Maternal and perinatal mortality remain huge challenges globally, particularly in low- and middle-income countries (LMICs) where >98% of these deaths occur. Emergency obstetric care (EmOC) provided by skilled health personnel is an evidence-based package of interventions effective in reducing these deaths associated with pregnancy and childbirth. Until recently, pregnant women residing in urban areas have been considered to have good access to care, including EmOC. However, emerging evidence shows that due to rapid urbanization, this so called “urban advantage” is shrinking and in some LMIC settings, it is almost non-existent. This poses a complex challenge for structuring an effective health service delivery system, which tend to have poor spatial planning especially in LMIC settings. To optimize access to EmOC and ultimately reduce preventable maternal deaths within the context of urbanization, it is imperative to accurately locate areas and population groups that are geographically marginalized. Underpinning such assessments is accurately estimating travel time to health facilities that provide EmOC. In this perspective, we discuss strengths and weaknesses of approaches commonly used to estimate travel times to EmOC in LMICs, broadly grouped as reported and modeled approaches, while contextualizing our discussion in urban areas. We then introduce the novel OnTIME project, which seeks to address some of the key limitations in these commonly used approaches by leveraging big data. The perspective concludes with a discussion on anticipated outcomes and potential policy applications of the OnTIME project.

IntroductionAccess to emergency obstetric care can lead to a 45%–75% reduction in stillbirths. However, before a pregnant woman can access this care, she needs to travel to a health facility. Our objective in this study was to assess the influence of distance and travel time to the actual hospital of care on stillbirth.MethodsWe conducted a retrospective cross-sectional study of pregnant women who presented with obstetric emergencies over a year across all 24 public hospitals in Lagos, Nigeria. Reviewing clinical records, we extracted sociodemographic, travel and obstetric data. Extracted travel data were exported to Google Maps, where typical distance and travel time for period-of-day they travelled were extracted. Multivariable logistic regression was conducted to determine the relative influence of distance and travel time on stillbirth.ResultsOf 3278 births, there were 408 stillbirths (12.5%). Women with livebirths travelled a median distance of 7.3 km (IQR 3.3–18.0) and over a median time of 24 min (IQR 12–51). Those with stillbirths travelled a median distance of 8.5 km (IQR 4.4–19.7) and over a median time of 30 min (IQR 16–60). Following adjustments, though no significant association with distance was found, odds of stillbirth were significantly higher for travel of 10–29 min (OR 2.25, 95% CI 1.40 to 3.63), 30–59 min (OR 2.30, 95% CI 1.22 to 4.34) and 60–119 min (OR 2.35, 95% CI 1.05 to 5.25). The adjusted OR of stillbirth was significantly lower following booking (OR 0.37, 95% CI 0.28 to 0.49), obstetric complications with mother (obstructed labour (OR 0.11, 95% CI 0.07 to 0.17) and haemorrhage (OR 0.30, 95%CI 0.20 to 0.46)). Odds were significantly higher with multiple gestations (OR 2.40, 95% CI 1.57 to 3.69) and referral (OR 1.55, 95% CI 1.13 to 2.12).ConclusionTravel time to a hospital was strongly associated with stillbirth. In addition to birth preparedness, efforts to get quality care quicker to women or women quicker to quality care will be critical for efforts to reduce stillbirths in a principally urban low-income and middle-income setting.

IntroductionPrompt access to emergency obstetrical care (EmOC) reduces the risk of maternal mortality. We assessed institutional maternal mortality by distance and travel time for pregnant women with obstetrical emergencies in Lagos State, Nigeria.MethodsWe conducted a facility-based retrospective cohort study across 24 public hospitals in Lagos. Reviewing case notes of the pregnant women presenting between 1 November 2018 and 30 October 2019, we extracted socio-demographic, travel and obstetrical data. The extracted travel data were exported to Google Maps, where driving distance and travel time data were extracted. Multivariable logistic regression was conducted to determine the relative influence of distance and travel time on maternal death.FindingsOf 4181 pregnant women with obstetrical emergencies, 182 (4.4%) resulted in maternal deaths. Among those who died, 60.3% travelled ≤10 km directly from home, and 61.9% arrived at the hospital ≤30 mins. The median distance and travel time to EmOC was 7.6 km (IQR 3.4–18.0) and 26 mins (IQR 12–50). For all women, travelling 10–15 km (2.53, 95% CI 1.27 to 5.03) was significantly associated with maternal death. Stratified by referral, odds remained statistically significant for those travelling 10–15 km in the non-referred group (2.48, 95% CI 1.18 to 5.23) and for travel ≥120 min (7.05, 95% CI 1.10 to 45.32). For those referred, odds became statistically significant at 25–35 km (21.40, 95% CI 1.24 to 36.72) and for journeys requiring travel time from as little as 10–29 min (184.23, 95% CI 5.14 to 608.51). Odds were also significantly higher for women travelling to hospitals in suburban (3.60, 95% CI 1.59 to 8.18) or rural (2.51, 95% CI 1.01 to 6.29) areas.ConclusionOur evidence shows that distance and travel time influence maternal mortality differently for referred women and those who are not. Larger scale research that uses closer-to-reality travel time and distance estimates as we have done, rethinking of global guidelines, and bold actions addressing access gaps, including within the suburbs, will be critical in reducing maternal mortality by 2030.

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Background The highest risk of maternal and perinatal deaths occurs during and shortly after childbirth and is preventable if functional referral systems enable women to reach appropriate health services when obstetric complications occur. Rising numbers of deliveries in health facilities, including in high mortality settings like Nigeria, require formalised coordination across the health system to ensure that women and newborns get to the right level of care, at the right time. This study describes and critically assesses the extent to which referral and its components can be captured using three different data sources from Nigeria, examining issues of data quality, validity, and usefulness for improving and monitoring obstetric care systems. Methods The study included three data sources on referral for childbirth care in Nigeria: a nationally representative household survey, patient records from multiple facilities in a state, and patient records from the apex referral facility in a city. We conducted descriptive analyses of the extent to which referral status and components were captured across the three sources. We also iteratively developed a visual conceptual framework to guide our critical comparative analysis. Results We found large differences in the proportion of women referred, and this reflected the different denominators and timings of the referral in each data source. Between 16 and 34% of referrals in the three sources originated in government hospitals, and lateral referrals (origin and destination facility of the same level) were observed in all three data sources. We found large gaps in the coverage of key components of referral as well as data gaps where this information was not routinely captured in facility-based sources. Conclusions Our analyses illustrated different perspectives from the national- to facility-level in the capture of the extent and components of obstetric referral. By triangulating across multiple data sources, we revealed the strengths and gaps within each approach in building a more complete picture of obstetric referral. We see our visual framework as assisting further research efforts to ensure all referral pathways are captured in order to better monitor and improve referral systems for women and newborns.

Background:The early phase of the COVID-19 pandemic led to significant disruptions in provision of maternal, newborn, and child health (MNCH) services, especially in low-and middle-income countries (LMICs) with fragile health systems, such as Nigeria. Measures taken to 'flatten the curve' such as lockdowns, curfews, travel restrictions, and suspension of public services inadvertently led to significant disruptions in provision of essential health services. In these countries, health facility leaders are directly responsible for driving changes needed for service delivery.Objective: To explore perspectives of health facility leaders in Lagos, Nigeria, on solutions and adaptations implemented to support MNCH service provision during the early phase of the COVID-19 pandemic.Methods: Key informant interviews were remotely conducted with purposively sampled 33 health facility leaders across primary, secondary, and tertiary public health facilities in Lagos between July and November 2020. Following verbatim transcription of recordings, data familiarization, and coding, thematic analysis was used to synthesize data.Results: Health facility leaders scaled down or discontinued outpatient MNCH services and elective surgeries. However, deliveries, newborn, immunization, and emergency services continued. Service provision was reorganized with long and staggered patient appointments, collapsing of wards and modification of health worker duty rosters. Some secondary and tertiary facilities leveraged technology like WhatsApp, webinars, and telemedicine to support service provision. Continuous capacity-building for health workers through training, motivation, psychological support, and atypical sourcing of PPE was instituted to be able to safely maintain service delivery.

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