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AIMS: To assess the knowledge of nurses of national guidelines for emergency maternity, routine newborn and small and sick newborn care in Nairobi County, Kenya. BACKGROUND: The vast majority of women deliver in a health facility in Nairobi. Yet, maternal and neonatal mortality remain high. Ensuring competency of health workers, in providing essential maternal and newborn interventions in health facilities will be key if further progress is to be made in reducing maternal and neonatal mortality in low-resource settings. DESIGN: Cross-sectional survey. METHODS: Questionnaires comprised of clinical vignettes and direct questions and were administered in 2015-2016 to nurses (n = 125 in 31 facilities) on duty in maternity and newborn units in public and private facilities providing 24/7 inpatient neonatal services. Composite knowledge scores were calculated and presented as weighted means. Associations were explored using regression. STROBE guidelines were followed. RESULTS: Nurses scored best for knowledge on active management of the mother after birth and immediate routine newborn care. Performance was worst for questions on infant resuscitation, checking signs and symptoms of sick newborns, and managing hypertension in pregnancy. Overall knowledge of care for sick newborns was particularly low (score 0.62 of 1). Across all areas assessed, nurses who had received training since qualifying performed better than those who had not. Poorly resourced and low case-load facilities had lower average knowledge scores compared with better-resourced and busier facilities. CONCLUSION: Overall, we estimate that 31% of maternity patients, 3% of newborns and 39% of small and sick newborns are being cared for in an environment where nursing knowledge is very low (score

BACKGROUND: Each year approximately 10 million babies do not breathe immediately at birth, of which about 6 million require basic neonatal resuscitation. The major burden is in low-income settings, where health system capacity to provide neonatal resuscitation is inadequate. OBJECTIVE: To systematically review the evidence for neonatal resuscitation content, training and competency, equipment and supplies, cost, and key program considerations, specifically for resource-constrained settings. RESULTS: Evidence from several observational studies shows that facility-based basic neonatal resuscitation may avert 30% of intrapartum-related neonatal deaths. Very few babies require advanced resuscitation (endotracheal intubation and drugs) and these newborns may not survive without ongoing ventilation; hence, advanced neonatal resuscitation is not a priority in settings without neonatal intensive care. Of the 60 million nonfacility births, most do not have access to resuscitation. Several trials have shown that a range of community health workers can perform neonatal resuscitation with an estimated effect of a 20% reduction in intrapartum-related neonatal deaths, based on expert opinion. Case studies illustrate key considerations for scale up. CONCLUSION: Basic resuscitation would substantially reduce intrapartum-related neonatal deaths. Where births occur in facilities, it is a priority to ensure that all birth attendants are competent in resuscitation. Strategies to address the gap for home births are urgently required. More data are required to determine the impact of neonatal resuscitation, particularly on long-term outcomes in low-income settings.

Multiple outcomes reflecting different aspects of routine care are a common phenomenon in health care research. A common approach of handling such outcomes is multiple univariate analyses, an approach which does not allow for answering research questions pertaining to joint inference. In this study, we sought to study associations among nine pediatric pneumonia care outcomes spanning assessment, diagnosis and treatment domains of care, while circumventing the computational challenge posed by their clustered and high-dimensional nature and incompletely recorded covariates. We analyzed data from a cluster randomized trial conducted in 12 Kenyan hospitals. There were varying degrees of missingness in the covariates of interest, and these were multiply imputed using latent normal joint modeling. We used the pairwise joint modeling strategy to fit a correlated random effects joint model for the nine outcomes. This entailed fitting 36 bivariate generalized linear mixed models and deriving inference for the joint model using pseudo-likelihood theory. We also analyzed the nine outcomes separately before and after multiple imputation. We observed joint effects of patient-, clinician- and hospital-level factors on pneumonia care indicators before and after multiple imputation of missing covariates. In both pairwise joint modeling and separate univariate analysis methods, enhanced audit and feedback improved documentation and adherence to recommended clinical guidelines over time in six and five pneumonia care indicators, respectively. Additionally, multiple imputation improved precision of parameter estimates compared to complete case analysis. The strength and direction of association among pneumonia outcomes varied within and across the three domains of pneumonia care This work was supported through the DELTAS Africa Initiative Grant No. 107754/Z/15/Z-DELTAS Africa SSACAB. The DELTAS Africa Initiative is an independent funding scheme of the African Academy of Sciences (AAS)’s Alliance for Accelerating Excellence in Science in Africa (AESA) and supported by the New Partnership for Africa's Development Planning and Coordinating Agency (NEPAD Agency) with funding from the Wellcome Trust (Grant No. 107754/Z/15/Z) and the UK government. The views expressed in this publication are those of the author(s) and not necessarily those of AAS, NEPAD Agency, Wellcome Trust or the UK government. Funds from the Wellcome Trust (Grant No. 207522) awarded to Prof. Mike English as a senior Fellow together with additional funds from a Wellcome Trust core grant awarded to the KEMRIWellcome Trust Research Programme (Grant No. 092654) supported CIN data collection.