Survey of women's report for 33 maternal and newborn indicators: EN-BIRTH multi-country validation study.

BACKGROUND: Population-based household surveys, notably the Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS), remain the main source of maternal and newborn health data for many low- and middle-income countries. As part of the Every Newborn Birth Indicators Research Tracking in Hospitals (EN-BIRTH) study, this paper focuses on testing validity of measurement of maternal and newborn indicators around the time of birth (intrapartum and postnatal) in survey-report. METHODS: EN-BIRTH was an observational study testing the validity of measurement for selected maternal and newborn indicators in five secondary/tertiary hospitals in Bangladesh, Nepal and Tanzania, conducted from July 2017 to July 2018. We compared women's report at exit survey with the gold standard of direct observation or verification from clinical records for women with vaginal births. Population-level validity was assessed by validity ratios (survey-reported coverage: observer-assessed coverage). Individual-level accuracy was assessed by sensitivity, specificity and percent agreement. We tested indicators already in DHS/MICS as well as indicators with potential to be included in population-based surveys, notably the first validation for small and sick newborn care indicators. RESULTS: 33 maternal and newborn indicators were evaluated. Amongst nine indicators already present in DHS/MICS, validity ratios for baby dried or wiped, birthweight measured, low birthweight, and sex of baby (female) were between 0.90-1.10. Instrumental birth, skin-to-skin contact, and early initiation of breastfeeding were highly overestimated by survey-report (2.04-4.83) while umbilical cord care indicators were massively underestimated (0.14-0.22). Amongst 24 indicators not currently in DHS/MICS, two newborn contact indicators (kangaroo mother care 1.00, admission to neonatal unit 1.01) had high survey-reported coverage amongst admitted newborns and high sensitivity. The remaining indicators did not perform well and some had very high "don't know" responses. CONCLUSIONS: Our study revealed low validity for collecting many maternal and newborn indicators through an exit survey instrument, even with short recall periods among women with vaginal births. Household surveys are already at risk of overload, and some specific clinical care indicators do not perform well and may be under-powered. Given that approximately 80% of births worldwide occur in facilities, routine registers should also be explored to track coverage of key maternal and newborn health interventions, particularly for clinical care

"Every Newborn-BIRTH" protocol: observational study validating indicators for coverage and quality of maternal and newborn health care in Bangladesh, Nepal and Tanzania.

Background: To achieve Sustainable Development Goals and Universal Health Coverage, programmatic data are essential. The Every Newborn Action Plan, agreed by all United Nations member states and >80 development partners, includes an ambitious Measurement Improvement Roadmap. Quality of care at birth is prioritised by both Every Newborn and Ending Preventable Maternal Mortality strategies, hence metrics need to advance from health service contact alone, to content of care. As facility births increase, monitoring using routine facility data in DHIS2 has potential, yet validation research has mainly focussed on maternal recall surveys. The Every Newborn - Birth Indicators Research Tracking in Hospitals (EN-BIRTH) study aims to validate selected newborn and maternal indicators for routine tracking of coverage and quality of facility-based care for use at district, national and global levels. Methods: EN-BIRTH is an observational study including >20 000 facility births in three countries (Tanzania, Bangladesh and Nepal) to validate selected indicators. Direct clinical observation will be compared with facility register data and a pre-discharge maternal recall survey for indicators including: uterotonic administration, immediate newborn care, neonatal resuscitation and Kangaroo mother care. Indicators including neonatal infection management and antenatal corticosteroid administration, which cannot be easily observed, will be validated using inpatient records. Trained clinical observers in Labour/Delivery ward, Operation theatre, and Kangaroo mother care ward/areas will collect data using a tablet-based customised data capturing application. Sensitivity will be calculated for numerators of all indicators and specificity for those numerators with adequate information. Other objectives include comparison of denominator options (ie, true target population or surrogates) and quality of care analyses, especially regarding intervention timing. Barriers and enablers to routine recording and data usage will be assessed by data flow assessments, quantitative and qualitative analyses. Conclusions: To our knowledge, this is the first large, multi-country study validating facility-based routine data compared to direct observation for maternal and newborn care, designed to provide evidence to inform selection of a core list of indicators recommended for inclusion in national DHIS2. Availability and use of such data are fundamental to drive progress towards ending the annual 5.5 million preventable stillbirths, maternal and newborn deaths.Children’s Investment Fund Foundation (CIFF)Swedish Research CouncilUnited States Agency for International DevelopmentSaving Newborn Lives/Save the ChildrenWHOBill & Melinda Gates Foundatio

Electronic data collection for multi-country, hospital-based, clinical observation of maternal and newborn care: EN-BIRTH study experiences.

BACKGROUND: Observation of care at birth is challenging with multiple, rapid and potentially concurrent events occurring for mother, newborn and placenta. Design of electronic data (E-data) collection needs to account for these challenges. The Every Newborn Birth Indicators Research Tracking in Hospitals (EN-BIRTH) was an observational study to assess measurement of indicators for priority maternal and newborn interventions and took place in five hospitals in Bangladesh, Nepal and Tanzania (July 2017-July 2018). E-data tools were required to capture individually-linked, timed observation of care, data extraction from hospital register-records or case-notes, and exit-survey data from women. METHODS: To evaluate this process for EN-BIRTH, we employed a framework organised around five steps for E-data design, data collection and implementation. Using this framework, a mixed methods evaluation synthesised evidence from study documentation, standard operating procedures, stakeholder meetings and design workshops. We undertook focus group discussions with EN-BIRTH researchers to explore experiences from the three different country teams (November-December 2019). Results were organised according to the five a priori steps. RESULTS: In accordance with the five-step framework, we found: 1) Selection of data collection approach and software: user-centred design principles were applied to meet the challenges for observation of rapid, concurrent events around the time of birth with time-stamping. 2) Design of data collection tools and programming: required extensive pilot testing of tools to be user-focused and to include in-built error messages and data quality alerts. 3) Recruitment and training of data collectors: standardised with an interactive training package including pre/post-course assessment. 4) Data collection, quality assurance, and management: real-time quality assessments with a tracking dashboard and double observation/data extraction for a 5% case subset, were incorporated as part of quality assurance. Internet-based synchronisation during data collection posed intermittent challenges. 5) Data management, cleaning and analysis: E-data collection was perceived to improve data quality and reduce time cleaning. CONCLUSIONS: The E-Data system, custom-built for EN-BIRTH, was valued by the site teams, particularly for time-stamped clinical observation of complex multiple simultaneous events at birth, without which the study objectives could not have been met. However before selection of a custom-built E-data tool, the development time, higher training and IT support needs, and connectivity challenges need to be considered against the proposed study or programme's purpose, and currently available E-data tool options

Labour and delivery ward register data availability, quality, and utility-Every Newborn-birth indicators research tracking in hospitals (EN-BIRTH) study baseline analysis in three countries

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. RESULTS: Data were extracted for 20,075 births. Register design was different between the five hospitals with 10-17 of the 21 selected MNH data elements available. More data were available for health outcomes than interventions. Nearly all available data elements were > 95% complete in four of the five hospitals and implausible values were rare. Data elements captured in specific columns were 85.2% highly complete compared to 25.0% captured in non-specific columns. Birthweight data were less complete for stillbirths than live births at two hospitals, and significant heaping was found in all sites, especially at 2500g and 3000g. All five hospitals recorded count data required to calculate impact indicators including; stillbirth rate, low birthweight rate, Caesarean section rate, and mortality rates. CONCLUSIONS: Data needed to calculate MNH indicators are mostly available and highly complete in EN-BIRTH study hospital routine labour ward registers in Bangladesh, Nepal and Tanzania. Register designs need to include interventions for coverage measurement. There is potential to improve data quality if Health Management Information Systems utilization with feedback loops can be strengthened. Routine health facility data could contribute to reduce the coverage and impact data gap around the time of birth