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Proactive case detection of common childhood illnesses by community health workers: a systematic review
INTRODUCTION: Identifying design features and implementation strategies to optimise community health worker (CHW) programmes is important in the context of mixed results at scale. We systematically reviewed evidence of the effects of proactive case detection by CHWs in low-income and middle-income c...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6936477/ https://www.ncbi.nlm.nih.gov/pubmed/31908858 http://dx.doi.org/10.1136/bmjgh-2019-001799 |
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author | Whidden, Caroline Thwing, Julie Gutman, Julie Wohl, Ethan Leyrat, Clémence Kayentao, Kassoum Johnson, Ari David Greenwood, Brian Chandramohan, Daniel |
author_facet | Whidden, Caroline Thwing, Julie Gutman, Julie Wohl, Ethan Leyrat, Clémence Kayentao, Kassoum Johnson, Ari David Greenwood, Brian Chandramohan, Daniel |
author_sort | Whidden, Caroline |
collection | PubMed |
description | INTRODUCTION: Identifying design features and implementation strategies to optimise community health worker (CHW) programmes is important in the context of mixed results at scale. We systematically reviewed evidence of the effects of proactive case detection by CHWs in low-income and middle-income countries (LMICs) on mortality, morbidity and access to care for common childhood illnesses. METHODS: Published studies were identified via electronic databases from 1978 to 2017. We included randomised and non-randomised controlled trials, controlled before–after studies and interrupted time series studies, and assessed their quality for risk of bias. We reported measures of effect as study investigators reported them, and synthesised by outcomes of mortality, disease prevalence, hospitalisation and access to treatment. We calculated risk ratios (RRs) as a principal summary measure, with CIs adjusted for cluster design effect. RESULTS: We identified 14 studies of 11 interventions from nine LMICs that met inclusion criteria. They showed considerable diversity in intervention design and implementation, comparison, outcomes and study quality, which precluded meta-analysis. Proactive case detection may reduce infant mortality (RR: 0.52–0.94) and increase access to effective treatment (RR: 1.59–4.64) compared with conventional community-based healthcare delivery (low certainty evidence). It is uncertain whether proactive case detection reduces mortality among children under 5 years (RR: 0.04–0.80), prevalence of infectious diseases (RR: 0.06–1.02), hospitalisation (RR: 0.38–1.26) or increases access to prompt treatment (RR: 1.00–2.39) because the certainty of this evidence is very low. CONCLUSION: Proactive case detection may provide promising benefits for child health, but evidence is insufficient to draw conclusions. More research is needed on proactive case detection with rigorous study designs that use standardised outcomes and measurement methods, and report more detail on complex intervention design and implementation. PROSPERO REGISTRATION NUMBER: CRD42017074621. |
format | Online Article Text |
id | pubmed-6936477 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-69364772020-01-06 Proactive case detection of common childhood illnesses by community health workers: a systematic review Whidden, Caroline Thwing, Julie Gutman, Julie Wohl, Ethan Leyrat, Clémence Kayentao, Kassoum Johnson, Ari David Greenwood, Brian Chandramohan, Daniel BMJ Glob Health Research INTRODUCTION: Identifying design features and implementation strategies to optimise community health worker (CHW) programmes is important in the context of mixed results at scale. We systematically reviewed evidence of the effects of proactive case detection by CHWs in low-income and middle-income countries (LMICs) on mortality, morbidity and access to care for common childhood illnesses. METHODS: Published studies were identified via electronic databases from 1978 to 2017. We included randomised and non-randomised controlled trials, controlled before–after studies and interrupted time series studies, and assessed their quality for risk of bias. We reported measures of effect as study investigators reported them, and synthesised by outcomes of mortality, disease prevalence, hospitalisation and access to treatment. We calculated risk ratios (RRs) as a principal summary measure, with CIs adjusted for cluster design effect. RESULTS: We identified 14 studies of 11 interventions from nine LMICs that met inclusion criteria. They showed considerable diversity in intervention design and implementation, comparison, outcomes and study quality, which precluded meta-analysis. Proactive case detection may reduce infant mortality (RR: 0.52–0.94) and increase access to effective treatment (RR: 1.59–4.64) compared with conventional community-based healthcare delivery (low certainty evidence). It is uncertain whether proactive case detection reduces mortality among children under 5 years (RR: 0.04–0.80), prevalence of infectious diseases (RR: 0.06–1.02), hospitalisation (RR: 0.38–1.26) or increases access to prompt treatment (RR: 1.00–2.39) because the certainty of this evidence is very low. CONCLUSION: Proactive case detection may provide promising benefits for child health, but evidence is insufficient to draw conclusions. More research is needed on proactive case detection with rigorous study designs that use standardised outcomes and measurement methods, and report more detail on complex intervention design and implementation. PROSPERO REGISTRATION NUMBER: CRD42017074621. BMJ Publishing Group 2019-12-15 /pmc/articles/PMC6936477/ /pubmed/31908858 http://dx.doi.org/10.1136/bmjgh-2019-001799 Text en © Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/. |
spellingShingle | Research Whidden, Caroline Thwing, Julie Gutman, Julie Wohl, Ethan Leyrat, Clémence Kayentao, Kassoum Johnson, Ari David Greenwood, Brian Chandramohan, Daniel Proactive case detection of common childhood illnesses by community health workers: a systematic review |
title | Proactive case detection of common childhood illnesses by community health workers: a systematic review |
title_full | Proactive case detection of common childhood illnesses by community health workers: a systematic review |
title_fullStr | Proactive case detection of common childhood illnesses by community health workers: a systematic review |
title_full_unstemmed | Proactive case detection of common childhood illnesses by community health workers: a systematic review |
title_short | Proactive case detection of common childhood illnesses by community health workers: a systematic review |
title_sort | proactive case detection of common childhood illnesses by community health workers: a systematic review |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6936477/ https://www.ncbi.nlm.nih.gov/pubmed/31908858 http://dx.doi.org/10.1136/bmjgh-2019-001799 |
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