Evidence map›Paper›PMID 42577112›Full record

ArticleFrontiers in digital health2026

Governance pathways for scaling neonatal risk stratification tools in LMIC health systems: a multi-site qualitative study in Kenya.

Ronald Danny Nyatuka, Faith Siva, Md Shafiqur Rahman Jabin

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Ronald Danny NyatukaSchool of Computing and Engineering Sciences, Strathmore University, Nairobi, Kenya.
Faith SivaSchool of Computing and Engineering Sciences, Strathmore University, Nairobi, Kenya.
Md Shafiqur Rahman JabinDepartment of Medicine and Optometry, Linnaeus University, Kalmar, Sweden.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

clinical workflowdigital transformationhealth policyimplementation scienceinstitutionalizationorganizational readiness

Identifiers

PMID42577112
PMCPMC13453704

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.