Related Experiment Video
Updated: Aug 12, 2026
Assessment and Evaluation of the High Risk Neonate: The NICU Network Neurobehavioral Scale
Published on: August 25, 2014
Governance pathways for scaling neonatal risk stratification tools in LMIC health systems: a multi-site qualitative
Ronald Danny Nyatuka1, Faith Siva1, Md Shafiqur Rahman Jabin2
1School of Computing and Engineering Sciences, Strathmore University, Nairobi, Kenya.
Background:
Neonatal mortality remains disproportionately high in low- and middle-income countries (LMICs), where health systems frequently face workforce, infrastructure, and governance constraints. Although neonatal risk stratification tools have demonstrated potential to support the early identification of high-risk newborns, many digital health innovations fail to transition from pilot implementation to sustained institutional practice.
Objective:
This study examined governance and health system determinants influencing the scalability of a neonatal risk stratification tool across Kenyan health facilities and identified policy-relevant pathways for sustainable scale-up in resource-constrained settings.
Methods:
A multi-site qualitative implementation study was conducted across three Kenyan health facilities implementing a paper-based neonatal risk stratification tool during pilot deployment. Semi-structured key informant interviews, field observations, and implementation reflections were used to examine governance alignment, workflow integration, infrastructure readiness, staffing capacity, financing considerations, and sustainability challenges. Data were analyzed using reflexive thematic analysis informed by implementation science frameworks, including the Consolidated Framework for Implementation Research (CFIR) and the Nonadoption, Abandonment, Scale-up, Spread, and Sustainability (NASSS) framework.
Results:
Implementation sustainability was shaped primarily by system-level determinants rather than technological functionality alone. Three major themes emerged: (1) governance fragmentation constrained institutional integration through parallel documentation systems and administrative approval pathways; (2) structural capacity limitations, including workforce shortages, infrastructure instability, and financing uncertainty, reduced implementation sustainability; and (3) adaptive hybrid implementation approaches facilitated transitional scale-up within resource-constrained environments. Leadership engagement, contextual adaptation, and phased implementation strategies emerged as important enabling factors influencing implementation feasibility and organizational integration.
Conclusions:
Scaling neonatal risk stratification tools in LMIC health systems requires governance-oriented, system-sensitive implementation strategies that extend beyond technology deployment alone. Sustainable institutionalization depends on alignment across workforce capacity, infrastructure readiness, financing mechanisms, workflow integration, and policy coordination. Hybrid and phased implementation approaches may offer pragmatic pathways to scale neonatal digital health innovations in resource-constrained settings.
