Improved measurement for mothers, newborns and children in the era of the Sustainable Development Goals

[Evaluation of the effectiveness of the intervention to improve the Brazilian Mortality Information System in Pernambuco, Brazil: a quasi-experimental study]

This study evaluated the influence of the variation in the implementation of the Brazilian Mortality Information System (SIM) on the results, before and after the intervention to improve the system in Pernambuco, Brazil. The SIM logical model and matrix of indicators and assessment were described, primary data were collected from the 184 municipalities and secondary data were collected from the system database. The degree of implementation (DI) was obtained from the indicators of structure and process, and then related to result indicators, based on the model. The intervention was directed at the shortcomings identified, and developed using strategic stages. The percentage of annual variation of the DI and the results before and after the intervention were calculated. The SIM was classified as partially implemented in the pre- (70.6%) and post-intervention (73.1%) evaluations, with increments in all components. The Health Regions followed the same classification of the state level, except for XII (80.3%), regarding implemented score after the intervention. The coverage of the system; deaths with a defined underlying cause; monthly transfer; and timely submission of data were above 90% in both evaluations. There was an improvement in the completeness of infant Death Certificates and in the timely recording of notifiable events. Strengthening the management and operationalization of the SIM with interventions applied to data registration can improve the system's results.

Advocacy for Better Integration and Use of Child Health Indicators for Global Monitoring

Making better use of harmonized indicators to monitor child health and well-being at the global level will avoid duplicative monitoring and evaluation exercises, improve evidence-based programming, and preserve resources that can be used to improve the quality of national data collection platforms.

Mortality by Admission Diagnosis in Children 1-60 Months of Age Admitted to a Tertiary Care Government Hospital in Malawi

Diagnosis-specific mortality is a measure of pediatric healthcare quality that has been incompletely studied in sub-Saharan African hospitals. Identifying the mortality rates of multiple conditions at the same hospital may allow leaders to better target areas for intervention. In this secondary analysis of routinely collected data, we investigated hospital mortality by admission diagnosis in children aged 1-60 months admitted to a tertiary care government referral hospital in Malawi between October 2017 and June 2020. The mortality rate by diagnosis was calculated as the number of deaths among children admitted with a diagnosis divided by the number of children admitted with the same diagnosis. There were 24,452 admitted children eligible for analysis. Discharge disposition was recorded in 94.2% of patients, and 4.0% (N = 977) died in the hospital. The most frequent diagnoses among admissions and deaths were pneumonia/bronchiolitis, malaria, and sepsis. The highest mortality rates by diagnosis were found in surgical conditions (16.1%; 95% CI: 12.0-20.3), malnutrition (15.8%; 95% CI: 13.6-18.0), and congenital heart disease (14.5%; 95% CI: 9.9-19.2). Diagnoses with the highest mortality rates were alike in their need for significant human and material resources for medical care. Improving mortality in this population will require sustained capacity building in conjunction with targeted quality improvement initiatives against both common and deadly diseases.

Evaluations of effective coverage of maternal and child health services: A systematic review

Conventionally used coverage measures do not reflect the quality of care. Effective coverage (EC) assesses the extent to which health care services deliver potential health gains to the population by integrating concepts of utilization, need and quality. We aimed to conduct a systematic review of studies evaluating EC of maternal and child health services, quality measurement strategies and disparities across wealth quantiles. A systematic search was performed in six electronic databases [MEDLINE, EMBASE, Cumulative Index of Nursing and Allied Health (CINAHL), Scopus, Web of Science and Maternity and Infant Care] and grey literature. We also undertook a hand search of references. We developed search terms having no restrictions based on publication period, country or language. We included studies which reported EC estimates based on the World Health Organization framework of measuring EC. Twenty-seven studies, all from low- and middle-income settings (49 countries), met the criteria and were included in the narrative synthesis of the results. Maternal and child health intervention(s) and programme(s) were assessed either at an individual level or as an aggregated measure of health system performance or both. The EC ranged from 0% for post-partum care to 95% for breastfeeding. When crude coverage measures were adjusted to account for the quality of care, the EC values turned lower. The gap between crude coverage and EC was as high as 86%, and it signified a low quality of care. The assessment of the quality of care addressed structural, process and outcome domains individually or combined. The wealthiest 20% had higher EC of services than the poorest 20%, an inequitable distribution of coverage. More efforts are needed to improve the quality of maternal and child health services and to eliminate the disparities. Moreover, considering multiple dimensions of quality and the use of standard measurements are recommended to monitor coverage effectively.

World Health Organization and knowledge translation in maternal, newborn, child and adolescent health and nutrition

The World Health Organization (WHO) has a mandate to promote maternal and child health and welfare through support to governments in the form of technical assistance, standards, epidemiological and statistical services, promoting teaching and training of healthcare professionals and providing direct aid in emergencies. The Strategic and Technical Advisory Group of Experts (STAGE) for maternal, newborn, child and adolescent health and nutrition (MNCAHN) was established in 2020 to advise the Director-General of WHO on issues relating to MNCAHN. STAGE comprises individuals from multiple low-income and middle-income and high-income countries, has representatives from many professional disciplines and with diverse experience and interests.Progress in MNCAHN requires improvements in quality of services, equity of access and the evolution of services as technical guidance, community needs and epidemiology changes. Knowledge translation of WHO guidance and other guidelines is an important part of this. Countries need effective and responsive structures for adaptation and implementation of evidence-based interventions, strategies to improve guideline uptake, education and training and mechanisms to monitor quality and safety. This paper summarises STAGE's recommendations on how to improve knowledge translation in MNCAHN. They include support for national and regional technical advisory groups and subnational committees that coordinate maternal and child health; support for national plans for MNCAHN and their implementation and monitoring; the production of a small number of consolidated MNCAHN guidelines to promote integrated and holistic care; education and quality improvement strategies to support guidelines uptake; monitoring of gaps in knowledge translation and operational research in MNCAHN.

Strengthening effectiveness evaluations to improve programs for women, children and adolescents

A full understanding of the pathways from efficacious interventions to population impact requires rigorous effectiveness evaluations conducted under realistic scale-up conditions at country level. In this paper, we introduce a deductive framework that underpins effectiveness evaluations. This framework forms the theoretical and conceptual basis for the 'Real Accountability: Data Analysis for Results' (RADAR) project, intended to address gaps in guidance and tools for the evaluation of projects being implemented at scale to reduce mortality among women and children. These gaps include needs for a framework to guide decisions about evaluations and practical measurement tools, as well as increased capacity in evaluation practice among donors and program planners at global, national and project levels. RADAR aimed to improve the evidence base for program and policy decisions in reproductive, maternal, newborn and child health and nutrition (RMNCH&N). We focus on five linked methodological steps - presented as core evaluation questions - for designing and implementing effectiveness evaluation of large-scale programs that support both the needs of program managers to improve their programs and the needs of donors to meet their accountability responsibilities. RADAR has operationalized each step with a tool to facilitate its application. We also describe cross-cutting methodological issues and broader contextual factors that affect the planning and implementation of such evaluations. We conclude with proposals for how the global RMNCH&N community can support rigorous program evaluations and make better use of the resulting evidence.

A rapid systematic review and evidence synthesis of effective coverage measures and cascades for childbirth, newborn and child health in low- and middle-income countries

BACKGROUND

Effective coverage measures aim to estimate the proportion of a population in need of a service that received a positive health outcome. In 2020, the Effective Coverage Think Tank Group recommended using a 'coverage cascade' for maternal, newborn, child and adolescent health and nutrition (MNCAHN), which organises components of effective coverage in a stepwise fashion, with each step accounting for different aspects of quality of care (QoC), applied at the population level. The cascade outlines six steps that increase the likelihood that the population in need experience the intended health benefit: 1) the population in need (target population) who contact a health service; 2) that has the inputs available to deliver the service; 3) who receive the health service; 4) according to quality standards; 5) and adhere to prescribed medication(s) or health workers instructions; and 6) experience the expected health outcome. We examined how effective coverage of life-saving interventions from childbirth to children aged nine has been defined and assessed which steps of the cascade are captured by existing measures.

METHODS

We undertook a rapid systematic review. Seven scientific literature databases were searched covering the period from May 1, 2017 to July, 8 2021. Reference lists from reviews published in 2018 and 2019 were examined to identify studies published prior to May 2017. Eligible studies reported population-level contact coverage measures adjusted for at least one dimension of QoC.

RESULTS

Based on these two search approaches this review includes literature published from 2010 to 2021. From 16 662 records reviewed, 33 studies were included, reporting 64 effective coverage measures. The most frequently examined measures were for childbirth and immediate newborn care (n = 24). No studies examined measures among children aged five to nine years. Definitions of effective coverage varied across studies. Key sources of variability included (i) whether a single effective coverage measure was reported for a package of interventions or separate measures were calculated for each intervention; (ii) the number and type of coverage cascade steps applied to adjust for QoC; and (iii) the individual items included in the effective coverage definition and the methods used to generate a composite quality measure.

CONCLUSION

In the MNCAHN literature there is substantial heterogeneity in both definitions and construction of effective coverage, limiting the comparability of measures over time and place. Current measurement approaches are not closely aligned with the proposed cascade. For widespread adoption, there is a need for greater standardisation of indicator definitions and transparency in reporting, so governments can use these measures to improve investments in MNACHN and implement life-saving health policies and programs.

Operationalising effective coverage measurement of facility based childbirth in Gombe State; a comparison of data sources

Estimating effective coverage of childbirth care requires linking population based data sources to health facility data. For effective coverage to gain widespread adoption there is a need to focus on the feasibility of constructing these measures using data typically available to decision makers in low resource settings. We estimated effective coverage of childbirth care in Gombe State, northeast Nigeria, using two different combinations of facility data sources and examined their strengths and limitations for decision makers. Effective coverage captures information on four steps: access, facility inputs, receipt of interventions and process quality. We linked data from the 2018 Nigerian Demographic and Health Survey (NDHS) to two sources of health facility data: (1) comprehensive health facility survey data generated by a research project; and (2) District Health Information Software 2 (DHIS2). For each combination of data sources, we examined which steps were feasible to calculate, the size of the drop in coverage between steps and the resulting estimate of effective coverage. Analysis included 822 women with a recent live birth, 30% of whom attended a facility for childbirth. Effective coverage was low: 2% based on the project data and less than 1% using the DHIS2. Linking project data with NDHS, it was feasible to measure all four steps; using DHIS2 it was possible to estimate three steps: no data was available to measure process quality. The provision of high quality care is suboptimal in this high mortality setting where access and facility readiness to provide care, crucial foundations to the provision of high quality of care, have not yet been met. This study demonstrates that partial effective coverage measures can be constructed from routine data combined with nationally representative surveys. Advocacy to include process of care indicators in facility summary reports could optimise this data source for decision making.

Can We Use Routine Data for Strategic Decision Making? A Time Trend Comparison Between Survey and Routine Data in Mali

Routine data, which is available more regularly than the "gold standard" survey data, can be used to inform programmatic decisions in Mali at the national level. However, caution must be used if using data at a subnational level.

Background:

Countries with scarce resources need timely and high-quality data on coverage of health interventions to make strategic decisions about where to allocate investments in health. Household survey data are generally regarded as “gold standard,” high-quality data. This study assessed the comparability of intervention coverage time trends from routine and survey data at national and subnational levels in Mali.

Methods:

We compared 3 coverage indicators: contraceptive prevalence rate, institutional delivery, and 3 doses of diphtheria, pertussis, and tetanus (DPT3) vaccine, using 3 Mali Demographic and Health Surveys (DHS 2001, 2006, and 2012–2013) and routine health system data covering 2001–2012. For routine data, we used local health information system (HIS) annual reports and an HIS database. To compare time trends between the data sources, we calculated the percentage point change and 95% confidence interval from 2001–2006 and 2006–2012. We then computed the absolute and relative differences between the 2 data sources for each indicator over time at national and regional levels and assessed their level of significance.

Results:

The direction and magnitude of the time trends of contraceptive prevalence rate, institutional delivery, and DPT3 vaccine from 2001 to 2012 were similar at the national level between data sources. At the regional level, there were significant differences in the magnitude and direction of time trends for institutional delivery and the DPT3 vaccine; contraceptive prevalence trends were more consistent. Routine data tended to overestimate DPT3 coverage, and underestimate institutional delivery and contraceptive prevalence relative to survey data.

Conclusion:

Routine data in Mali—particularly at the national level—appear to be appropriate for use to inform program planning and prioritization, but routine time trends should be interpreted with caution at the subnational level. For program evaluations, routine data may not be appropriate to draw accurate inferences about program impact.

A Call to Action: Reinvigorating Interest and Investments in Health Infrastructure

Infrastructure investments can contribute substantially to alleviating burdens of morbidity and mortality while also providing a positive return on investment in the long term.

Assessment of the validity of the measurement of newborn and maternal health-care coverage in hospitals (EN-BIRTH): an observational study

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 design and information systems has the potential to sustainably improve the quality of data on care at birth.

FUNDING

Children's Investment Fund Foundation and Swedish Research Council.

Helping Babies Survive Programs as an Impetus for Quality Improvement

Achieving the ambitious reduction in global neonatal mortality targeted in the Sustainable Development Goals and Every Newborn Action Plan will require reducing geographic disparities in newborn deaths through targeted implementation of evidence-based practices. Helping Babies Survive, a suite of educational programs targeting the 3 leading causes of neonatal mortality, has been commonly used to educate providers in evidence-based practices in low-resource settings. Quality improvement (QI) can play a pivotal role in translating this education into improved care. Measurement of key process and outcome indicators, derived from the algorithms ("Action Plans") central to these training programs, can assist health care providers in understanding the baseline quality of their care, identifying gaps, and assessing improvement. Helping Babies Survive has been the focus of QI programs in Kenya, Nepal, Honduras, and Ethiopia, with critical lessons learned regarding the challenge of measurement, necessity of facility-based QI mentorship and multidisciplinary teams, and importance of systemic commitment to improvement in promoting a culture of QI. Complementing education with QI strategies to identify and close remaining gaps in newborn care will be essential to achieving the Sustainable Development Goals and Every Newborn Action Plan targets in the coming decade.

Coverage and equity of maternal and newborn health care in rural Nigeria, Ethiopia and India

BACKGROUND

Despite progress toward meeting the Sustainable Development Goals, a large burden of maternal and neonatal mortality persists for the most vulnerable people in rural areas. We assessed coverage, coverage change and inequity for 8 maternal and newborn health care indicators in parts of rural Nigeria, Ethiopia and India.

METHODS

We examined coverage changes and inequity in 2012 and 2015 in 3 high-burden populations where multiple actors were attempting to improve outcomes. We conducted cluster-based household surveys using a structured questionnaire to collect 8 priority indicators, disaggregated by relative household socioeconomic status. Where there was evidence of a change in coverage between 2012 and 2015, we used binomial regression models to assess whether the change reduced inequity.

RESULTS

In 2015, we interviewed women with a birth in the previous 12 months in Gombe, Nigeria (n = 1100 women), Ethiopia (n = 404) and Uttar Pradesh, India (n = 584). Among the 8 indicators, 2 positive coverage changes were observed in each of Gombe and Uttar Pradesh, and 5 in Ethiopia. Coverage improvements occurred equally for all socioeconomic groups, with little improvement in inequity. For example, in Ethiopia, coverage of facility delivery almost tripled, increasing from 15% (95% confidence interval [CI] 9%-25%) to 43% (95% CI 33%-54%). This change was similar across socioeconomic groups (p = 0.2). By 2015, the poorest women had about the same facility delivery coverage as the least poor women had had in 2012 (32% and 36%, respectively), but coverage for the least poor had increased to 60%.

INTERPRETATION

Although coverage increased equitably because of various community-based interventions, underlying inequities persisted. Action is needed to address the needs of the most vulnerable women, particularly those living in the most rural areas.

Determinants and patterns of care-seeking for childhood illness in rural Pune District, India

BACKGROUND

An estimated 1.2 million children under five years of age die each year in India, with pneumonia and diarrhea among the leading causes. Increasing care-seeking is important to reduce mortality and morbidity from these causes. This paper explores the determinants and patterns of care-seeking for childhood illness in rural Pune district, India.

METHODS

Mothers having at least one child <5 years from the study area of the Vadu Health and Demographic Surveillance System were enrolled in a prospective cohort study. Household sociodemographic information was collected through a baseline questionnaire administered at enrollment. Participants were visited up to six times between July 2015 and February 2016 to collect information on recent childhood acute illness and associated care-seeking behavior. Multivariate logistic regression explored the associations between care-seeking and child, participant, and household characteristics.

RESULTS

We enrolled 743 mothers with 1066 eligible children, completing 2585 follow-up interviews (90% completion). Overall acute illness prevalence in children was 26% with care sought from a health facility during 71% of episodes. Multivariable logistic regression showed care-seeking was associated with the number of reported symptoms (Odds ratio (OR) = 2.4, 95% confidence interval (CI) = 1.5-3.9) and household insurance coverage (OR = 2.2, 95% CI = 1.1-4.3). We observed an interaction between the associations of illness severity and maternal employment on care-seeking. Somewhat-to-very severe illness was associated with increased care-seeking among both employed (OR = 5.0, 95% CI = 2.2-11.1) and currently unemployed mothers (OR = 7.0, 95% CI = 3.9-12.6). Maternal employment was associated with reduced care-seeking for non-severe illness (OR = 0.3, 95% CI = 0.1-0.7), but not associated with care-seeking for somewhat-to-very severe illness. Child sex was not associated with care-seeking.

CONCLUSIONS

This study demonstrates the importance of illness characteristics in determining facility-based care-seeking while also suggesting that maternal employment resulted in decreased care-seeking among non-severe illness episodes. The nature of the association between maternal employment and care-seeking is unclear and should be explored through additional studies. Similarly, the absence of male bias in care-seeking should be examined to assess for potential bias at other stages in the management of childhood illness.

Assessing capacity of health facilities to provide routine maternal and newborn care in low-income settings: what proportions are ready to provide good-quality care, and what proportions of women receive it?

Background

Good quality maternal and newborn care at primary health facilities is essential, but in settings with high maternal and newborn mortality the evidence for the protective effect of facility delivery is inconsistent. We surveyed samples of health facilities in three settings with high maternal mortality to assess their readiness to provide routine maternal and newborn care, and proportions of women using facilities that were ready to offer good quality care. Surveys were conducted in 2012 and 2015 to assess changes over time.

Methods

Surveys were conducted in Ethiopia, the Indian state of Uttar Pradesh and Gombe State in North-Eastern Nigeria. At each facility the staffing, infrastructure and commodities were quantified. These formed components of four “signal functions” that described aspects of routine maternal and newborn care. A facility was considered ready to perform a signal function if all the required components were present. Readiness to perform all four signal functions classed a facility as ready to provide good quality routine care. From facility registers we counted deliveries and calculated the proportions of women delivering in facilities ready to offer good quality routine care.

Results

In Ethiopia the proportion of deliveries in facilities classed as ready to offer good quality routine care rose from 40% (95% confidence interval (CI) 26–57) in 2012 to 43% (95% CI 31–56) in 2015. In Uttar Pradesh these estimates were 4% (95% CI 1–24) in 2012 and 39% (95% CI 25–55) in 2015, while in Nigeria they were 25% (95% CI 6–66) in 2012 and zero in 2015. Improved facility readiness in Ethiopia and Uttar Pradesh arose from increased supplies of commodities, while in Nigeria facility readiness fell due to depleted commodity supplies and fewer Skilled Birth Attendants.

Conclusions

This study quantified the readiness of health facilities to offer good quality routine maternal and newborn care, and may help explain inconsistent outcomes of facility care in some settings. Signal function methodology can provide a rapid and inexpensive measure of such facility readiness. Incorporating data on facility deliveries and repeating the analyses highlighted adjustments that could have greatest impact upon routine maternal and newborn care.

"What gets measured better gets done better": The landscape of validation of global maternal and newborn health indicators through key informant interviews

Background

A large number of indicators are currently used to monitor the state of maternal and newborn health, including those capturing dimensions of health system and input, care access and availability, care quality and safety, coverage and outcomes, and impact. Validity of these indicators is a key issue in the process of assessing indicator performance and suitability. This paper aims to understand the meaning of indicator validity in the field of maternal and newborn health, and to identify key recommendations for future research.

Methods

This qualitative study used purposive sampling to identify key informants until thematic saturation was achieved. We interviewed 32 respondents from a variety of backgrounds using semi-structured interviews covering five themes: the meaning of indicator validity, methodological approaches to assessing validity, acceptable levels of indicator validity, gaps in validation research, and recommendations for addressing these gaps. Interview transcripts were analysed data using thematic content approach.

Results

Three conceptually different definitions of indicator validity were described by respondents. They considered indicator validity to encompass meaning and potential to spur action, going beyond diagnostic validity. Indicator validation was seen as an ongoing process of building and synthesising a wide range of evidence rather than a one-size-fits-all cut-off in diagnostic validity tests. Gaps identified included assessing validity of indicators of quality of care and indicators based on facility-level data, as well as expanding studies to a broader range of global settings. The key recommendation was to develop a coordinated approach to summarising and evaluating research on indicator validity, including capacity building in appraising and communicating the available evidence for country-specific needs.

Conclusion

The findings will inform future recommendations around indicator testing and validation.

Implementation of an international standardized set of outcome indicators in pregnancy and childbirth in Kenya: Utilizing mobile technology to collect patient-reported outcomes

Background

Limited data exist on health outcomes during pregnancy and childbirth in low- and middle-income countries. This is a pilot of an innovative data collection tool using mobile technology to collect patient-reported outcome measures (PROMs) selected from the International Consortium of Health Outcomes Measurement (ICHOM) Pregnancy and Childbirth Standard Set in Nairobi, Kenya.

Methods

Pregnant women in the third trimester were recruited at three primary care facilities in Nairobi and followed prospectively throughout delivery and until six weeks postpartum. PROMs were collected via mobile surveys at three antenatal and two postnatal time points. Outcomes included incontinence, dyspareunia, mental health, breastfeeding and satisfaction with care. Hospitals reported morbidity and mortality. Descriptive statistics on maternal and child outcomes, survey completion and follow-up rates were calculated.

Results

In six months, 204 women were recruited: 50% of women returned for a second ante-natal care visit, 50% delivered at referral hospitals and 51% completed the postnatal visit. The completion rates for the five PROM surveys were highest at the first antenatal care visit (92%) and lowest in the postnatal care visit (38%). Data on depression, dyspareunia, fecal and urinary incontinence were successfully collected during the antenatal and postnatal period. At six weeks postpartum, 86% of women breastfeed exclusively. Most women that completed the survey were very satisfied with antenatal care (66%), delivery care (51%), and post-natal care (60%).

Conclusion

We have demonstrated that it is feasible to use mobile technology to follow women throughout pregnancy, track their attendance to pre-natal and post-natal care visits and obtain data on PROM. This study demonstrates the potential of mobile technology to collect PROM in a low-resource setting. The data provide insight into the quality of maternal care services provided and will be used to identify and address gaps in access and provision of high quality care to pregnant women.

Effective coverage of facility delivery in Bangladesh, Haiti, Malawi, Nepal, Senegal, and Tanzania

BACKGROUND

The persistence of preventable maternal and newborn deaths highlights the importance of quality of care as an essential element in coverage interventions. Moving beyond the conventional measurement of crude coverage, we estimated effective coverage of facility delivery by adjusting for facility preparedness to provide delivery services in Bangladesh, Haiti, Malawi, Nepal, Senegal, and Tanzania.

METHODS

The study uses data from Demographic and Health Surveys (DHS) and Service Provision Assessments (SPA) in Bangladesh (2014 DHS and 2014 SPA), Haiti (2012 DHS and 2013 SPA), Malawi (2015-16 DHS and 2013-14 SPA), Nepal (2016 DHS and 2015 SPA), Senegal (2016 DHS and 2015 SPA), and Tanzania (2015-16 DHS and 2014-15 SPA). We defined effective coverage as the mathematical product of crude coverage and quality of care. The coverage of facility delivery was measured with DHS data and quality of care was measured with facility data from SPA. We estimated effective coverage at both the regional and the national level and accounted for type of facility where delivery care was sought.

FINDINGS

The findings from the six countries indicate the effective coverage ranges from 24% in Haiti to 66% in Malawi, representing substantial reductions (20% to 39%) from crude coverage rates. Although Malawi has achieved almost universal coverage of facility delivery (93%), effective coverage was only 66%.vSuch gaps between the crude coverage and the effective coverage suggest that women delivered in health facility but did not necessarily receive an adequate quality of care. In all countries except Malawi, effective coverage differed substantially among the country's regions of the country, primarily due to regional variability in coverage.

INTERPRETATION

Our findings reinforce the importance of quality of obstetric and newborn care to achieve further reduction of maternal and newborn mortality. Continued efforts are needed to increase the use of facility delivery service in countries or regions where coverage remains low.

Understanding client and provider perspectives of antenatal care service quality: a qualitative multi-method study from Tanzania

BACKGROUND

Measures of quality of care in low- and middle-income countries (LMICs) rarely include experience of care. This gap in service quality metrics may be driven by a lack of understanding of client and provider perspectives. Understanding these perspectives is a critical first step in not only improving metrics, but also in improving service delivery. This study identifies the items antenatal care (ANC) clients and health care providers in Tanzania associate with a quality ANC service and explores the experience of care domain from both client and provider perspectives.

METHODS

We conducted semi-structured interviews with15 providers and 35 clients in Tanzania that included a free-listing activity to elicit items clients and providers associate with quality ANC services. We analyzed the free-listing for rank order and frequency to identify the most salient items, which were included in the second phase of data collection. We then conducted semi-structured interviews with a pile sort activity with the same 15 providers and 32 new clients to understand the importance of the items identified in the free-listing. We used a thematic analysis driven by the framework approach to analyze interview data.

RESULTS

Both clients and providers perceived quality of ANC as being comprised of items related to experience of care, provision of care, and cross-cutting essential physical and human resources. The free-listing findings illuminated that the experience of care was equally important to clients and providers as the availability of physical and human resources and the content of the care delivered. In addition, clients and providers perceived that a positive patient care experience - marked by good communication, active listening, keeping confidentiality, and being spoken to politely - increased utilization of health services and improved health outcomes.

CONCLUSIONS

The experience of care in LMICs is an overlooked, yet critically important topic. Understanding the experience of care from those who receive and deliver services is key to measuring and improving the quality of ANC. Our research highlights the importance of incorporating experience of care into future quality improvement activities and quality measures. By doing so, we identify barriers and facilitating factors of practical use to policy-makers and governments in LMICs.

'Who assisted with the delivery of (NAME)?' Issues in estimating skilled birth attendant coverage through population-based surveys and implications for improving global tracking

The percentage of live births attended by a skilled birth attendant (SBA) is a key global indicator and proxy for monitoring progress in maternal and newborn health. Yet, the discrepancy between rising SBA coverage and non-commensurate declines in maternal and neonatal mortality in many low-income and middle-income countries has brought increasing attention to the challenge of what the indicator of SBA coverage actually measures, and whether the indicator can be improved. In response to the 2018 revised definition of SBA and the push for improved measurement of progress in maternal and newborn health, this paper examines the evidence on what women can tell us about who assisted them during childbirth and methodological issues in estimating SBA coverage via population-based surveys. We present analyses based on Demographic and Health Surveys and Multiple Indicator Cluster Surveys conducted since 2015 for 23 countries. Our findings show SBA coverage can be reasonably estimated from population-based surveys in settings of high coverage, though women have difficulty reporting specific cadres. We propose improvements in how skilled cadres are classified and documented, how linkages can be made to facility-based data to examine the enabling environment and further ways data can be disaggregated to understand the complexity of delivery care. We also reflect on the limitations of what SBA coverage reveals about the quality and circumstances of childbirth care. While improvements to the indicator are possible, we call for the use of multiple indicators to inform local efforts to improve the health of women and newborns.

Indicators for monitoring maternal and neonatal quality care: a systematic review

BACKGROUND

Research and different organizations have proposed indicators to monitor the quality of maternal and child healthcare, such indicators are used for different purposes.

OBJECTIVE

To perform a systematic review of indicators for the central phases of the maternal and child healthcare continuum of care (pregnancy, childbirth, newborn care and postpartum).

METHOD

A search conducted using international repositories, national and international indicator sets, scientific articles published between 2012 and 2016, and grey literature. The eligibility criteria was documents in Spanish or English with indicators to monitor aspects of the continuum of care phases of interest. The identified indicators were characterized as follows: formula, justification, evidence level, pilot study, indicator type, phase of the continuum, intended organizational level of application, level of care, and income level of the countries. Selection was based on the characteristics associated with scientific soundness (formula, evidence level, and reliability).

RESULTS

We identified 1791 indicators. Three hundred forty-six were duplicated, which resulted in 1445 indicators for analysis. Only 6.7% indicators exhibited all requirements for scientific soundness. The distribution by the classifying variables is clearly uneven, with a predominance of indicators for childbirth, hospital care and facility level.

CONCLUSIONS

There is a broad choice of indicators for maternal and child healthcare. However, most indicators lack demonstrated scientific soundness and refer to particular continuum phases and levels within the healthcare system. Additional efforts are needed to identify good indicators for a comprehensive maternal and child healthcare monitoring system.

Linking household survey and health facility data for effective coverage measures: a comparison of ecological and individual linking methods using the Multiple Indicator Cluster Survey in Côte d'Ivoire

Background

Population-based measures of intervention coverage are used in low- and middle-income countries for program planning, prioritization, and evaluation. There is increased interest in effective coverage, which integrates information about service quality or health outcomes. Approaches proposed for quality-adjusted effective coverage include linking data on need and service contact from population-based surveys with data on service quality from health facility surveys. However, there is limited evidence about the validity of different linking methods for effective coverage estimation.

Methods

We collaborated with the 2016 Côte d'Ivoire Multiple Indicator Cluster Survey (MICS) to link data from a health provider assessment to care-seeking data collected by the MICS in the Savanes region of Côte d'Ivoire. The provider assessment was conducted in a census of public and non-public health facilities and pharmacies in Savanes in May-June 2016. We also included community health workers managing sick children who served the clusters sampled for the MICS. The provider assessment collected information on structural and process quality for antenatal care, delivery and immediate newborn care, postnatal care, and sick child care. We linked the MICS and provider data using exact-match and ecological linking methods, including aggregate linking and geolinking methods. We compared the results obtained from exact-match and ecological methods.

Results

We linked 731 of 786 care-seeking episodes (93%) from the MICS to a structural quality score for the provider named by the respondent. Effective coverage estimates computed using exact-match methods were 13%-63% lower than the care-seeking estimates from the MICS. Absolute differences between exact match and ecological linking methods were ±7 percentage points for all ecological methods. Incorporating adjustments for provider category and weighting by service-specific utilization into the ecological methods generally resulted in better agreement between ecological and exact match estimates.

Conclusions

Ecological linking may be a feasible and valid approach for estimating quality-adjusted effective coverage when a census of providers is used. Adjusting for provider type and caseload may improve agreement with exact match results. There remain methodological questions to be addressed to develop guidance on using linking methods for estimating quality-adjusted effective coverage, including the effect of facility sampling and time displacement.

Newborn resuscitation in Gombe State, northeastern Nigeria

Background

Basic newborn resuscitation for babies not breathing at birth is a highly effective intervention and its scale-up identified as a top research priority. However, tracking progress on the scale-up and coverage of this intervention is compromised by limitations in measuring both the number of newborns receiving the intervention and the number of newborns requiring the intervention. Using data from a facility and birth attendant survey in Gombe State, Nigeria, we aimed to advance the measurement agenda by developing a proxy indicator defined as the "percent of newborns born in a facility with the potential to provide newborn resuscitation".

Methods

The indicator's denominator was defined as: the total number of births in facilities during a defined time period (facility records). The numerator was constructed from the number of those births that occurred in appropriately equipped facilities (facility inventory), where a birth attendant demonstrated basic resuscitation competence (assessed by a simulation exercise). The proportion of facility-births that took place in a setting with the potential to provide newborn resuscitation was then calculated.

Results

The analysis included 17 383 births that occurred during May-October 2015 in 117 primary and referral facilities surveyed in November 2015. Overall 81% of the facilities did not have all items of essential equipment required for resuscitation; the items of equipment least frequently present included a timing device and resuscitation bag with two sizes of neonatal face mask. Only 3% of 117 birth attendants interviewed demonstrated competence to undertake resuscitation, all of whom were classified as skilled attendants and worked in referral facilities. We found that 20% of the 17 383 births took place in a facility with the potential to provide lifesaving resuscitation care.

Conclusions

The indicator definition of neonatal resuscitation presented here responds to the need to advance the measurement agenda for newborn care and importantly adjusts for the volume of births occurring in different facilities. Its application in this setting revealed substantial missed opportunities to providing lifesaving care and highlights the need for a greater focus on input as well as process quality in all levels of health facilities.

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.

Ethnic group inequalities in coverage with reproductive, maternal and child health interventions: cross-sectional analyses of national surveys in 16 Latin American and Caribbean countries

BACKGROUND

Latin American and Caribbean populations include three main ethnic groups: indigenous people, people of African descent, and people of European descent. We investigated ethnic inequalities among these groups in population coverage with reproductive, maternal, newborn, and child health interventions.

METHODS

We analysed 16 standardised, nationally representative surveys carried out from 2004 to 2015 in Latin America and the Caribbean that provided information on ethnicity or a proxy indicator (household language or skin colour) and on coverage of reproductive, maternal, newborn, and child health interventions. We selected four outcomes: coverage with modern contraception, antenatal care coverage (defined as four or more antenatal visits), and skilled attendants at birth for women aged 15-49 years; and coverage with three doses of diphtheria-pertussis-tetanus (DPT3) vaccine among children aged 12-23 months. We classified women and children as indigenous, of African descent, or other ancestry (reference group) on the basis of their self-reported ethnicity or language. Mediating variables included wealth quintiles (based on household asset indices), woman's education, and urban-rural residence. We calculated crude and adjusted coverage ratios using Poisson regression.

FINDINGS

Ethnic gaps in coverage varied substantially from country to country. In most countries, coverage with modern contraception (median coverage ratio 0·82, IQR 0·66-0·92), antenatal care (0·86, 0·75-0·94), and skilled birth attendants (0·75, 0·68-0·92) was lower among indigenous women than in the reference group. Only three countries (Nicaragua, Panama, and Paraguay) showed significant gaps in DPT3 coverage between the indigenous and the reference groups. The differences were attenuated but persisted after adjustment for wealth, education, and residence. Women and children of African descent showed similar coverage to the reference group in most countries.

INTERPRETATION

The lower coverage levels for indigenous women are pervasive, and cannot be explained solely by differences in wealth, education, or residence. Interventions delivered at community level-such as vaccines-show less inequality than those requiring access to services, such as birth attendance. Regular monitoring of ethnic inequalities is essential to evaluate existing initiatives aimed at the inclusion of minorities and to plan effective multisectoral policies and programmes.

FUNDING

The Bill & Melinda Gates Foundation (through the Countdown to 2030 initiative) and the Wellcome Trust.

Linking household and health facility surveys to assess obstetric service availability, readiness and coverage: evidence from 17 low- and middle-income countries

Background

Improving access and quality of obstetric service has the potential to avert preventable maternal, neonatal and stillborn deaths, yet little is known about the quality of care received. This study sought to assess obstetric service availability, readiness and coverage within and between 17 low- and middle-income countries.

Methods

We linked health facility data from the Service Provision Assessments and Service Availability and Readiness Assessments, with corresponding household survey data obtained from the Demographic and Health Surveys and Multiple Indicator Cluster Surveys. Based on performance of obstetric signal functions, we defined four levels of facility emergency obstetric care (EmOC) functionality: comprehensive (CEmOC), basic (BEmOC), BEmOC-2, and low/substandard. Facility readiness was evaluated based on the direct observation of 23 essential items; facilities “ready to provide obstetric services” had ≥20 of 23 items available. Across countries, we used medians to characterize service availability and readiness, overall and by urban-rural location; analyses also adjusted for care-seeking patterns to estimate population-level coverage of obstetric services.

Results

Of the 111 500 health facilities surveyed, 7545 offered obstetric services and were included in the analysis. The median percentages of facilities offering EmOC and “ready to provide obstetric services” were 19% and 10%, respectively. There were considerable urban-rural differences, with absolute differences of 19% and 29% in the availability of facilities offering EmOC and “ready to provide obstetric services”, respectively. Adjusting for care-seeking patterns, results from the linking approach indicated that among women delivering in a facility, a median of 40% delivered in facilities offering EmOC, and 28% delivered in facilities “ready to provide obstetric services”. Relatively higher coverage of facility deliveries (≥65%) and coverage of deliveries in facilities “ready to provide obstetric services” (≥30% of facility deliveries) were only found in three countries.

Conclusions

The low levels of availability, readiness and coverage of obstetric services documented represent substantial missed opportunities within health systems. Global and national efforts need to prioritize upgrading EmOC functionality and improving readiness to deliver obstetric service, particularly in rural areas. The approach of linking health facility and household surveys described here could facilitate the tracking of progress towards quality obstetric care.

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.

Countdown to 2030: tracking progress towards universal coverage for reproductive, maternal, newborn, and child health

Building upon the successes of Countdown to 2015, Countdown to 2030 aims to support the monitoring and measurement of women's, children's, and adolescents' health in the 81 countries that account for 95% of maternal and 90% of all child deaths worldwide. To achieve the Sustainable Development Goals by 2030, the rate of decline in prevalence of maternal and child mortality, stillbirths, and stunting among children younger than 5 years of age needs to accelerate considerably compared with progress since 2000. Such accelerations are only possible with a rapid scale-up of effective interventions to all population groups within countries (particularly in countries with the highest mortality and in those affected by conflict), supported by improvements in underlying socioeconomic conditions, including women's empowerment. Three main conclusions emerge from our analysis of intervention coverage, equity, and drivers of reproductive, maternal, newborn, and child health (RMNCH) in the 81 Countdown countries. First, even though strong progress was made in the coverage of many essential RMNCH interventions during the past decade, many countries are still a long way from universal coverage for most essential interventions. Furthermore, a growing body of evidence suggests that available services in many countries are of poor quality, limiting the potential effect on RMNCH outcomes. Second, within-country inequalities in intervention coverage are reducing in most countries (and are now almost non-existent in a few countries), but the pace is too slow. Third, health-sector (eg, weak country health systems) and non-health-sector drivers (eg, conflict settings) are major impediments to delivering high-quality services to all populations. Although more data for RMNCH interventions are available now, major data gaps still preclude the use of evidence to drive decision making and accountability. Countdown to 2030 is investing in improvements in measurement in several areas, such as quality of care and effective coverage, nutrition programmes, adolescent health, early childhood development, and evidence for conflict settings, and is prioritising its regional networks to enhance local analytic capacity and evidence for RMNCH.

Psychosocial stimulation interventions for children with severe acute malnutrition: a systematic review

Background

The WHO Guidelines for the inpatient treatment of severely malnourished children include a recommendation to provide sensory stimulation or play therapy for children with severe acute malnutrition (SAM). This systematic review was performed to synthesize evidence around this recommendation. Specifically, the objective was to answer the question: “In children with severe acute malnutrition, does psychosocial stimulation improve child developmental, nutritional, or other outcomes?”

Methods

A review protocol was registered on the International Prospective Register of Systematic Reviews (PROSPERO 2016: CRD42016036403). MEDLINE, Embase, CINAHL, and PsycINFO were searched with terms related to SAM and psychosocial stimulation. Studies were selected if they applied a stimulation intervention in children with SAM and child developmental and nutritional outcomes were assessed. Findings were presented within a narrative synthesis and a summary of findings table. Quality of the evidence was evaluated using the Cochrane risk of bias tool and the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach.

Findings

Only two studies, both non–randomized controlled trials, met the selection criteria for this review. One was conducted in Jamaica (1975) with a follow–up period of 14 years; the other was done in Bangladesh (2002) with a six–month follow–up. At the individual study level, each of the included studies demonstrated significant differences in child development outcomes between intervention and control groups. Only the study conducted in Bangladesh demonstrated a clinically significant increase in weight–for–age z–scores in the intervention group compared to the control group.

Conclusions

The evidence supporting the recommendation of psychosocial stimulation for children with SAM is not only sparse, but also of very low quality across important outcomes. High–quality trials are needed to determine the effects of psychosocial stimulation interventions on outcomes in children with SAM.

'What gets measured gets managed': revisiting the indicators for maternal and newborn health programmes

Background

The health of women and children are critical for global development. The Sustainable Development Goals (SDG) agenda and the Global Strategy for Women’s, Children’s, and Adolescent’s Health 2016–2030 aim to reduce maternal and newborn deaths, disability, and enhancement of well-being. However, information and data on measuring countries’ progress are limited given the variety of methodological challenges of measuring care around the time of birth, when most maternal and neonatal deaths and morbidities occur.

Main body

In 2015, the World Health Organization launched Mother and Newborn Information for Tracking Outcomes and Results (MoNITOR), a technical advisory group to WHO. MoNITOR comprises 14 independent global experts from a variety of disciplines selected in a competitive process for their technical expertise and regional representation. MoNITOR will provide technical guidance to WHO to ensure harmonized guidance, messages, and tools so that countries can collect useful data to track progress toward achieving the Sustainable Development Goals.

Short conclusion

Ultimately, MoNITOR will provide technical guidance to WHO to ensure harmonized guidance, messages, and tools so that countries can collect useful data to track progress toward achieving the Sustainable Development Goals.

Linking household surveys and health facility assessments to estimate intervention coverage for the Lives Saved Tool (LiST)

Background

Calls have been made for improved measurement of coverage for maternal, newborn and child health interventions. Recently, methods linking household and health facility surveys have been used to improve estimation of intervention coverage. However, linking methods rely the availability of household and health facility surveys which are temporally matched. Because nationally representative health facility assessments are not yet routinely conducted in many low and middle income countries, estimates of intervention coverage based on linking methods can be produced for only a subset of countries. Estimates of intervention coverage are a critical input for modelling the health impact of intervention scale-up in the Lives Saved Tool (LiST). The purpose of this study was to develop a data-driven approach to estimate coverage for a subset of antenatal care interventions modeled in LiST.

Methods

Using a five-step process, estimates of population level coverage for syphilis detection and treatment, case management of diabetes, malaria infection, hypertensive disorders, and pre-eclampsia, were computed by linking household and health facility surveys. Based on data characterizing antenatal care and estimates of coverage derived from the linking approach, predictive models for intervention coverage were developed. Updated estimates of coverage based on the predictive models were compared, first with current default proxies, then with estimates based on the linking approach. Model fit and accuracy were assessed using three measures: the coefficient of determination, Pearson’s correlation coefficient, and the root mean square error (RMSE).

Results

The ability to predict intervention coverage was fairly accurate across all interventions considered. Predictive models accounted for 20–63% of the variance in intervention coverages, and correlation coefficients ranged from 0.5 to 0.83. The predictive model used to estimate coverage of management of pre-eclampsia performed relatively better (RMSE = 0.11) than the model estimating coverage of diabetes case management (RMSE = 0.19).

Conclusions

The new approach to estimate coverage represents an improvement over current default proxies in LiST. As the availability of reliable coverage data improves, impact estimates generated by LiST will improve. This study underscores the need for continued efforts to improve coverage measurement, while bringing to the fore the importance of health facility assessments as complementary data sources.

Electronic supplementary material

The online version of this article (10.1186/s12889-017-4743-4) contains supplementary material, which is available to authorized users.