Abstract
Introduction: Understanding the extent and cause of high neonatal deaths rates in Sub-Saharan Africa is a challenge, especially in the presence of poor-quality and inaccurate data. The NeoTree digital data capture and quality improvement system has been live at Kamuzu Central Hospital, Neonatal Unit, Malawi, since April 2019.Objective: To describe patterns of admissions and outcomes in babies admitted to a Malawian neonatal unit over a 1-year period via a prototype data dashboard.Methods: Data were collected prospectively at the point of care, using the NeoTree app, which includes digital admission and outcome forms containing embedded clinical decision and management support and education in newborn care according to evidence-based guidelines. Data were exported and visualised using Microsoft Power BI. Descriptive and inferential analysis statistics were executed using R.Results: Data collected via NeoTree were 100% for all mandatory fields and, on average, 96% complete across all fields. Coverage of admissions, discharges, and deaths was 97, 99, and 91%, respectively, when compared with the ward logbook. A total of 2,732 neonates were admitted and 2,413 (88.3%) had an electronic outcome recorded: 1,899 (78.7%) were discharged alive, 12 (0.5%) were referred to another hospital, 10 (0.4%) absconded, and 492 (20%) babies died. The overall case fatality rate (CFR) was 204/1,000 admissions. Babies who were premature, low birth weight, out born, or hypothermic on admission, and had significantly higher CFR. Lead causes of death were prematurity with respiratory distress (n = 252, 51%), neonatal sepsis (n = 116, 23%), and neonatal encephalopathy (n = 80, 16%). The most common perceived modifiable factors in death were inadequate monitoring of vital signs and suboptimal management of sepsis. Two hundred and two (8.1%) neonates were HIV exposed, of whom a third [59 (29.2%)] did not receive prophylactic nevirapine, hence vulnerable to vertical infection.Conclusion: A digital data capture and quality improvement system was successfully deployed in a low resource neonatal unit with high (1 in 5) mortality rates providing and visualising reliable, timely, and complete data describing patterns, risk factors, and modifiable causes of newborn mortality. Key targets for quality improvement were identified. Future research will explore the impact of the NeoTree on quality of care and newborn survival.
Highlights
Understanding the extent and cause of high neonatal deaths rates in SubSaharan Africa is a challenge, especially in the presence of poor-quality and inaccurate data
We report a digital case fatality rate (CFR) of 204 per 1,000 at Kamuzu Central Hospital (KCH) with prematurity with respiratory distress syndrome (RDS), neonatal sepsis, and neonatal encephalopathy being the commonest causes of death
The NeoTree app and dashboard produced aggregate data, which is likely to be of high quality and reliability, whilst simultaneously providing clinical decision support and quality improvement in a low- resource setting
Summary
Understanding the extent and cause of high neonatal deaths rates in SubSaharan Africa is a challenge, especially in the presence of poor-quality and inaccurate data. The country reached its fourth World Health Organisation (WHO) Millennium Development Goal to reduce childhood mortality by two-thirds in 2013 [9]. Despite these gains, Malawi still has high neonatal mortality rates of 27 per 1,000 live births [10]. Preventable or modifiable perinatal factors frequently contribute to the leading causes of neonatal mortality in low-resource settings. This is in contrast to high resource settings where the main causes of neonatal mortality are congenital abnormalities, which are less modifiable [12]
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