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Using clinical cascades to measure health facilities’ obstetric emergency readiness: testing the cascade model using cross-sectional facility data in East Africa
OBJECTIVES: Globally, hundreds of women die daily from preventable pregnancy-related causes, with the greatest burden in sub-Saharan Africa. Five key emergencies—bleeding, infections, high blood pressure, delivery complications and unsafe abortions—account for nearly 75% of these obstetric deaths. S...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8981352/ https://www.ncbi.nlm.nih.gov/pubmed/35379635 http://dx.doi.org/10.1136/bmjopen-2021-057954 |
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author | Whaley, Bridget Butrick, Elizabeth Sales, Jessica M Wanyoro, Anthony Waiswa, Peter Walker, Dilys Cranmer, John N |
author_facet | Whaley, Bridget Butrick, Elizabeth Sales, Jessica M Wanyoro, Anthony Waiswa, Peter Walker, Dilys Cranmer, John N |
author_sort | Whaley, Bridget |
collection | PubMed |
description | OBJECTIVES: Globally, hundreds of women die daily from preventable pregnancy-related causes, with the greatest burden in sub-Saharan Africa. Five key emergencies—bleeding, infections, high blood pressure, delivery complications and unsafe abortions—account for nearly 75% of these obstetric deaths. Skilled clinicians with strategic supplies could prevent most deaths. In this study, we (1) measured facility readiness to manage common obstetric emergencies using the clinical cascades and signal function tracers; (2) compared these readiness estimates by facility characteristics; and (3) measured cascading drop-offs in resources. DESIGN: A facility-based cross-sectional analysis of resources for common obstetric emergencies. SETTING: Data were collected in 2016 from 23 hospitals (10 designated comprehensive emergency obstetric care (CEmOC) facilities) in Migori County, western Kenya, and Busoga Region, eastern Uganda, in the Preterm Birth Initiative study in East Africa. Baseline data were used to estimate a facility’s readiness to manage common obstetric emergencies using signal function tracers and the clinical cascade model. We compared emergency readiness using the proportion of facilities with tracers (signal functions) and the proportion with resources for identifying and treating the emergency (cascade stages 1 and 2). RESULTS: The signal functions overestimated practical emergency readiness by 23 percentage points across five emergencies. Only 42% of CEmOC-designated facilities could perform basic emergency obstetric care. Across the three stages of care (identify, treat and monitor-modify) for five emergencies, there was a 28% pooled mean drop-off in readiness. Across emergencies, the largest drop-off occurred in the treatment stage. Patterns of drop-off remained largely consistent across facility characteristics. CONCLUSIONS: Accurate measurement of obstetric emergency readiness is a prerequisite for strengthening facilities’ capacity to manage common emergencies. The cascades offer stepwise, emergency-specific readiness estimates designed to guide targeted maternal survival policies and programmes. TRIAL REGISTRATION NUMBER: NCT03112018. |
format | Online Article Text |
id | pubmed-8981352 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-89813522022-04-22 Using clinical cascades to measure health facilities’ obstetric emergency readiness: testing the cascade model using cross-sectional facility data in East Africa Whaley, Bridget Butrick, Elizabeth Sales, Jessica M Wanyoro, Anthony Waiswa, Peter Walker, Dilys Cranmer, John N BMJ Open Obstetrics and Gynaecology OBJECTIVES: Globally, hundreds of women die daily from preventable pregnancy-related causes, with the greatest burden in sub-Saharan Africa. Five key emergencies—bleeding, infections, high blood pressure, delivery complications and unsafe abortions—account for nearly 75% of these obstetric deaths. Skilled clinicians with strategic supplies could prevent most deaths. In this study, we (1) measured facility readiness to manage common obstetric emergencies using the clinical cascades and signal function tracers; (2) compared these readiness estimates by facility characteristics; and (3) measured cascading drop-offs in resources. DESIGN: A facility-based cross-sectional analysis of resources for common obstetric emergencies. SETTING: Data were collected in 2016 from 23 hospitals (10 designated comprehensive emergency obstetric care (CEmOC) facilities) in Migori County, western Kenya, and Busoga Region, eastern Uganda, in the Preterm Birth Initiative study in East Africa. Baseline data were used to estimate a facility’s readiness to manage common obstetric emergencies using signal function tracers and the clinical cascade model. We compared emergency readiness using the proportion of facilities with tracers (signal functions) and the proportion with resources for identifying and treating the emergency (cascade stages 1 and 2). RESULTS: The signal functions overestimated practical emergency readiness by 23 percentage points across five emergencies. Only 42% of CEmOC-designated facilities could perform basic emergency obstetric care. Across the three stages of care (identify, treat and monitor-modify) for five emergencies, there was a 28% pooled mean drop-off in readiness. Across emergencies, the largest drop-off occurred in the treatment stage. Patterns of drop-off remained largely consistent across facility characteristics. CONCLUSIONS: Accurate measurement of obstetric emergency readiness is a prerequisite for strengthening facilities’ capacity to manage common emergencies. The cascades offer stepwise, emergency-specific readiness estimates designed to guide targeted maternal survival policies and programmes. TRIAL REGISTRATION NUMBER: NCT03112018. BMJ Publishing Group 2022-04-03 /pmc/articles/PMC8981352/ /pubmed/35379635 http://dx.doi.org/10.1136/bmjopen-2021-057954 Text en © Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY. Published by BMJ. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Obstetrics and Gynaecology Whaley, Bridget Butrick, Elizabeth Sales, Jessica M Wanyoro, Anthony Waiswa, Peter Walker, Dilys Cranmer, John N Using clinical cascades to measure health facilities’ obstetric emergency readiness: testing the cascade model using cross-sectional facility data in East Africa |
title | Using clinical cascades to measure health facilities’ obstetric emergency readiness: testing the cascade model using cross-sectional facility data in East Africa |
title_full | Using clinical cascades to measure health facilities’ obstetric emergency readiness: testing the cascade model using cross-sectional facility data in East Africa |
title_fullStr | Using clinical cascades to measure health facilities’ obstetric emergency readiness: testing the cascade model using cross-sectional facility data in East Africa |
title_full_unstemmed | Using clinical cascades to measure health facilities’ obstetric emergency readiness: testing the cascade model using cross-sectional facility data in East Africa |
title_short | Using clinical cascades to measure health facilities’ obstetric emergency readiness: testing the cascade model using cross-sectional facility data in East Africa |
title_sort | using clinical cascades to measure health facilities’ obstetric emergency readiness: testing the cascade model using cross-sectional facility data in east africa |
topic | Obstetrics and Gynaecology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8981352/ https://www.ncbi.nlm.nih.gov/pubmed/35379635 http://dx.doi.org/10.1136/bmjopen-2021-057954 |
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