An assessment of geographical access and factors influencing travel time to emergency obstetric care in the urban state of Lagos, Nigeria

Abstract

Previous efforts to estimate the travel time to comprehensive emergency obstetric care (CEmOC) in low- and middle-income countries (LMICs) have either been based on spatial models or self-reported travel time, both with known inaccuracies. The study objectives were to estimate more realistic travel times for pregnant women in emergency situations using Google Maps, determine system-level factors that influence travel time and use these estimates to assess CEmOC geographical accessibility and coverage in Lagos state, Nigeria. Data on demographics, obstetric history and travel to CEmOC facilities of pregnant women with an obstetric emergency, who presented between 1st November 2018 and 31st December 2019 at a public CEmOC facility were collected from hospital records. Estimated travel times were individually extracted from Google Maps for the period of the day of travel. Bivariate and multivariate analyses were used to test associations between travel and health system-related factors with reaching the facility >60 minutes. Mean travel times were compared and geographical coverage mapped to identify ‘hotspots’ of predominantly >60 minutes travel to facilities. For the 4005 pregnant women with traceable journeys, travel time ranges were 2–240 minutes (without referral) and 7–320 minutes (with referral). Total travel time was within the 60 and 120 minute benchmark for 80 and 96% of women, respectively. The period of the day of travel and having been referred were significantly associated with travelling >60 minutes. Many pregnant women living in the central cities and remote towns typically travelled to CEmOC facilities around them. We identified four hotspots from which pregnant women travelled >60 minutes to facilities. Mean travel time and distance to reach tertiary referral hospitals were significantly higher than the secondary facilities. Our findings suggest that actions taken to address gaps need to be contextualized. Our approach provides a useful guide for stakeholders seeking to comprehensively explore geographical inequities in CEmOC access within urban/peri-urban LMIC settings.

Travel of pregnant women in emergency situations to hospital and maternal mortality in Lagos, Nigeria: a retrospective cohort study

“…In Lagos, most pregnant women with obstetrical emergencies living in the peripheral rural areas usually travelled to public hospitals around them. 28 In a separate study, we found that travel to care in this settlement type is typically prolonged in the suburbs. 28 This blurring of the so-called ‘urban advantage’, or at least the ‘suburb advantage’, may explain the higher odds of maternal death in hospitals situated in the suburbs.…”

“… 28 In a separate study, we found that travel to care in this settlement type is typically prolonged in the suburbs. 28 This blurring of the so-called ‘urban advantage’, or at least the ‘suburb advantage’, may explain the higher odds of maternal death in hospitals situated in the suburbs.…”

“…Even if women themselves were asked, issues of recall bias have been raised by researchers. 28–30 In addition, our study included women with emergencies across the entire pregnancy period and disaggregates by referral status, reflecting the different journeys that women follow to care. 31 These are some of the key strengths of our study.…”

A tale of 22 cities: utilisation patterns and content of maternal care in large African cities

“…Traffic and poor road conditions, complexities of urban governance for health and living environments of slums and informal settlements further challenge access to critical maternal and newborn health services, especially for the urban poor. 17 21 22 …”

“… 23 The result is a ‘know-do’ gap in maternal and perinatal care, 24 with the phenomena of ‘too little too late’ and ‘too much too soon’ occurring in parallel. 25 26 Although large cities also tend to have tertiary care such as teaching hospitals, 17 urban populations differ hugely in terms of their ability to pay for healthcare and other essential services, which in part has contributed to the growth of a diversity of private providers—for-profit and not-for-profit, formal and informal—targeting various population groups in cities. The presence of different categories of providers, while alleviating some pressure on public services, 16 creates challenges for regulating care quality standards across the variety of providers and ensuring affordable, high-quality care within the umbrella of universal health coverage.…”