Data-driven decision-making for district health management: a cluster-randomised study in 24 districts of Ethiopia.

BACKGROUND: Use of local data for health system planning and decision-making in maternal, newborn and child health services is limited in low-income and middle-income countries, despite decentralisation and advances in data gathering. An improved culture of data-sharing and collaborative planning is needed. The Data-Informed Platform for Health is a system-strengthening strategy which promotes structured decision-making by district health officials using local data. Here, we describe implementation including process evaluation at district level in Ethiopia, and evaluation through a cluster-randomised trial. METHODS: We supported district health teams in 4-month cycles of data-driven decision-making by: (a) defining problems using a health system framework; (b) reviewing data; (c) considering possible solutions; (d) value-based prioritising; and (e) a consultative process to develop, commit to and follow up on action plans. 12 districts were randomly selected from 24 in the North Shewa zone of Ethiopia between October 2020 and June 2022. The remaining districts formed the trial's comparison arm. Outcomes included health information system performance and governance of data-driven decision-making. Analysis was conducted using difference-in-differences. RESULTS: 58 4-month cycles were implemented, four or five in each district. Each focused on a health service delivery challenge at district level. Administrators' practice of, and competence in, data-driven decision-making showed a net increase of 77% (95% CI: 40%, 114%) in the regularity of monthly reviews of service performance, and 48% (95% CI: 9%, 87%) in data-based feedback to health facilities. Statistically significant improvement was also found in administrators' use of information to appraise services. Qualitative findings also suggested that district health staff reported enhanced data use and collaborative decision-making. CONCLUSIONS: This study generated robust evidence that 20 months' implementation of the Data-Informed Platform for Health strengthened health management through better data use and appraisal practices, systemised problem analysis to follow up on action points and improved stakeholder engagement. TRIAL REGISTRATION NUMBER: NCT05310682.

"We don't trust all data coming from all facilities": factors influencing the quality of care network data quality in Ethiopia.

BACKGROUND: Good quality data are a key to quality health care. In 2017, WHO has launched the Quality of Care Network (QCN) to reduce maternal, newborn and stillbirth mortality via learning and sharing networks. Guided by the principle of equity and dignity, the network members agreed to implement the programme in 2017-2021. OBJECTIVE: This paper seeks to explore how QCN has contributed to improving data quality and to identify factors influencing quality of data in Ethiopia. METHODS: We conducted a qualitative study in selected QCN facilities in Ethiopia using key informant interview and observation methods. We interviewed 40 people at national, sub-national and facility levels. Non-participant observations were carried out in four purposively selected health facilities; we accessed monthly reports from 41 QCN learning facilities. A codebook was prepared following a deductive and inductive analytical approach, coded using Nvivo 12 and thematically analysed. RESULTS: There was a general perception that QCN had improved health data documentation and use in the learning facilities, achieved through coaching, learning and building from pre-existing initiatives. QCN also enhanced the data elements available by introducing a broader set of quality indicators. However, the perception of poor data quality persisted. Factors negatively affecting data quality included a lack of integration of QCN data within routine health system activities, the perception that QCN was a pilot, plus a lack of inclusive engagement at different levels. Both individual and system capabilities needed to be strengthened. CONCLUSION: There is evidence of QCN's contribution to improving data awareness. But a lack of inclusive engagement of actors, alignment and limited skill for data collection and analysis continued to affect data quality and use. In the absence of new resources, integration of new data activities within existing routine health information systems emerged as the most important potential action for positive change.

How valid are women's reports of the antenatal health services they receive from Community Health Workers in Gombe State north-eastern Nigeria?

BACKGROUND: Community health workers (CHWs) in low- and middle-income countries are key to increasing coverage of maternal and newborn interventions through home visits to counsel families about healthy behaviours. Household surveys enable tracking the progress of CHW programmes but recent evidence questions the accuracy of maternal reports. We measured the validity of women's responses about the content of care they received during CHW home visits and examined whether the accuracy of women's responses was affected by CHW counselling skills. METHODS: We conducted a criterion validity study in 2019, in Gombe State-Nigeria, and collected data from 362 pregnant women. During accompanied CHW home visits the content of CHW care and the presence or absence of 18 positive counselling skills were observed and documented by a researcher. In a follow-up interview three months later, the same women were asked about the care received during the CHW home visit. Women's reports were compared with observation data and the sensitivity, specificity, and area under receiver curve (AUC) calculated. We performed a covariate validity analysis that adjusted for a counselling skill score to assess the variation in accuracy of women's reports with CHW counselling skills. RESULTS: Ten indicators were included in the validity analysis. Women consistently overestimated the content of care CHWs provided and no indicator met the condition for individual-level accuracy set at AUC ≥ 0.6. The CHW counselling skill score ranged from 9-18 points from a possible 18, with a mean of 14.3; checking on client history or concerns were the most frequently missed item. There was evidence that unmarried women and the relatively most poor women received less skilled counselling than other women (mean counselling scores of 13.2 and 13.7 respectively). There was no consistent evidence of an association between higher counselling skill scores and better accuracy of women's reports. CONCLUSIONS: The validity of women's responses about CHW care content was poor and consistently overestimated coverage. We discuss several challenges in applying criterion validity study methods to examine measures of community-based care and make only cautious interpretation of the findings that may be relevant to other researchers interested in developing similar studies.

Improving maternal and newborn health services in Northeast Nigeria through a government-led partnership of stakeholders: a quasi-experimental study.

OBJECTIVES: This study aimed to quantify change in the coverage, quality and equity of essential maternal and newborn healthcare interventions in Gombe state, Northeast Nigeria, following a four year, government-led, maternal and newborn health intervention. DESIGN: Quasi-experimental plausibility study. Repeat cross-sectional household and linked health facility surveys were implemented in intervention and comparison areas. SETTING: Gombe state, Northeast Nigeria. PARTICIPANTS: Each household survey included a sample of 1000 women aged 13-49 years with a live birth in the previous 12 months. Health facility surveys comprised a readiness assessment and birth attendant interview. INTERVENTIONS: Between 2016-2019 a complex package of evidence-based interventions was implemented to increase access, use and quality of maternal and newborn healthcare, spanning the six WHO health system building blocks. OUTCOME MEASURES: Eighteen indicators of maternal and newborn healthcare. RESULTS: Between 2016 and 2019, the coverage of all indicators improved in intervention areas, with the exception of postnatal and postpartum contacts, which remained below 15%. Greater improvements were observed in intervention than comparison areas for eight indicators, including coverage of at least one antenatal visit (71% (95% CI 62 to 68) to 88% (95% CI 82 to 93)), at least four antenatal visits (46% (95% CI 39 to 53) to 69% (95% CI 60 to 75)), facility birth (48% (95% CI 37 to 59) to 64% (95% CI 54 to 73)), administration of uterotonics (44% (95% CI 34 to 54) to 59% (95% CI 50 to 67)), delayed newborn bathing (44% (95% CI 36 to 52) to 62% (95% CI 52 to 71)) and clean cord care (42% (95% CI 34 to 49) to 73% (95% CI 66 to 79)). Wide-spread inequities persisted however; only at least one antenatal visit saw pro-poor improvement. CONCLUSIONS: This intervention achieved improvements in life-saving behaviours for mothers and newborns, demonstrating that multipartner action, coordinated through government leadership, can shift the needle in the right direction, even in resource-constrained settings.

Stated job preferences of three health worker cadres in Ethiopia: a discrete choice experiment.

Attracting, training and retaining high-quality health workers are critical for a health system to function well, and it is important to know what health workers value in their roles. Many studies eliciting the labour market preferences of health workers have interviewed doctors or medical students, and there has been little research on the job preferences of lower-skilled cadres such as community health workers, mid-skilled clinical care staff such as nurses and midwives, or non-patient facing staff who manage health facilities. This study estimated the job preferences of public health sector community health extension workers (HEWs), care providers including nurses and midwives, and non-patient-facing administrative and managerial staff in Ethiopia. We used a discrete choice experiment to estimate which aspects of a job are most influential to health worker choices. A multinomial logistic regression model estimated the importance of six attributes to respondents: salary, training, workload, facility quality, management and opportunities to improve patient outcomes. We found that non-financial factors were important to respondents from all three cadres: e.g., supportive management [odds ratio (OR) = 2.96, P-value = 0.001] was the only attribute that influenced the job choices of non-patient-facing administrative and managerial staff. Training opportunities (OR = 3.45, P-value < 0.001), supportive management (OR = 3.26, P-value < 0.001) and good facility quality (OR = 2.42, P-value < 0.001) were valued the most amongst HEWs. Similarly, supportive management (OR = 3.22, P-value < 0.001), good facility quality (OR = 2.69, P-value < 0.001) and training opportunities (OR = 2.67, P-value < 0.001) influenced the job choices of care providers the most. Earning an average salary also influenced the jobs choices of HEWs (OR = 1.43, P-value = 0.02) and care providers (OR = 2.00, P-value < 0.001), which shows that a combination of financial and non-financial incentives should be considered to motivate health workers in Ethiopia.

Bypassing or successful referral? A population-based study of reasons why women travel far for childbirth in Eastern Uganda.

BACKGROUND: Delivery in a facility with a skilled health provider is considered the most important intervention to reduce maternal and early newborn deaths. Providing care close to people's homes is an important strategy to facilitate equitable access, but many women are known to bypass the closest delivery facility for a higher level one. The aim of this study was to investigate to what extent mothers in rural Uganda bypassed their nearest facility for childbirth care and the determinants for their choice. METHODS: The study used data collected as part of the Expanded Quality Management Using Information power (EQUIP) study in the Mayuge District of Eastern Uganda between 2011 and 2014. In this study, bypassing was defined as delivering in a health facility that was not the nearest childbirth facility to the mother's home. Multilevel logistic regression was used to model the relationship between bypassing the nearest health facility for childbirth and the different independent factors. RESULTS: Of all women delivering in a health facility, 45% (499/1115) did not deliver in the nearest facility regardless of the level of care. Further, after excluding women who delivered in health centre II (which is not formally equipped to provide childbirth care) and excluding those who were referred or had a caesarean section (because their reasons for bypassing may be different), 29% (204/717) of women bypassed their nearest facility to give birth in another facility, 50% going to the only hospital of the district. The odds of bypassing increased if a mother belonged to highest wealth quintile compared to the lowest quintile (AOR 2.24, 95% CI: 1.12-4.46) and decreased with increase of readiness of score of the nearest facility for childbirth (AOR = 0.84, 95% CI: 0.69-0.99). CONCLUSIONS: The extent of bypassing the nearest childbirth facility in this rural Ugandan setting was 29%, and was associated primarily with the readiness of the nearest facility to provide care as well as the wealth of the household. These results suggest inequalities in bypassing for better quality care that have important implications for improving Uganda's maternal and newborn health outcomes.

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.

Understanding mistreatment during institutional delivery in Northeast Nigeria: a mixed-method study.

BACKGROUND: Improving quality of care including the clinical aspects and the experience of care has been advocated for improved coverage and better childbirth outcomes. OBJECTIVE: This study aimed to explore the quality of care relating to the prevalence and manifestations of mistreatment during institutional birth in Gombe State, northeast Nigeria, an area of low institutional delivery coverage. METHODS: The frequency of dimensions of mistreatment experienced by women delivering in 10 health facilities of Gombe State were quantitatively captured during exit interviews with 342 women in July-August 2017. Manifestations of mistreatment were qualitatively explored through in-depth interviews and focus groups with 63 women living in communities with high and low coverage of institutional deliveries. RESULTS: The quantitative data showed that at least one dimension of mistreatment was reported by 66% (95% confidence interval (CI) 45-82%) of women exiting a health facility after delivery. Mistreatment related to health system conditions and constraints were reported in 50% (95% CI 31-70%) of deliveries. In the qualitative data women expressed frustration at being urged to deliver at the health facility only to be physically or verbally mistreated, blamed for poor birth outcomes, discriminated against because of their background, left to deliver without assistance or with inadequate support, travelling long distances to the facility only to find staff unavailable, or being charged unjustified amount of money for delivery. CONCLUSIONS: Mistreatment during institutional delivery in Gombe State is highly prevalent and predominantly relates to mistreatment arising from both health system constraints as well as health worker behaviours, limiting efforts to increase coverage of institutional delivery. To address mistreatment during institutional births, strategies that emphasise a broader health systems approach, tackle multiple causes, integrate a detailed understanding of the local context and have buy-in from grassroots-level stakeholders are recommended.

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.

Monitoring childbirth care in primary health facilities: a validity study in Gombe State, northeastern Nigeria.

BACKGROUND: Improving the quality of facility-based births is a critical strategy for reducing the high burden of maternal and neonatal mortality and morbidity across all settings. Accurate data on childbirth care is essential for monitoring progress. In northeastern Nigeria, we assessed the validity of childbirth care indicators in a rural primary health care context, as documented by health workers and reported by women at different recall periods. METHODS: We compared birth observations (gold standard) to: (i) facility exit interviews with observed women; (ii) household follow-up interviews 9-22 months after childbirth; and (iii) health worker documentation in the maternity register. We calculated sensitivity, specificity, and area under the receiver operating curve (AUC) to determine individual-level reporting accuracy. We calculated the inflation factor (IF) to determine population-level validity. RESULTS: Twenty-five childbirth care indicators were assessed to validate health worker documentation and women's self-reports. During exit interviews, women's recall had high validity (AUC≥0.70 and 0.75

Equity in antenatal care quality: an analysis of 91 national household surveys.

BACKGROUND: Emerging data show that many low-income and middle-income country (LMIC) health systems struggle to consistently provide good-quality care. Although monitoring of inequalities in access to health services has been the focus of major international efforts, inequalities in health-care quality have not been systematically examined. METHODS: Using the most recent (2007-16) Demographic and Health Surveys and Multiple Indicator Cluster Surveys in 91 LMICs, we described antenatal care quality based on receipt of three essential services (blood pressure monitoring and urine and blood testing) among women who had at least one visit with a skilled antenatal-care provider. We compared quality across country income groups and quantified within-country wealth-related inequalities using the slope and relative indices of inequality. We summarised inequalities using random-effects meta-analyses and assessed the extent to which other geographical and sociodemographic factors could explain these inequalities. FINDINGS: Globally, 72·9% (95% CI 69·1-76·8) of women who used antenatal care reported blood pressure monitoring and urine and blood testing; this number ranged from 6·3% in Burundi to 100·0% in Belarus. Antenatal care quality lagged behind antenatal care coverage the most in low-income countries, where 86·6% (83·4-89·7) of women accessed care but only 53·8% (44·3-63·3) reported receiving the three services. Receipt of the three services was correlated with gross domestic product per capita and was 40 percentage points higher in upper-middle-income countries compared with low-income countries. Within countries, the wealthiest women were on average four times more likely to report good quality care than the poorest (relative index of inequality 4·01, 95% CI 3·90-4·13). Substantial inequality remained after adjustment for subnational region, urban residence, maternal age, education, and number of antenatal care visits (3·20, 3·11-3·30). INTERPRETATION: Many LMICs that have reached high levels of antenatal care coverage had much lower and inequitable levels of quality. Achieving ambitious maternal, newborn, and child health goals will require greater focus on the quality of health services and their equitable distribution. Equity in effective coverage should be used as the new metric to monitor progress towards universal health coverage. FUNDING: Bill & Melinda Gates Foundation.

Birth preparedness and place of birth in Tandahimba district, Tanzania: what women prepare for birth, where they go to deliver, and why.

BACKGROUND: As making preparations for birth and health facility delivery are behaviours linked to positive maternal and newborn health outcomes, we aimed to describe what birth preparations were made, where women delivered, and why. METHODS: Outcomes were tabulated using data derived from a repeated sample (continuous) quantitative household survey of women aged 13-49 who had given birth in the past year. Insights into why behaviours took place emerged from analysis of in-depth interviews (12) and birth narratives (36) with recently delivered mothers and male partners. RESULTS: Five hundred-twenty three women participated in the survey from April 2012-November 2013. Ninety-five percent (496/523) of women made any birth preparations for their last pregnancy. Commonly prepared birth items were cotton gauze (93 %), a plastic cover to deliver on (84 %), gloves (72 %), clean clothes (70 %), and money (42 %). Qualitative data suggest that preparation of items used directly during delivery was perceived as necessary to facilitate good care and prevent disease transmission. Sixty-eight percent of women gave birth at a health facility, 30 % at home, and 2 % on the way to a health facility. Qualitative data suggested that health facility delivery was viewed positively and that women were inclined to go to a health facility because of a perception of: increased education about delivery and birth preparedness; previous health facility delivery; and better availability and accessibility of facilities in recent years. Perceived barriers: were a lack of money; absent health facility staff or poor provider attitudes; women perceiving that they were unable to go to a health facility or arrange transport on their own; or a lack of support of pregnant women from their partners. CONCLUSIONS: The majority of women made at least some birth preparations and gave birth in a health facility. Functional items needed for birth seem to be given precedence over practices like saving money. As such, maintaining education about the importance of these practices, with an emphasis on emergency preparedness, would be valuable. Alongside education delivered as part of focussed antenatal care, community-based interventions that aim to increase engagement of men in birth preparedness, and support agency among women, are recommended.

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

BACKGROUND: An urgent priority in maternal, newborn and child health is to accelerate the scale-up of cost-effective essential interventions, especially during labor, the immediate postnatal period and for the treatment of serious infectious diseases and acute malnutrition. Tracking intervention coverage is a key activity to support scale-up and in this paper we examine priorities in coverage measurement, distinguishing between essential interventions that can be measured now and those that require methodological development. METHODS: We conceptualized a typology of indicators related to intervention coverage that distinguishes access to care from receipt of an intervention by the population in need. We then built on documented evidence on coverage measurement to determine the status of indicators for essential interventions and to identify areas for development. RESULTS: Contact indicators from pregnancy to childhood were identified as current indicators for immediate use, but indicators reflecting the quality of care provided during these contacts need development. At each contact point, some essential interventions can be measured now, but the need for development of indicators predominates around interventions at the time of birth and interventions to treat infections. Addressing this need requires improvements in routine facility based data capture, methods for linking provider and community-based data, and improved guidance for effective coverage measurement that reflects the provision of high-quality care. CONCLUSION: Coverage indicators for some essential interventions can be measured accurately through household surveys and be used to track progress in maternal, newborn and child health. Other essential interventions currently rely on contact indicators as proxies for coverage but urgent attention is needed to identify new measurement approaches that directly and reliably measure their effective coverage.

Count every newborn; a measurement improvement roadmap for coverage data.

BACKGROUND: The Every Newborn Action Plan (ENAP), launched in 2014, aims to end preventable newborn deaths and stillbirths, with national targets of ≤12 neonatal deaths per 1000 live births and ≤12 stillbirths per 1000 total births by 2030. This requires ambitious improvement of the data on care at birth and of small and sick newborns, particularly to track coverage, quality and equity. METHODS: In a multistage process, a matrix of 70 indicators were assessed by the Every Newborn steering group. Indicators were graded based on their availability and importance to ENAP, resulting in 10 core and 10 additional indicators. A consultation process was undertaken to assess the status of each ENAP core indicator definition, data availability and measurement feasibility. Coverage indicators for the specific ENAP treatment interventions were assigned task teams and given priority as they were identified as requiring the most technical work. Consultations were held throughout. RESULTS: ENAP published 10 core indicators plus 10 additional indicators. Three core impact indicators (neonatal mortality rate, maternal mortality ratio, stillbirth rate) are well defined, with future efforts needed to focus on improving data quantity and quality. Three core indicators on coverage of care for all mothers and newborns (intrapartum/skilled birth attendance, early postnatal care, essential newborn care) have defined contact points, but gaps exist in measuring content and quality of the interventions. Four core (antenatal corticosteroids, neonatal resuscitation, treatment of serious neonatal infections, kangaroo mother care) and one additional coverage indicator for newborns at risk or with complications (chlorhexidine cord cleansing) lack indicator definitions or data, especially for denominators (population in need). To address these gaps, feasible coverage indicator definitions are presented for validity testing. Measurable process indicators to help monitor health service readiness are also presented. A major measurement gap exists to monitor care of small and sick babies, yet signal functions could be tracked similarly to emergency obstetric care. CONCLUSIONS: The ENAP Measurement Improvement Roadmap (2015-2020) outlines tools to be developed (e.g., improved birth and death registration, audit, and minimum perinatal dataset) and actions to test, validate and institutionalise proposed coverage indicators. The roadmap presents a unique opportunity to strengthen routine health information systems, crosslinking these data with civil registration and vital statistics and population-based surveys. Real measurement change requires intentional transfer of leadership to countries with the greatest disease burden and will be achieved by working with centres of excellence and existing networks.

Identifying implementation bottlenecks for maternal and newborn health interventions in rural districts of the United Republic of Tanzania.

OBJECTIVE: To estimate effective coverage of maternal and newborn health interventions and to identify bottlenecks in their implementation in rural districts of the United Republic of Tanzania. METHODS: Cross-sectional data from households and health facilities in Tandahimba and Newala districts were used in the analysis. We adapted Tanahashi's model to estimate intervention coverage in conditional stages and to identify implementation bottlenecks in access, health facility readiness and clinical practice. The interventions studied were syphilis and pre-eclampsia screening, partograph use, active management of the third stage of labour and postpartum care. FINDINGS: Effective coverage was low in both districts, ranging from only 3% for postpartum care in Tandahimba to 49% for active management of the third stage of labour in Newala. In Tandahimba, health facility readiness was the largest bottleneck for most interventions, whereas in Newala, it was access. Clinical practice was another large bottleneck for syphilis screening in both districts. CONCLUSION: The poor effective coverage of maternal and newborn health interventions in rural districts of the United Republic of Tanzania reinforces the need to prioritize health service quality. Access to high-quality local data by decision-makers would assist planning and prioritization. The approach of estimating effective coverage and identifying bottlenecks described here could facilitate progress towards universal health coverage for any area of care and in any context.