Objectiveto analyse the impact of in-hospital care on severe maternal morbidity using WHO’s near-miss approach in the low-resource, high mortality setting of Zanzibar’s referral hospital.SettingMnazi Mmoja Hospital, a tertiary care facility, in Zanzibar, Tanzania.MethodsWe identified all cases of morbidity and mortality in women admitted within 42 days after the end of pregnancy at Mnazi Mmoja Hospital in the period from April to October 2016. The severity of complications was classified using WHO’s near-miss approach definitions: potentially life-threatening condition (PLTC), maternal near-miss (MNM) or maternal death (MD). Quality of in-hospital care was assessed using the mortality index (MI) defined as ratio between mortality and severe maternal outcome (SMO) where SMO = MD + MNM, cause-specific case facility rates and comparison with predicted mortality based on the Maternal Severity Index model.Main outcomes5551 women were included. 569 (10.3%) had a potentially life-threatening condition and 65 (1.2%) a severe maternal outcome (SMO): 37 maternal near-miss cases and 28 maternal deaths. The mortality index was high at 0.43 and similar for women who developed a SMO within 12 hours of admission and women who developed a SMO after 12 hours. A standardized mortality ratio of 6.03 was found; six times higher than that expected in moderate maternal mortality settings given the same severity of cases. Obstetric haemorrhage was found to be the main cause of SMO. Ruptured uterus and admission to ICU had the highest case-fatality rates. Maternal death cases seemed to have received essential interventions less often.ConclusionsWHO’s near-miss approach can be used in this setting. The high mortality index observed shows that in-hospital care is not preventing progression of disease adequately once a severe complication occurs. Almost one in two women experiencing life-threatening complications will die. This is six times higher than in moderate mortality settings.
Objective To evaluate the validity of WHO’s near-miss approach in a low-resource, high maternal mortality setting. Design Prospective cohort study. Setting Mnazi Mmoja Hospital, the main referral hospital of Zanzibar, Tanzania, from 1 April 2017 until 31 December 2018. Population All women, pregnant or until 42 days after the end of pregnancy, admitted at Mnazi Mmoja Hospital, the tertiary referral hospital in Zanzibar. Methods Cases of maternal morbidity and mortality were evaluated according to WHO’s near-miss approach. The approach’s performance was determined by calculating its accuracy through sensitivity, specificity and positive and negative likelihood ratios. The approach’s validity was assessed with Pearson’s correlation coefficient between the number of organ dysfunction markers and risk of mortality. Main outcomes measures Correlation between number of organ dysfunction markers and risk of mortality, sensitivity and specificity. Results 26,842 women were included. There were 335 with a severe maternal outcome: 256 maternal near-miss cases and 79 maternal deaths. No signs of organ dysfunction were documented in only 4 of the 79 cases of maternal death. The number of organ dysfunction markers was highly correlated to the risk of mortality with Pearson’s correlation coefficient of 0.89. Conclusions WHO’s near-miss approach adequately identifies women at high risk of maternal mortality in Zanzibar’s referral hospital. There is a strong correlation between the number of markers of organ dysfunction and mortality risk.
To support the global restart of elective surgery, data from an international prospective cohort study of 8492 patients (69 countries) was analysed using artificial intelligence (machine learning techniques) to develop a predictive score for mortality in surgical patients with SARS-CoV-2. We found that patient rather than operation factors were the best predictors and used these to create the COVIDsurg Mortality Score (https://covidsurgrisk.app). Our data demonstrates that it is safe to restart a wide range of surgical services for selected patients.
Poor intra-facility maternity care is a major contributor to maternal mortality in low- and middle-income countries. Close to 830 women die each day due to preventable maternal complications, partly due to the increasing number of women giving birth in health facilities that are not adequately resourced to manage growing patient populations. Barriers to adequate care during the ‘last mile’ of healthcare delivery are attributable to deficiencies at multiple levels: education, staff, medication, facilities, and delays in receiving care. Moreover, the scope and multi-scale interdependence of these factors make individual contributions of each challenging to analyze, particularly in settings where basic data registration is often lacking. To address this need, we have designed and implemented a novel systems-level and dynamic mathematical model that simulates the impact of hospital resource allocations on maternal mortality rates at Mnazi Mmoja Hospital (MMH), a referral hospital in Zanzibar, Tanzania. The purpose of this model is to provide a rigorous and flexible tool that enables hospital administrators and public health officials to quantitatively analyze the impact of resource constraints on patient outcomes within the maternity ward, and prioritize key areas for further human or capital investment. Currently, no such tool exists to assist administrators and policy makers with effective resource allocation and planning. This paper describes the structure and construct of the model, provides validation of the assumptions made with anonymized patient data and discusses the predictive capacity of our model. Application of the model to specific resource allocations, maternal treatment plans, and hospital loads at MMH indicates through quantitative results that medicine stocking schedules and staff allocations are key areas that can be addressed to reduce mortality by up to 5-fold. With data-driven evidence provided by the model, hospital staff, administration, and the local ministries of health can enact policy changes and implement targeted interventions to improve maternal health outcomes at MMH. While our model is able to determine specific gaps in resources and health care delivery specifically at MMH, the model should be viewed as an additional tool that may be used by other facilities seeking to analyze and improve maternal health outcomes in resource constrained environments.
Background This study aims to explore the stories of three women from Zanzibar, Tanzania, who survived life-threatening obstetric complications. Their narratives will increase understanding of the individual and community-level burden masked behind the statistics of maternal morbidity and mortality in Tanzania. In line with a recent systematic review of women-centred, qualitative maternal morbidity research, this study will contribute to guidance of local and global maternal health agendas. Methods This two-phased qualitative study was conducted in July-August 2017 and July-August 2018, and involved three key informants, who were recruited from a maternal near-miss cohort in May 2017 in Mnazi Mmoja Hospital, Zanzibar. The used methods were participant observation, interviews (informal, unstructured and semi-structured), participatory methods and focus group discussions. Data analysis relied primarily on grounded theory, leading to a theoretical model, which was validated repeatedly by the informants and within the study team. The findings were then positioned in the existing literature. Approval was granted by Zanzibar’s Medical Ethical Research Committee (reference number: ZAMREC/0002/JUN/17). Results The impact of severe maternal morbidity was found to be multi-dimensional and to extend beyond hospital discharge and thus institutionalized care. Four key areas impacted by maternal morbidities emerged, namely (1) social, (2) sexual and reproductive, (3) psychological, and (4) economic well-being. Conclusions This study showed how three women’s lives and livelihoods were profoundly impacted by the severe obstetric complications they had survived, even up to 16 months later. These impacts took a toll on their physical, social, economic, sexual and psychological well-being, and affected family and community members alike. These findings advocate for a holistic, dignified, patient value-based approach to the necessary improvement of maternal health care in low-income settings. Furthermore, it emphasizes the need for strategies to be directed not only towards quality of care during pregnancy and delivery, but also towards support after obstetric complications.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.