Applying a multi-layered, mixed methods approach to evaluate technology and workforce interventions in Kenyan neonatal units

Understanding how to best implement healthcare innovations in resource-poor settings requires complex interventions and evaluations, often straining existing healthcare systems. We aimed to address this challenge in our Kenyan neonatal intervention research by deeply integrating stakeholder engagement, applying layered methodologies, and leveraging our research team's diverse expertise. This paper reports on the design and implementation of a research programme examining the impact of new staff introductions on care quality, staff, and family experiences within an existing neonatal technology programme in Kenya. Collaborating with stakeholders, our multidisciplinary programme of research included the analysis of routine health data before and after staff introductions, co-creation of novel quantitative data collection tools, and embedded qualitative research. Continuous feedback from participants, stakeholders, and researchers facilitated an adaptive approach, with timelines and methods adjusted to minimise participant burden. This iterative process allowed for robust data collection to inform health system improvements. Our findings provide insights into implementation and evaluation research for healthcare innovations in resource-constrained settings and emphasise ethical, context-sensitive research practices for sustainable health system strengthening.

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Publication Details

Journal
Global Health Action
Published
2025-09-25
DOI
https://doi.org/10.1080/16549716.2025.2558267
Citations
4
Primary Topic
Global Maternal and Child Health
Type
article
Field-Weighted Citation Impact
13.98
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article

Applying a multi-layered, mixed methods approach to evaluate technology and workforce interventions in Kenyan neonatal units

Dorothy Oluoch, Zainab Kioni, Onesmus Onyango, David Gathara et al.
4 citations
Global Health Action
Global Maternal and Child Health
13.98
article

Applying a multi-layered, mixed methods approach to evaluate technology and workforce interventions in Kenyan neonatal units

Dorothy Oluoch, Zainab Kioni, Onesmus Onyango, David Gathara, Fred Were, Asma Rababeh, Mike English, Vincent Kagonya, Lydia Thuranira, Naima Nasir, Edna Mutua, Loise Mwangi, Sassy Molyneux, Caroline Jones, Penina Musyoka, Lucy Kinyua, Abdulazeez Imam, Michuki Maina, Peter Mwangi, Gulraj Grewal, Sebastian Fuller, Gloria Karungo Ngaiza, Ngina Mwangi, Kenneth Karumba, Nancy Odinga, Caroline Waithira, Virginia Njoroge
article en
4 citations

Abstract

Understanding how to best implement healthcare innovations in resource-poor settings requires complex interventions and evaluations, often straining existing healthcare systems. We aimed to address this challenge in our Kenyan neonatal intervention research by deeply integrating stakeholder engagement, applying layered methodologies, and leveraging our research team's diverse expertise. This paper reports on the design and implementation of a research programme examining the impact of new staff introductions on care quality, staff, and family experiences within an existing neonatal technology programme in Kenya. Collaborating with stakeholders, our multidisciplinary programme of research included the analysis of routine health data before and after staff introductions, co-creation of novel quantitative data collection tools, and embedded qualitative research. Continuous feedback from participants, stakeholders, and researchers facilitated an adaptive approach, with timelines and methods adjusted to minimise participant burden. This iterative process allowed for robust data collection to inform health system improvements. Our findings provide insights into implementation and evaluation research for healthcare innovations in resource-constrained settings and emphasise ethical, context-sensitive research practices for sustainable health system strengthening.

Global Health ActionVol. 18(1)
Machakos University (KE), Kenya Medical Research Institute (KE), University of Embu (KE), University of Oxford (GB), Kenya School of Government (KE), Machakos School (KE), People's Government of Shaanxi Province (CN)
Openalex Percentile: Top 1%
Global Maternal and Child Health
13.98
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