The MOMENTUM study: Putting the 'Three Delays' to work to evaluate access to emergency obstetric and neonatal care in a remote island community in Western Kenya
Despite worldwide improvements in maternal and infant mortality, mothers and babies in remote, low-resource communities remain disproportionately vulnerable to adverse health outcomes. In these settings, delays in accessing emergency care are a major driver of poor outcomes. The 'Three Delays...
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Veröffentlicht in: | Global public health 2020-07, Vol.15 (7), p.1016-1029 |
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Sprache: | eng |
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Zusammenfassung: | Despite worldwide improvements in maternal and infant mortality, mothers and babies in remote, low-resource communities remain disproportionately vulnerable to adverse health outcomes. In these settings, delays in accessing emergency care are a major driver of poor outcomes. The 'Three Delays' model is now widely utilised to conceptualise these delays. However, in out-of-hospital contexts, operational and methodological constraints present major obstacles in practically quantifying the 'Three Delays'. Here, we describe a novel protocol for the MOMENTUM study (Monitoring of Maternal Emergency Navigation and Triage on Mfangano), a 12-month cohort design to assess delays during obstetric and neonatal emergencies within the remote villages of Mfangano Island Division, Lake Victoria, Kenya. This study also evaluates the preliminary impact of a community-based intervention called the 'Mfangano Health Navigation' programme. Utilising participatory case audits and contextually specific chronological reference strategies, this study combines quantitative tools with deeper-digging qualitative inquiry. This pragmatic design was developed to empower local research staff and study participants themselves as assets in unravelling the complex socio-economic, cultural, and logistical dynamics that contribute to delays, while providing real-time feedback for locally driven intervention. We present our methods as an adaptive framework for researchers grappling with similar challenges across fragmented, rural health landscapes. |
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ISSN: | 1744-1692 1744-1706 |
DOI: | 10.1080/17441692.2020.1741662 |