JMIR Publications

ABSTRACT

Background:

Background:

In the last two decades, neonatal mortality has significantly reduced globally. However, it still contributes to almost half of the deaths of children under five years of age. Improving access to quality health care during pregnancy, childbirth and postpartum is urgently needed in Low- and Middle-Income Countries (LMICS) to ensure that the sustainable development goal (SDG) targets for neonatal and infant mortality are met. Healthcare delivery in low resource settings is characterised as fragmented, with poorly staffed health facilities working in silos with limited opportunity for cross learning and collaboration. Neotree, a digital health intervention, has been developed and implemented in Zimbabwe and Malawi to improve neonatal survival by optimising and standardising the quality of newborn care in health facilities linked in a network of care. Understanding the key factors that affect the success of Neotree implementation and its effectiveness in a network of health facilities will inform the development of a scale-up plan which is context specific and robust.

Objective:

Objective:

We aim to understand how Neotree is implemented and used in a network of health facilities in Kasungu district for the care of newborns, the intervention mechanisms of action and the contextual factors that affect both implementation and intervention effectiveness.

Methods:

Method: We designed a mixed methods process evaluation as part of a wider effectiveness and economic evaluation of Neotree across a network of 11 health facilities, in Kasungu district, Malawi. The evaluation is guided by the RE-AIM (reach, effectiveness, adoption, implementation and maintenance) framework, the realist approach, and other implementation science frameworks. Methods include periodic analysis of routine newborn data (collected via Neotree), qualitative interviews and focus group discussions with stakeholders, direct observations of newborn care, health facility and healthcare provider surveys and review of documents related to the implementation plans, processes and reports. Data will be collected over multiple rounds between December 2024 and December 2027.

Results:

Result: This research project was initiated in December 2024. As of December 2026, all 11 health facilities were enrolled into the intervention. Routine clinical data are being captured using Neotree and data collection for the mixed methods process evaluation is underway.

Conclusions:

this study will identify barriers and facilitators of successful implementation of a learning digital health system tool, Neotree in a low resource setting. It will enable us to explain the mechanism by which Neotree could contribute to quality of healthcare and better health outcome for the newborns. Furthermore, the result of the study will guide future scaleup of Neotree in Malawi and other similar settings.