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Individual interactions in a multi-country implementation-focused quality of care network for maternal, newborn and child health: A social network analysis
The Network for Improving Quality of Care for Maternal, Newborn and Child Health (QCN) was established to build a cross-country platform for joint-learning around quality improvement implementation approaches to reduce mortality. This paper describes and explores the structure of the QCN in four cou...
Autores principales: | , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10513266/ https://www.ncbi.nlm.nih.gov/pubmed/37733733 http://dx.doi.org/10.1371/journal.pgph.0001769 |
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author | Mukinda, Fidele Kanyimbu Djellouli, Nehla Akter, Kohenour Sarker, Mithun Tufa, Asebe Amenu Mwandira, Kondwani Seruwagi, Gloria Kyamulabi, Agnes Mwaba, Kasonde Marchant, Tanya Shawar, Yusra R. English, Mike Namakula, Hilda Gonfa, Geremew Colbourn, Tim Kinney, Mary V. |
author_facet | Mukinda, Fidele Kanyimbu Djellouli, Nehla Akter, Kohenour Sarker, Mithun Tufa, Asebe Amenu Mwandira, Kondwani Seruwagi, Gloria Kyamulabi, Agnes Mwaba, Kasonde Marchant, Tanya Shawar, Yusra R. English, Mike Namakula, Hilda Gonfa, Geremew Colbourn, Tim Kinney, Mary V. |
author_sort | Mukinda, Fidele Kanyimbu |
collection | PubMed |
description | The Network for Improving Quality of Care for Maternal, Newborn and Child Health (QCN) was established to build a cross-country platform for joint-learning around quality improvement implementation approaches to reduce mortality. This paper describes and explores the structure of the QCN in four countries and at global level. Using Social Network Analysis (SNA), this cross-sectional study maps the QCN networks at global level and in four countries (Bangladesh, Ethiopia, Malawi and Uganda) and assesses the interactions among actors involved. A pre-tested closed-ended structured questionnaire was completed by 303 key actors in early 2022 following purposeful and snowballing sampling. Data were entered into an online survey tool, and exported into Microsoft Excel for data management and analysis. This study received ethical approval as part of a broader evaluation. The SNA identified 566 actors across the four countries and at global level. Bangladesh, Malawi and Uganda had multiple-hub networks signifying multiple clusters of actors reflecting facility or district networks, whereas the network in Ethiopia and at global level had more centralized networks. There were some common features across the country networks, such as low overall density of the network, engagement of actors at all levels of the system, membership of related committees identified as the primary role of actors, and interactions spanning all types (learning, action and information sharing). The most connected actors were facility level actors in all countries except Ethiopia, which had mostly national level actors. The results reveal the uniqueness and complexity of each network assessed in the evaluation. They also affirm the broader qualitative evaluation assessing the nature of these networks, including composition and leadership. Gaps in communication between members of the network and limited interactions of actors between countries and with global level actors signal opportunities to strengthen QCN. |
format | Online Article Text |
id | pubmed-10513266 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-105132662023-09-22 Individual interactions in a multi-country implementation-focused quality of care network for maternal, newborn and child health: A social network analysis Mukinda, Fidele Kanyimbu Djellouli, Nehla Akter, Kohenour Sarker, Mithun Tufa, Asebe Amenu Mwandira, Kondwani Seruwagi, Gloria Kyamulabi, Agnes Mwaba, Kasonde Marchant, Tanya Shawar, Yusra R. English, Mike Namakula, Hilda Gonfa, Geremew Colbourn, Tim Kinney, Mary V. PLOS Glob Public Health Research Article The Network for Improving Quality of Care for Maternal, Newborn and Child Health (QCN) was established to build a cross-country platform for joint-learning around quality improvement implementation approaches to reduce mortality. This paper describes and explores the structure of the QCN in four countries and at global level. Using Social Network Analysis (SNA), this cross-sectional study maps the QCN networks at global level and in four countries (Bangladesh, Ethiopia, Malawi and Uganda) and assesses the interactions among actors involved. A pre-tested closed-ended structured questionnaire was completed by 303 key actors in early 2022 following purposeful and snowballing sampling. Data were entered into an online survey tool, and exported into Microsoft Excel for data management and analysis. This study received ethical approval as part of a broader evaluation. The SNA identified 566 actors across the four countries and at global level. Bangladesh, Malawi and Uganda had multiple-hub networks signifying multiple clusters of actors reflecting facility or district networks, whereas the network in Ethiopia and at global level had more centralized networks. There were some common features across the country networks, such as low overall density of the network, engagement of actors at all levels of the system, membership of related committees identified as the primary role of actors, and interactions spanning all types (learning, action and information sharing). The most connected actors were facility level actors in all countries except Ethiopia, which had mostly national level actors. The results reveal the uniqueness and complexity of each network assessed in the evaluation. They also affirm the broader qualitative evaluation assessing the nature of these networks, including composition and leadership. Gaps in communication between members of the network and limited interactions of actors between countries and with global level actors signal opportunities to strengthen QCN. Public Library of Science 2023-09-21 /pmc/articles/PMC10513266/ /pubmed/37733733 http://dx.doi.org/10.1371/journal.pgph.0001769 Text en © 2023 Mukinda et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Mukinda, Fidele Kanyimbu Djellouli, Nehla Akter, Kohenour Sarker, Mithun Tufa, Asebe Amenu Mwandira, Kondwani Seruwagi, Gloria Kyamulabi, Agnes Mwaba, Kasonde Marchant, Tanya Shawar, Yusra R. English, Mike Namakula, Hilda Gonfa, Geremew Colbourn, Tim Kinney, Mary V. Individual interactions in a multi-country implementation-focused quality of care network for maternal, newborn and child health: A social network analysis |
title | Individual interactions in a multi-country implementation-focused quality of care network for maternal, newborn and child health: A social network analysis |
title_full | Individual interactions in a multi-country implementation-focused quality of care network for maternal, newborn and child health: A social network analysis |
title_fullStr | Individual interactions in a multi-country implementation-focused quality of care network for maternal, newborn and child health: A social network analysis |
title_full_unstemmed | Individual interactions in a multi-country implementation-focused quality of care network for maternal, newborn and child health: A social network analysis |
title_short | Individual interactions in a multi-country implementation-focused quality of care network for maternal, newborn and child health: A social network analysis |
title_sort | individual interactions in a multi-country implementation-focused quality of care network for maternal, newborn and child health: a social network analysis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10513266/ https://www.ncbi.nlm.nih.gov/pubmed/37733733 http://dx.doi.org/10.1371/journal.pgph.0001769 |
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