Disinfection of Neonatal Resuscitation Equipment in Resource-Limited Settings: Lessons From a Mixed-Methods Implementation Experience in Kenya.

backgroundThe majority of neonatal deaths occur in low- and middle-income countries, most often due to perinatal events, prematurity, and/or infection. Reprocessing of neonatal resuscitation equipment is vital for ensuring the availability of clean equipment and preventing transmission of infection to a newborn. Staff at Tenwek Hospital, a tertiary referral hospital in rural Kenya, identified reprocessing medical equipment as a gap in improving neonatal care. We sought to implement steam-based high-level disinfection (HLD) for reprocessing neonatal resuscitation equipment in the labor and delivery ward of Tenwek Hospital. NEEDS ASSESSMENT: Before implementation, a needs assessment was conducted to identify existing facilitators and barriers to reprocessing through semistructured interviews with key stakeholders at the hospital (N=12) and identify gaps in the hospital's existing reprocessing procedures. A chemical, chlorine-based method of disinfection was used for neonatal resuscitation equipment in the ward. We conducted baseline bacterial burden of neonatal resuscitation equipment before clinical use, after clinical use, and after reprocessing. There was not a significant decrease in bacterial burden after reprocessing. IMPLEMENTATION: After implementing a new steam-based HLD process, we conducted bacterial burden testing, which showed a reduction. However, staff preferences and implementation challenges compelled us to modify our original plan and instead implement optimized chemical HLD using chlorine. Although testing showed improved bacterial burden from baseline, in our small number of samples, bacterial burden testing after implementing the optimized chemical HLD process did not differ significantly compared to steam-based HLD.

conclusionsOptimal chemical HLD was felt to be feasible and sustainable in the local setting. Reprocessing methods should be designed for unique challenges in low-resource settings.