Linking data sources for measurement of effective coverage in maternal and newborn health: what do we learn from individual- vs ecological-linking methods?

BACKGROUND: Improving maternal and newborn health requires improvements in the quality of facility-based care. This is challenging to measure: routine data may be unreliable; respondents in population surveys may be unable to accurately report on quality indicators; and facility assessments lack population level denominators. We explored methods for linking access to skilled birth attendance (SBA) from household surveys to data on provision of care from facility surveys with the aim of estimating population level effective coverage reflecting access to quality care. METHODS: We used data from Mayuge District, Uganda. Data from household surveys on access to SBA were linked to health facility assessment census data on readiness to provide basic emergency obstetric and newborn care (BEmONC) in the same district. One individual- and two ecological-linking methods were applied. All methods used household survey reports on where care at birth was accessed. The individual-linking method linked this to data about facility readiness from the specific facility where each woman delivered. The first ecological-linking approach used a district-wide mean estimate of facility readiness. The second used an estimate of facility readiness adjusted by level of health facility accessed. Absolute differences between estimates derived from the different linking methods were calculated, and agreement examined using Lin's concordance correlation coefficient. RESULTS: A total of 1177 women resident in Mayuge reported a birth during 2012-13. Of these, 664 took place in facilities within Mayuge, and were eligible for linking to the census of the district's 38 facilities. 55% were assisted by a SBA in a facility. Using the individual-linking method, effective coverage of births that took place with an SBA in a facility ready to provide BEmONC was just 10% (95% confidence interval CI 3-17). The absolute difference between the individual- and ecological-level linking method adjusting for facility level was one percentage point (11%), and tests suggested good agreement. The ecological method using the district-wide estimate demonstrated poor agreement. CONCLUSIONS: The proportion of women accessing appropriately equipped facilities for care at birth is far lower than the coverage of facility delivery. To realise the life-saving potential of health services, countries need evidence to inform actions that address gaps in the provision of quality care. Linking household and facility-based information provides a simple but innovative method for estimating quality of care at the population level. These encouraging findings suggest that linking data sets can result in meaningful evidence even when the exact location of care seeking is not known

Improving coverage measurement for reproductive, maternal, neonatal and child health: gaps and opportunities.

BACKGROUND: Regular monitoring of coverage for reproductive, maternal, neonatal, and child health (RMNCH) is central to assessing progress toward health goals. The objectives of this review were to describe the current state of coverage measurement for RMNCH, assess the extent to which current approaches to coverage measurement cover the spectrum of RMNCH interventions, and prioritize interventions for a novel approach to coverage measurement linking household surveys with provider assessments. METHODS: We included 58 interventions along the RMNCH continuum of care for which there is evidence of effectiveness against cause-specific mortality and stillbirth. We reviewed household surveys and provider assessments used in low- and middle-income countries (LMICs) to determine whether these tools generate measures of intervention coverage, readiness, or quality. For facility-based interventions, we assessed the feasibility of linking provider assessments to household surveys to provide estimates of intervention coverage. RESULTS: Fewer than half (24 of 58) of included RMNCH interventions are measured in standard household surveys. The periconceptional, antenatal, and intrapartum periods were poorly represented. All but one of the interventions not measured in household surveys are facility-based, and 13 of these would be highly feasible to measure by linking provider assessments to household surveys. CONCLUSIONS: We found important gaps in coverage measurement for proven RMNCH interventions, particularly around the time of birth. Based on our findings, we propose three sets of actions to improve coverage measurement for RMNCH, focused on validation of coverage measures and development of new measurement approaches feasible for use at scale in LMICs

Community-based Health Workers Achieve High Coverage in Neonatal Intervention Trials: A Case Study from Sylhet, Bangladesh

A large proportion of four million neonatal deaths occur each year during the first 24 hours of life. Research is particularly needed to determine the efficacy of interventions during the first 24 hours. Large cadres of community-based workers are required in newborn-care research both to deliver these interventions in a standardized manner in the home and to measure the outcomes of the study. In a large-scale community-based efficacy trial of chlorhexidine for cleansing the cord in north-eastern rural Bangladesh, a two-tiered system of community-based workers was established to deliver a package of essential maternal and newborn-care interventions and one of three umbilical cord-care regimens. At any given time, the trial employed approximately 133 community health workers—each responsible for 4–5 village health workers and a population of approximately 4,000. Over the entire trial period, 29,760 neonates were enrolled, and 87% of them received the intervention (their assigned cord-care regimen) within 24 hours of birth. Approaches to recruitment, training, and supervision in the study are described. Key lessons included the importance of supportive processes for community-based workers, including a strong training and field supervisory system, community acceptance of the study, consideration of the setting, study objectives, and human resources available

Community-based Health Workers Achieve High Coverage in Neonatal Intervention Trials: A Case Study from Sylhet, Bangladesh

A large proportion of four million neonatal deaths occur each year during the first 24 hours of life. Research is particularly needed to determine the efficacy of interventions during the first 24 hours. Large cadres of community-based workers are required in newborn-care research both to deliver these interventions in a standardized manner in the home and to measure the outcomes of the study. In a large-scale community-based efficacy trial of chlorhexidine for cleansing the cord in north-eastern rural Bangladesh, a two-tiered system of community-based workers was established to deliver a package of essential maternal and newborn-care interventions and one of three umbilical cord-care regimens. At any given time, the trial employed approximately 133 community health workers-each responsible for 4-5 village health workers and a population of approximately 4,000. Over the entire trial period, 29,760 neonates were enrolled, and 87% of them received the intervention (their assigned cord-care regimen) within 24 hours of birth. Approaches to recruitment, training, and supervision in the study are described. Key lessons included the importance of supportive processes for community-based workers, including a strong training and field supervisory system, community acceptance of the study, consideration of the setting, study objectives, and human resources available

Validation studies for population-based intervention coverage indicators: design, analysis, and interpretation.

BACKGROUND: Population-based intervention coverage indicators are widely used to track country and program progress in improving health and to evaluate health programs. Indicator validation studies that compare survey responses to a "gold standard" measure are useful to understand whether the indicator provides accurate information. The Improving Coverage Measurement (ICM) Core Group has developed and implemented a standard approach to validating coverage indicators measured in household surveys, described in this paper. METHODS: The general design of these studies includes measurement of true health status and intervention receipt (gold standard), followed by interviews with the individuals observed, and a comparison of the observations (gold standard) to the responses to survey questions. The gold standard should use a data source external to the respondent to document need for and receipt of an intervention. Most frequently, this is accomplished through direct observation of clinical care, and/or use of a study-trained clinician to obtain a gold standard diagnosis. Follow-up interviews with respondents should employ standard survey questions, where they exist, as well as alternative or additional questions that can be compared against the standard household survey questions. RESULTS: Indicator validation studies should report on participation at every stage, and provide data on reasons for non-participation. Metrics of individual validity (sensitivity, specificity, area under the receiver operating characteristic curve) and population-level validity (inflation factor) should be reported, as well as the percent of survey responses that are "don't know" or missing. Associations between interviewer and participant characteristics and measures of validity should be assessed and reported. CONCLUSIONS: These methods allow respondent-reported coverage measures to be validated against more objective measures of need for and receipt of an intervention, and should be considered together with cognitive interviewing, discriminative validity, or reliability testing to inform decisions about which indicators to include in household surveys. Public health researchers should assess the evidence for validity of existing and proposed household survey coverage indicators and consider validation studies to fill evidence gaps

Advances in the measurement of coverage for RMNCH and nutrition: from contact to effective coverage.

Current methods for measuring intervention coverage for reproductive, maternal, newborn, and child health and nutrition (RMNCH+N) do not adequately capture the quality of services delivered. Without information on the quality of care, it is difficult to assess whether services provided will result in expected health improvements. We propose a six-step coverage framework, starting from a target population to (1) service contact, (2) likelihood of services, (3) crude coverage, (4) quality-adjusted coverage, (5) user-adherence-adjusted coverage and (6) outcome-adjusted coverage. We support our framework with a comprehensive review of published literature on effective coverage for RMNCH+N interventions since 2000. We screened 8103 articles and selected 36 from which we summarised current methods for measuring effective coverage and computed the gaps between 'crude' coverage measures and quality-adjusted measures. Our review showed considerable variability in data sources, indicator definitions and analytical approaches for effective coverage measurement. Large gaps between crude coverage and quality-adjusted coverage levels were evident, ranging from an average of 10 to 38 percentage points across the RMNCH+N interventions assessed. We define effective coverage as the proportion of individuals experiencing health gains from a service among those who need the service, and distinguish this from other indicators along a coverage cascade that make quality adjustments. We propose a systematic approach for analysis along six steps in the cascade. Research to date shows substantial drops in effective delivery of care across these steps, but variation in methods limits comparability of the results. Advancement in coverage measurement will require standardisation of effective coverage terminology and improvements in data collection and methodological approaches

Revitalizing child health: lessons from the past

Essential health, education and other service disruptions arising from the COVID-19 pandemic risk reversing some of the hard-won gains in improving child survival over the past 40 years. Although children have milder symptoms of COVID-19 disease than adults, pandemic control measures in many countries have disrupted health, education and other services for children, often leaving them without access to birth and postnatal care, vaccinations and early childhood preventive and treatment services. These disruptions mean that the SARS-CoV-2 virus, along with climate change and shifting epidemiological and demographic patterns, are challenging the survival gains that we have seen over the past 40 years. We revisit the initiatives and actions of the past that catalyzed survival improvements in an effort to learn how to maintain these gains even in the face of today's global challenges

The effect of oral rehydration solution and recommended home fluids on diarrhoea mortality

Background Most diarrhoeal deaths can be prevented through the prevention and treatment of dehydration. Oral rehydration solution (ORS) and recommended home fluids (RHFs) have been recommended since 1970s and 1980s to prevent and treat diarrhoeal dehydration. We sought to estimate the effects of these interventions on diarrhoea mortality in children aged <5 years

A call for standardised age-disaggregated health data.

The 2030 Sustainable Development Goals agenda calls for health data to be disaggregated by age. However, age groupings used to record and report health data vary greatly, hindering the harmonisation, comparability, and usefulness of these data, within and across countries. This variability has become especially evident during the COVID-19 pandemic, when there was an urgent need for rapid cross-country analyses of epidemiological patterns by age to direct public health action, but such analyses were limited by the lack of standard age categories. In this Personal View, we propose a recommended set of age groupings to address this issue. These groupings are informed by age-specific patterns of morbidity, mortality, and health risks, and by opportunities for prevention and disease intervention. We recommend age groupings of 5 years for all health data, except for those younger than 5 years, during which time there are rapid biological and physiological changes that justify a finer disaggregation. Although the focus of this Personal View is on the standardisation of the analysis and display of age groups, we also outline the challenges faced in collecting data on exact age, especially for health facilities and surveillance data. The proposed age disaggregation should facilitate targeted, age-specific policies and actions for health care and disease management