ABSTRACT
BACKGROUND: Health care-associated infections (HCAI) in neonatal units in low- and middle-income countries (LMIC) are a major cause of mortality. This scoping review aimed to synthesise published literature on infection prevention and care bundles addressing neonatal HCAI in LMICs and to construct a Classification Framework for their components (elements). METHODS: Five electronic databases were searched between January 2001 and July 2020. A mixed-methods approach was applied: qualitative content analysis was used to build a classification framework to categorise bundle elements and the contents of the classification groups were then described quantitatively. FINDINGS: 3619 records were screened, with 44 eligible studies identified. The bundle element Classification Framework created involved: (1) Primary prevention, (2) Detection, (3) Case management, and Implementation (3 + I). The 44 studies included 56 care bundles with 295 elements that were then classified. Primary prevention elements (128, 43%) predominated of which 71 (55%) focused on central line catheters and mechanical ventilators. Only 12 elements (4%) were related to detection. A further 75 (25%) elements addressed case management and 66 (88%) of these aimed at outbreak control. INTERPRETATION: The 3 + I Classification Framework was a feasible approach to reporting and synthesising research for infection-relevant bundled interventions in neonatal units. A shift towards the use in infection prevention and care bundles of primary prevention elements focused on the neonate and on commonly used hospital devices in LMIC (e.g., self-inflating bags, suctioning equipment) would be valuable to reduce HCAI transmission. Detection elements were a major gap. FUNDING: This work was made possible in part by the John D. and Catherine T. MacArthur Foundation, the Bill & Melinda Gates Foundation, ELMA Philanthropies, The Children's Investment Fund Foundation UK, The Lemelson Foundation, and the Ting Tsung and Wei Fong Chao Foundation under agreements to William Marsh Rice University. The project leading to these results has also received the support of a fellowship from the "la Caixa" Foundation (ID 100010434). The fellowship code is LCF/BQ/EU19/11710040. EJAF is an Academic Clinical Fellow whose salary is funded by the UK National Institute for Health Research (NIHR). NES receives a Research Training Program Scholarship (Australian Commonwealth Government).
