Severe maternal outcomes and quality of care at district hospitals in Rwanda– a multicentre prospective case-control study

Sayinzoga, Félix; Bijlmakers, Leon; Velden, Koos van der; Dillen, Jeroen van

doi:10.1186/s12884-017-1581-4

Cited by 28 publications

(39 citation statements)

References 29 publications

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“…e relatively high SMO incidence ratio (MD and MNM) observed in the current study shows that there is a weakness in prevention and treatment of obstetric emergencies in the study region despite the known and availability of effective evidenced-based approaches [21,22]. Similar findings have been reported in earlier studies conducted in other regions within the country [14,15] and neighboring countries such as Rwanda [23] and Ethiopia [24]. e study also revealed a high proportion of newborns with poor perinatal outcomes as a result of SMO.…”

Section: Discussionsupporting

confidence: 88%

Incidence and Predictors of Maternal and Perinatal Mortality among Women with Severe Maternal Outcomes: A Tanzanian Facility-Based Survey for Improving Maternal and Newborn Care

Lilungulu

Bintabara

Mujungu

et al. 2020

Obstetrics and Gynecology International

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Introduction. Maternal and perinatal mortality is still a major public health challenge in Tanzania, despite the ongoing government efforts to improve maternal and newborn care. Among the contributors to these problems is the high magnitude of severe maternal outcomes (maternal near-miss). The current study, therefore, aimed to identify the magnitude and predictors of maternal and perinatal mortality among women with severe maternal outcomes admitted to Dodoma Regional Referral Hospital. Methods. A retrospective cross-sectional study was conducted from October 2015 to January 2016 at Dodoma Regional Referral Hospital in Dodoma City. All maternal deaths and maternal near-misses based on WHO criteria were included in this study. Three outcome variables have been identified: maternal mortality, perinatal mortality, and neonatal complications. To examine the predictors for the three predetermined outcome variables, the three logit models each containing unadjusted and adjusted findings were fitted. A P-value less than 0.05 was considered indicative of statistically significant. Results. A total of 3600 pregnant women were admitted for obstetric reasons during the mentioned period. 140 of them were diagnosed with severe maternal outcomes; hence, they were included in this study. The severe maternal outcome incidence ratio was 40.23 per 1000 live births, the institutional maternal mortality ratio was 459.77 per 100000 live births, and the perinatal mortality rate was 10.83 per 1000 total births. Most of the maternal morbidity and mortality were due to direct causes in which postpartum hemorrhage and hypertensive disorders were the leading causes. In adjusted analysis, per-protocol management, maternal age, and mode of birth were predictors of maternal mortality, perinatal mortality, and neonatal complications, respectively. Conclusion. Establishing and strengthening obstetric ICUs will help reduce maternal mortality as the response time from the onset of obstetric complications, while the provision of high-quality care will be substantially reduced. Furthermore, the study recommends regular provision of in-service refresher training to emphasize the practice and compliance of per-protocol case management through a team approach in order to reduce the burden of maternal and perinatal mortality in Tanzania.

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Section: Discussionsupporting

confidence: 88%

Incidence and Predictors of Maternal and Perinatal Mortality among Women with Severe Maternal Outcomes: A Tanzanian Facility-Based Survey for Improving Maternal and Newborn Care

Lilungulu

Bintabara

Mujungu

et al. 2020

Obstetrics and Gynecology International

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“…The mortality index (i.e., case‐fatality ratio) was found to range from 3% to 37% . A more recent review reported a median maternal near‐miss incidence of 2.4%, and other studies have reported low levels of near miss per 100 live births of 1.2 in Zanzibar, 2.5 in a rural hospital in Rwanda, 3.6 in district hospitals Rwanda, and 0.8 in Uganda (Supplementary Fig. S1).…”

Section: Introductionmentioning

confidence: 94%

Rethinking the definition of maternal near‐miss in low‐income countries using data from 104 health facilities in Tanzania and Uganda

Pembe

Hirose

Al‐beity

et al. 2019

Intl J Gynecology & Obste

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Objective To assess the consistency of maternal near‐miss incidence and mortality index between two definitions across 104 facilities in Tanzania and Uganda. Methods Based on WHO guidance, cross‐sectional near‐miss data were collected in Tanzania (July 2015 to October 2016) and Uganda (June 2016 to September 2017). Prepartum hemorrhage and abortion were included as additional screening events and the number of blood units transfused was recorded. Near‐miss incidence and mortality index were determined by using two near‐miss definitions: the WHO standard definition, and a modified definition including women receiving at least 1 unit of blood. A sensitivity analysis excluded the additional screening events. Results Near‐miss incidence differed between Tanzania and Uganda (1.79 and 4.00, respectively, per 100 deliveries) when estimated by the standard definition, but was similar (5.24 and 4.94, respectively) by the modified definition. The mortality index was higher in Tanzania than in Uganda when estimated by the standard definition (8.56% vs 3.54%), but was similar by the modified definition (3.10% vs 2.89%). Conclusion The modified definition provided a more consistent estimate of near‐miss incidence and mortality index. Lowering the threshold for units of blood transfusion might improve comparability between settings, but more research is needed.

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“…It is worth noting though, that Rwanda does have a mechanism in place to conduct maternal death audits, and the country is currently in the process of institutionalizing ‘near-miss’ audits and confidential enquiries into maternal deaths [20]. Some studies recently reported rather high rates of postpartum haemorrhage and infection, as causes of maternal near miss and death [21,22]. This suggests there is a need for improvement of quality of care at the level of district hospitals, where the majority of deliveries occur.…”

Section: Discussionmentioning

confidence: 99%

Understanding variation in maternal health service coverage and maternal health outcomes among districts in Rwanda

Sayinzoga

Moses

et al. 2019

Preprint

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37Objective: To identify factors that explain variations between districts in maternal 38 health service coverage and maternal health outcomes. 39 Methods: Individual key informant interviews and focus group discussions using 40 structured topic lists were conducted in May 2015 in four purposively selected 41 districts. 42 Results: The solidarity support for poor people and the interconnectedness between 43 local leaders and heads of health facilities were identified as enablers of health service 44 utilization. Geographical factors, in particular location close to borders with mobile 45 populations and migrants, and large populations with sparsely distributed health 46 infrastructure, exacerbated by hilly topography and muddy roads were identified as 47 barriers. Shortages of skilled health providers at the level of district hospitals were 48 cited as contributing to poor maternal health outcomes.49Conclusion: There is a need to take into account disparities between districts when 50 allocating staff and financial resources in order to achieve universal coverage for 51 high-quality maternal health services and better outcomes. Local innovations such as 52 the use of SMS and WhatsApp text messages by health workers and financial 53 protection schemes for poor patients improve solidarity and are worth to be scaled up. 54 55 innovations 57 59 Worldwide in 2015, an estimated 303,000 women died due to complications of 60 pregnancy or childbirth [1]. Most of them died because of severe bleeding after 61 childbirth, infections, hypertensive disorders or unsafe abortions. Low and middle 62 income countries account for 99% of these deaths, with sub-Saharan Africa alone 63 accounting for roughly two-thirds (201,000 deaths in 2015) [1]. Maternal mortality is 64 one of the health outcomes that typically show very wide gaps between rich and poor 65 populations [1]. 66 The 2014/15 Demographic and health survey (DHS) in Rwanda estimated the 67 maternal mortality ratio (MMR) at 210 deaths per 100,000 live births [2], which is 68 significantly less than the ratios reported in the 2010 DHS (476 per 100,000) and the 69 2000 DHS (1071 per 100,000) [3,4]. Although everything points to significant 70 improvements, deaths related to pregnancy and childbirth are still too common and 71 will need to be reduced further in order to reach the SDG target MMR of 70 per 72 100,000 by the year 2030. 73Globally, health service coverage rates have increased but many countries are still a 74 long way from universal coverage for most essential reproductive, maternal, newborn 75 and child health (RMNCH) interventions. Furthermore, intra-country variations in 76 service coverage rates are reducing in most countries but the pace is slow. The main 77 impediments to the delivery of high-quality services are a combination of health 78 sector specific and non-health sector drivers [5]. Reliable and timely information is 79 required for effective remedial action at local, regional and national health sector 80 management levels, in order to address intra-...

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Severe maternal outcomes and quality of care at district hospitals in Rwanda– a multicentre prospective case-control study

Cited by 28 publications

References 29 publications

Incidence and Predictors of Maternal and Perinatal Mortality among Women with Severe Maternal Outcomes: A Tanzanian Facility-Based Survey for Improving Maternal and Newborn Care

Incidence and Predictors of Maternal and Perinatal Mortality among Women with Severe Maternal Outcomes: A Tanzanian Facility-Based Survey for Improving Maternal and Newborn Care

Rethinking the definition of maternal near‐miss in low‐income countries using data from 104 health facilities in Tanzania and Uganda

Understanding variation in maternal health service coverage and maternal health outcomes among districts in Rwanda

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