Closing data gaps

Good quality data can help to drive informed decision making about implementation strategies and targeted investment. ‘Countdown to 2030’ is a multi-institutional partnership and initiative recognising the power of data to enhance accountability and monitor progress towards achieving the Sustainable Development Goals (SDGs) and the vision of the Global Strategy for Women’s, Children’s and Adolescents’ Health.

‘Countdown to 2030’ has three main objectives: improving measurement of and equity within drivers of coverage of interventions; strengthening capacity to collect data and; generating and using evidence at regional and country levels.

Common themes around data gaps have arisen throughout this course, summarised below, and are especially pertinent across newborn and adolescent health despite their high burden and potential for impact. A number of international and national groups are now focussing on these issues, including for example the Bill & Melinda Gates funded “IDEAS” project at the London School of Hygiene and Tropical Medicine.

Common themes about data gaps across the life cycle

Civil registration and vital statistics systems are often poor and require investment, particularly in high burden and conflict settings. Counting is essential as many countries today still lack timely data about births and deaths. We still don’t know how many women, children and adolescents die, when and why they die, who survives, and therefore what interventions are most effective in many high burden settings.

Better data to inform the implementation of programmes so that investments become more efficient is frequently lacking. These data need to be both timely and relevant at sub-national levels, and accessible to programme leaders. Survey data that measures population level indicators are vital, but so too is the strengthening of routinely collected data that can be summarised more frequently through programme monitoring, and through health information systems. Without this, essential, timely information needed to best target and manage precious resources is missing.

Inequities between rich and poor populations are pronounced for women, children and adolescents, despite intentions to deliver pro-poor services. It is important that data systems are designed to reveal and track these inequities and drive accountability mechanisms for targeted action to benefit those in poverty. Going forward, further investment and advocacy are required to ensure equity analysis tools are institutionalised across all major data collection platforms.

Highlighted data gaps at each stage of the life cycle

Adolescent

Many data gaps exist in adolescent health, in part because the health of young people has only recently been prioritised at the global level. Beyond the need to design data collection tools that specifically target the priorities in adolescent health, three design issues also lead to critical data gaps:

• Existing data collection systems frequently leave young people invisible as they fall between target child and adult populations, and sample sizes are not adequate to confidently estimate outcomes for this group

• There is a lack of standardisation in measurement of adolescent outcomes, meaning that comparisons within and between countries can be limited

• The age of consent for participating in interviews can have the unintended effect of limiting young people’s engagement with surveys, particularly for younger adolescents aged 10–14 years.

Maternal

Continuing to invest in the measurement of maternal mortality is essential, but as survival rates improve this will necessitate greater financial investment. Currently, only a very small minority of the coverage indicators prioritised for global tracking target maternal health interventions, in part because they tend to be clinical and delivered in health facilities. Thus improved facility-based monitoring mechanisms are needed to compliment women’s reports during surveys. Accountability mechanisms to track quality of care, including respect of women, require ongoing improvement to ensure valid measurement at scale. In addition, increased coverage of near-miss technologies alongside maternal perinatal audits is an ongoing priority in high burden settings.

Newborn

Preterm birth is the leading cause of neonatal mortality yet the ability to accurately estimate the gestation of pregnancies, or gestational age at birth, can severely limit delivery of life-saving interventions to those in need. With over 75% of births now occurring in facilities, coverage measurement of routine life-saving care is needed. Accurate estimation of the number of newborns with severe bacterial infections, and the number who receive appropriate treatment for those infections, is similarly limited. Further to these data gaps, the newborn experiences the same data limitations as the mother, especially with regard to measurement of quality of care.

Stillbirths

Improved data on stillbirths are an urgent priority. Nearly all babies who enter the world stillborn, do not receive a birth or death certificate. In order to understand and prevent stillbirths, countries require mechanisms to count, audit and review reasons for death. Mortality audit for neonatal deaths and stillbirths, linked to maternal contributory conditions, are vital for generating quality data for decision making, action and accountability.

Child

Many of the successes in improved child survival have been accompanied by better data tracking of childhood interventions, even in high burden settings, for example vaccination coverage and malaria prevention and treatment. As for the other stages of the life cycle, better country-owned systems for reporting must be developed, sustained, and include disaggregation by equity indicators. New data methods and generation of data on early childhood development that can be scaled-up to estimate the child who thrives will be essential in the SDG era.

Moving forward

Key messages based on findings from Countdown 2030:

• Country specific coverage targets, for example 2020 and 2025, with attention to inequality dimension for monitoring indicators in support of meeting SDG, and Every Newborn targets

• Country ownership and investment in local analytical capacity for collecting and using data at all levels of national systems

• Investments prioritised on reliable data on intervention coverage, with attention to measurement of quality of care

• Strengthen vital statistics to improve measurement of and inequities in coverage

• Better data within humanitarian emergency and high burden settings

• Understanding on the drivers of intervention coverage change

• Better data on early childhood development and adolescent health to ensure we support children to not only survive but also thrive as they transition through adolescence and into adulthood.

In the next step we will look in more detail initiatives such as the ‘Global Financing Facility’ to support the global targets set out for women, newborns, children and adolescents are designed to help drive the changes needed in data.