Background Progress in reducing maternal and neonatal deaths and stillbirths is impeded by data gaps, especially regarding coverage and quality of care in hospitals. We aimed to assess the validity of indicators of maternal and newborn health-care coverage around the time of birth in survey data and routine facility register data.Methods Every Newborn-BIRTH Indicators Research Tracking in Hospitals was an observational study in five hospitals in Bangladesh, Nepal, and Tanzania. We included women and their newborn babies who consented on admission to hospital. Exclusion critiera at admission were no fetal heartbeat heard or imminent birth. For coverage of uterotonics to prevent post-partum haemorrhage, early initiation of breastfeeding (within 1 h), neonatal bag-mask ventilation, kangaroo mother care (KMC), and antibiotics for clinically defined neonatal infection (sepsis, pneumonia, or meningitis), we collected time-stamped, direct observation or case note verification data as gold standard. We compared data reported via hospital exit surveys and via hospital registers to the gold standard, pooled using random effects meta-analysis. We calculated population-level validity ratios (measured coverage to observed coverage) plus individual-level validity metrics. Findings We observed 23 471 births and 840 mother-baby KMC pairs, and verified the case notes of 1015 admitted newborn babies regarding antibiotic treatment. Exit-survey-reported coverage for KMC was 99•9% (95% CI 98•3-100) compared with observed coverage of 100% (99•9-100), but exit surveys underestimated coverage for uterotonics (84•7% [79•1-89•5]) vs 99•4% [98•7-99•8] observed), bag-mask ventilation (0•8% [0•4-1•4]) vs 4•4% [1•9-8•1]), and antibiotics for neonatal infection (74•7% [55•3-90•1] vs 96•4% [94•0-98•6] observed). Early breastfeeding coverage was overestimated in exit surveys (53•2% [39•4-66•8) vs 10•9% [3•8-21•0] observed). "Don't know" responses concerning clinical interventions were more common in the exit survey after caesarean birth. Register data underestimated coverage of uterotonics (77•9% [37•8-99•5] vs 99•2% [98•6-99•7] observed), bag-mask ventilation (4•3% [2•1-7•3] vs 5•1% [2•0-9•6] observed), KMC (92•9% [84•2-98•5] vs 100% [99•9-100] observed), and overestimated early breastfeeding (85•9% (58•1-99•6) vs 12•5% [4•6-23•6] observed). Inter-hospital heterogeneity was higher for register-recorded coverage than for exit survey report. Even with the same register design, accuracy varied between hospitals.Interpretation Coverage indicators for newborn and maternal health care in exit surveys had low accuracy for specific clinical interventions, except for self-report of KMC, which had high sensitivity after admission to a KMC ward or corner and could be considered for further assessment. Hospital register design and completion are less standardised than surveys, resulting in variable data quality, with good validity for the best performing sites. Because approximately 80% of births worldwide take place in facilities, standardising register d...
Background Immediate newborn care (INC) practices, notably early initiation of breastfeeding (EIBF), are fundamental for newborn health. However, coverage tracking currently relies on household survey data in many settings. “Every Newborn Birth Indicators Research Tracking in Hospitals” (EN-BIRTH) was an observational study validating selected maternal and newborn health indicators. This paper reports results for EIBF. Methods The EN-BIRTH study was conducted in five public hospitals in Bangladesh, Nepal, and Tanzania, from July 2017 to July 2018. Clinical observers collected tablet-based, time-stamped data on EIBF and INC practices (skin-to-skin within 1 h of birth, drying, and delayed cord clamping). To assess validity of EIBF measurement, we compared observation as gold standard to register records and women’s exit-interview survey reports. Percent agreement was used to assess agreement between EIBF and INC practices. Kaplan Meier survival curves showed timing. Qualitative interviews were conducted to explore barriers/enablers to register recording. Results Coverage of EIBF among 7802 newborns observed for ≥1 h was low (10.9, 95% CI 3.8–21.0). Survey-reported (53.2, 95% CI 39.4–66.8) and register-recorded results (85.9, 95% CI 58.1–99.6) overestimated coverage compared to observed levels across all hospitals. Registers did not capture other INC practices apart from breastfeeding. Agreement of EIBF with other INC practices was high for skin-to-skin (69.5–93.9%) at four sites, but fair/poor for delayed cord-clamping (47.3–73.5%) and drying (7.3–29.0%). EIBF and skin-to-skin were the most delayed and EIBF rarely happened after caesarean section (0.5–3.6%). Qualitative findings suggested that focusing on accuracy, as well as completeness, contributes to higher quality with register reporting. Conclusions Our study highlights the importance of tracking EIBF despite measurement challenges and found low coverage levels, particularly after caesarean births. Both survey-reported and register-recorded data over-estimated coverage. EIBF had a strong agreement with skin-to-skin but is not a simple tracer for other INC indicators. Other INC practices are challenging to measure in surveys, not included in registers, and are likely to require special studies or audits. Continued focus on EIBF is crucial to inform efforts to improve provider practices and increase coverage. Investment and innovation are required to improve measurement.
Background: Countries with the highest burden of maternal and newborn deaths and stillbirths often have little information on these deaths. Since over 81% of births worldwide now occur in facilities, using routine facility data could reduce this data gap. We assessed the availability, quality, and utility of routine labour and delivery ward register data in five hospitals in Bangladesh, Nepal, and Tanzania. This paper forms the baseline register assessment for the Every Newborn-Birth Indicators Research Tracking in Hospitals (EN-BIRTH) study. Methods: We extracted 21 data elements from routine hospital labour ward registers, useful to calculate selected maternal and newborn health (MNH) indicators. The study sites were five public hospitals during a one-year period (2016-17). We measured 1) availability: completeness of data elements by register design, 2) data quality: implausibility, internal consistency, and heaping of birthweight and explored 3) utility by calculating selected MNH indicators using the available data.
BackgroundLess than 5 years remain before the 2015 mark when countries will be evaluated on their achievements for the Millennium Development Goals (MDGs). The MDG 4 and 6 call for a reduction of child mortality by two-thirds and combating malaria, HIV/AIDS, TB, and other diseases, respectively. To accelerate the achievement of these goals, focused allocation of resources and high deployment of cost-effective interventions is paramount. The knowledge of spatial and temporal distribution of diseases is important for health authorities to prioritize and allocate resources.MethodsTo identify possible significant clusters, we used SatTScan software, and analyzed 2,745 cases of under-five with 134,099 person-years for the period between 1999and 2008. Mortality rates for every year were calculated, likewise a spatial scan statistic was used to test for clusters of total under-five mortalities in both space and time.ResultsA number of significant clusters from space, time, and space–time analysis were identified in several locations for a period of 10 years in the Rufiji Demographic Surveillance Site (RDSS). These locations show that villages within the clusters have an elevated risk of under-five deaths. The spatial analysis identified three significant clusters. The first cluster had only one village, Kibiti A (p < 0.05, the second cluster involved five villages (Mtawanya, Pagae, Kibiti A, Machepe, and Kibiti B; p < 0.05), the third cluster involved one village, Jaribu Mpakani (p < 0.05). A space–time cluster of 10 villages for the period between 1999 and 2002 with a radius of 14.73 km was discovered with the highest risk (RR 1.6, p < 0.001). The mortality rates were very high for the years 1999–2002 according to the analysis. The death rates were 33.5, 26.4, 24.1, and 24.9, respectively. Total childhood mortality rates calculated for the period of 10 years were 21.0 per 1,000 person-years.ConclusionDuring the 10 years of analysis, mortality seemed to decrease in RDSS. The mortality decline should be taken with caution because the Demographic Surveillance System is not statistically representative of the whole population; therefore, inference should not be made to the general population of Tanzania. The pattern observed could be attributed to demographic and weather characteristics of RDSS. This should provide new insights for further studies and interventions toward reducing under-five mortality.
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