Neonatal mortality in Kenyan hospitals: a multisite, retrospective, cohort study

Abstract

BackgroundMost of the deaths among neonates in low-income and middle-income countries (LMICs) can be prevented through universal access to basic high-quality health services including essential facility-based inpatient care. However, poor routine data undermines data-informed efforts to monitor and promote improvements in the quality of newborn care across hospitals.MethodsContinuously collected routine patients’ data from structured paper record forms for all admissions to newborn units (NBUs) from 16 purposively selected Kenyan public hospitals that are part of a clinical information network were analysed together with data from all paediatric admissions ages 0–13 years from 14 of these hospitals. Data are used to show the proportion of all admissions and deaths in the neonatal age group and examine morbidity and mortality patterns, stratified by birth weight, and their variation across hospitals.FindingsDuring the 354 hospital months study period, 90 222 patients were admitted to the 14 hospitals contributing NBU and general paediatric ward data. 46% of all the admissions were neonates (aged 0–28 days), but they accounted for 66% of the deaths in the age group 0–13 years. 41 657 inborn neonates were admitted in the NBUs across the 16 hospitals during the study period. 4266/41 657 died giving a crude mortality rate of 10.2% (95% CI 9.97% to 10.55%), with 60% of these deaths occurring on the first-day of admission. Intrapartum-related complications was the single most common diagnosis among the neonates with birth weight of 2000 g or more who died. A threefold variation in mortality across hospitals was observed for birth weight categories 1000–1499 g and 1500–1999 g.InterpretationThe high proportion of neonatal deaths in hospitals may reflect changing patterns of childhood mortality. Majority of newborns died of preventable causes (>95%). Despite availability of high-impact low-cost interventions, hospitals have high and very variable mortality proportions after stratification by birth weight.

Randomised controlled trial of fosfomycin in neonatal sepsis: pharmacokinetics and safety in relation to sodium overload

“…We aimed to enrol neonates aged ≤28 days and did not selectively include suspected early onset sepsis. However, 86% neonates were hospitalised within the first week of life, confirming the high burden of early neonatal morbidity reported in similar LMICs 33–36. High levels of resistance of pathogens causing early onset and late-onset sepsis (including ESBL Escherichia coli and Klebsiella pneumoniae ) to empiric antimicrobials have been observed,37–39 potentially acquired in the maternity department.…”

“…However, 86% neonates were hospitalised within the first week of life, confirming the high burden of early neonatal morbidity reported in similar LMICs. [33][34][35][36] High levels of resistance of pathogens causing early onset and late-onset sepsis (including ESBL Escherichia coli and Klebsiella pneumoniae) to empiric antimicrobials have been observed, [37][38][39] potentially acquired in the maternity department. Broad-spectrum antimicrobial coverage that includes fosfomycin as first-line treatment in such settings may improve outcomes and spare the use of carbapenems.…”

Evaluation of an audit and feedback intervention to reduce gentamicin prescription errors in newborn treatment (ReGENT) in neonatal inpatient care in Kenya: a controlled interrupted time series study protocol

“…The study will be conducted in partnership with 20 first-referral level hospitals in Kenya purposefully selected to be of at least moderate size and representative of different malaria transmission zones (Table 2 ). This will involve the patient population admitted to the newborn unit (NBU), a separate unit with a specific clinical and nursing team, where the average age on admission is 0- or 1-day old; most admitted neonates are inborn [ 39 ]. These hospitals joined the Clinical Information Network (CIN), a learning health system in Kenya at different calendar time points between 2014 and 2020 [ 11 , 13 , 39 ].…”

“…This will involve the patient population admitted to the newborn unit (NBU), a separate unit with a specific clinical and nursing team, where the average age on admission is 0- or 1-day old; most admitted neonates are inborn [ 39 ]. These hospitals joined the Clinical Information Network (CIN), a learning health system in Kenya at different calendar time points between 2014 and 2020 [ 11 , 13 , 39 ]. The hospitals receive 3 monthly clinical audit and feedback reports on the quality of care they provide for common conditions, which include a summary of prescription error rates for gentamicin and penicillin [ 30 ].…”

“…More specifically, we work with 20 first-referral level hospitals organised into a Clinical Information Network (CIN) [ 11 , 13 , 39 ] where the hospitals receive 3-monthly clinical A&F reports on the quality of care they provide for common conditions, which include a summary of prescription error rates for gentamicin [ 30 ]. More details are provided later on in the “ Study setting ” sub-section of the “ Design and methodology ” section.…”