed in Kenya, Madagascar, and Tanzania (including Zanzibar).

Results: An index that performed best on validation benchmarks was identified, including 20 indicators of intrapartum/immediate postpartum/essential newborn care. This index represented most key dimensions of L&D QoC, effectively discriminated between poorly and well-performed deliveries, and appears to be a strong proxy for overall care quality. Responding to concerns about time required to observe full L&D care, a shorter version of the index was created, containing just 13 items that can be assessed at delivery and in the first hour after birth. The comprehensive index is preferred, as it provides a more complete picture of L&D QoC. However, the “delivery-only” index may be a robust alternative in resource-constrained settings.

Conclusions: These tools complement existing MNC quality assessment approaches. Following further validation and piloting, they may be useful in ongoing supervision processes as well as quality improvement research.