The RADAR coverage tool: developing a toolkit for rigorous household surveys for reproductive, maternal, newborn, and child health & nutrition indicators

Evaluation of a comprehensive maternal newborn health intervention in rural Tanzania: single-arm pre-post coverage survey results

Background

In Tanzania, maternal and newborn deaths can be prevented via quality facility-based antenatal care (ANC), delivery, and postnatal care (PNC). Scalable, integrated, and comprehensive interventions addressing demand and service-side care-seeking barriers are needed.

Objective

Assess coverage survey indicators before and after a comprehensive maternal newborn health (MNH) intervention in Misungwi District, Tanzania.

Methods

A prospective, single-arm, pre- (2016) and post-(2019) coverage survey (ClinicalTrials.gov #NCT02506413) was used to assess key maternal and newborn health (MNH) outcomes. The Mama na Mtoto intervention included district activities (planning, leadership training, supportive supervision), health facility activities (training, equipment, infrastructure upgrades), and plus community health worker mobilization. Implementation change strategies, a process model, and a motivational framework incorporated best practices from a similar Ugandan intervention. Cluster sampling randomized hamlets then used ‘wedge sampling’ protocol as an alternative to full household enumeration. Key outcomes included: four or more ANC visits (ANC4+); skilled birth attendant (SBA); PNC for mother within 48 hours (PNC-woman); health facility delivery (HFD); and PNC for newborn within 48 hours (PNC-baby). Trained interviewers administered the ‘Real Accountability: Data Analysis for Results Coverage Survey to women 15–49 years old. Descriptive statistics incorporated design effect; the Lives Saved Tool estimated deaths averted based on ANC4+/HFD.

Results

Between baseline (n = 2,431) and endline (n = 2,070), surveys revealed significant absolute percentage increases for ANC4+ (+11.6, 95% CI [5.4, 17.7], p < 0.001), SBA (+16.6, 95% CI [11.1, 22.0], p < 0.001), PNC-woman (+9.2, 95% CI [3.2, 15.2], p = 0.002), and HFD (+17.2%, 95% CI [11.3, 23.1], p < 0.001). A PNC-baby increase (+6.1%, 95% CI [−0.5, 12.8], p = 0.07) was not statistically significant. An estimated 121 neonatal and 20 maternal lives were saved between 2016 and 2019.

Conclusions

Full-district scale-up of a comprehensive MNH package embedded government health system was successfully implemented over a short time and associated with significant maternal care-seeking improvements and potential for lives saved.

The role of modeling in evaluation of maternal and child health programs: using the lives saved tool to help answer core evaluation questions

This paper explains how The Lives Saved Tool (LiST), a computer-based model that estimates the impact of scaling up interventions on stillbirths, maternal, neonatal and child health, can contribute to evaluations of programs being delivered at scale to improve maternal and child health. LiST can be used to estimate the impact of a program in advance, allowing planners to refine, streamline and set appropriate program targets. LiST can also be used to estimate the impact of a program, which is particularly useful given the high costs of measuring changes in population health. Finally, LiST can be used to estimate the relative contributions of different interventions or sets of interventions within programs that are found to have a positive impact. The latest version of LiST allows users to manipulate both utilization and quality of service to generate estimates of effective coverage. In addition, a new, web-based version of LiST is now available, with a simpler and more streamlined interface designed to increase accessibility to beginning users. LiST modeling can help program planners, evaluators and funders respond to core evaluation questions related to program design and impact, providing evidence to support decisions about how best to use available resources to save the lives of women and children.