ArticleFrontiers in digital health2026
Governance pathways for scaling neonatal risk stratification tools in LMIC health systems: a multi-site qualitative study in Kenya.
Article in Frontiers in digital health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Usability and Workflow Integration of a Machine Learning-Derived Neonatal Risk Predictor in Kenyan Neonatal Units: Multisite User-Centered Pilot Evaluation.JMIR human factors · 2026Article
- Governance and implementation of solar-powered digital health systems in low- and middle-income countries: a mixed-methods study from Kenya and Ethiopia.Frontiers in digital health · 2026Article
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Authors and funding
3 authors.
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Abstract
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.
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