Good practices to optimise the performance of maternal and neonatal quality improvement teams: Results from a longitudinal qualitative evaluation in South Africa, before, and during COVID-19

Many maternal and neonatal deaths can be avoided if quality healthcare is provided. To this end, the South African National Department of Health implemented a quality improvement (QI) programme (2018-2022) to improve maternal and neonatal health services in 21 public health facilities. This study so...

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Published inPloS one Vol. 19; no. 11; p. e0314024
Main Authors Odendaal, Willem, Tomlinson, Mark, Goga, Ameena, Singh, Yages, Kauchali, Shuaib, Marshall, Carol, Pillay, Yogan, Makua, Manala, Chetty, Terusha, Hunt, Xanthe
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LanguageEnglish
Published United States Public Library of Science 19.11.2024
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Abstract Many maternal and neonatal deaths can be avoided if quality healthcare is provided. To this end, the South African National Department of Health implemented a quality improvement (QI) programme (2018-2022) to improve maternal and neonatal health services in 21 public health facilities. This study sought to identify good practices aimed at improving QI teams' performance by identifying optimal facility-level contextual factors and implementation processes. We purposively selected 14 facilities of the 21 facilities for a longitudinal qualitative process evaluation. We interviewed 17 team leaders, 47 members, and five QI advisors who provided technical support to the teams. The data were analysed using framework analysis. We choose the Consolidated Framework for Implementation Research as framework given that it explicates contexts and processes that shape programme implementation. Six quality improvement teams were assessed as well-performing, and eight as less well-performing. This research conceptualises a 'life course lens' for setting up and managing a QI team. We identified eight good practices, six related to implementation processes, and two contextual variables that will optimise team performance. The two most impactful practices to improve the performance of a QI team were (i) selecting healthcare workers with quality improvement-specific characteristics, and (ii) appointing advisors whose interpersonal skills match their technical quality improvement competencies.
AbstractList Many maternal and neonatal deaths can be avoided if quality healthcare is provided. To this end, the South African National Department of Health implemented a quality improvement (QI) programme (2018-2022) to improve maternal and neonatal health services in 21 public health facilities. This study sought to identify good practices aimed at improving QI teams' performance by identifying optimal facility-level contextual factors and implementation processes. We purposively selected 14 facilities of the 21 facilities for a longitudinal qualitative process evaluation. We interviewed 17 team leaders, 47 members, and five QI advisors who provided technical support to the teams. The data were analysed using framework analysis. We choose the Consolidated Framework for Implementation Research as framework given that it explicates contexts and processes that shape programme implementation. Six quality improvement teams were assessed as well-performing, and eight as less well-performing. This research conceptualises a 'life course lens' for setting up and managing a QI team. We identified eight good practices, six related to implementation processes, and two contextual variables that will optimise team performance. The two most impactful practices to improve the performance of a QI team were (i) selecting healthcare workers with quality improvement-specific characteristics, and (ii) appointing advisors whose interpersonal skills match their technical quality improvement competencies.
Many maternal and neonatal deaths can be avoided if quality healthcare is provided. To this end, the South African National Department of Health implemented a quality improvement (QI) programme (2018-2022) to improve maternal and neonatal health services in 21 public health facilities. This study sought to identify good practices aimed at improving QI teams' performance by identifying optimal facility-level contextual factors and implementation processes. We purposively selected 14 facilities of the 21 facilities for a longitudinal qualitative process evaluation. We interviewed 17 team leaders, 47 members, and five QI advisors who provided technical support to the teams. The data were analysed using framework analysis. We choose the Consolidated Framework for Implementation Research as framework given that it explicates contexts and processes that shape programme implementation. Six quality improvement teams were assessed as well-performing, and eight as less well-performing. This research conceptualises a 'life course lens' for setting up and managing a QI team. We identified eight good practices, six related to implementation processes, and two contextual variables that will optimise team performance. The two most impactful practices to improve the performance of a QI team were (i) selecting healthcare workers with quality improvement-specific characteristics, and (ii) appointing advisors whose interpersonal skills match their technical quality improvement competencies.Many maternal and neonatal deaths can be avoided if quality healthcare is provided. To this end, the South African National Department of Health implemented a quality improvement (QI) programme (2018-2022) to improve maternal and neonatal health services in 21 public health facilities. This study sought to identify good practices aimed at improving QI teams' performance by identifying optimal facility-level contextual factors and implementation processes. We purposively selected 14 facilities of the 21 facilities for a longitudinal qualitative process evaluation. We interviewed 17 team leaders, 47 members, and five QI advisors who provided technical support to the teams. The data were analysed using framework analysis. We choose the Consolidated Framework for Implementation Research as framework given that it explicates contexts and processes that shape programme implementation. Six quality improvement teams were assessed as well-performing, and eight as less well-performing. This research conceptualises a 'life course lens' for setting up and managing a QI team. We identified eight good practices, six related to implementation processes, and two contextual variables that will optimise team performance. The two most impactful practices to improve the performance of a QI team were (i) selecting healthcare workers with quality improvement-specific characteristics, and (ii) appointing advisors whose interpersonal skills match their technical quality improvement competencies.
Audience Academic
Author Pillay, Yogan
Chetty, Terusha
Odendaal, Willem
Singh, Yages
Goga, Ameena
Marshall, Carol
Makua, Manala
Kauchali, Shuaib
Hunt, Xanthe
Tomlinson, Mark
AuthorAffiliation 2 Department of Psychiatry, Stellenbosch University, Cape Town, Western Cape, South Africa
4 Institute for Life Course Health Research, Stellenbosch University, Cape Town, Western Cape, South Africa
8 South African National Department of Health, Pretoria, Gauteng, South Africa
11 University of South Africa, Pretoria, Gauteng, South Africa
3 Health Systems Research Unit, South African Medical Research Council, Cape Town, Western Cape, South Africa
5 School of Nursing and Midwifery, Queens University, Belfast, United Kingdom
12 Discipline of Public Health Medicine, School of Nursing and Public Health, University of KwaZulu-Natal, Durban, KwaZulu-Natal, South Africa
9 Clinton Health Access Initiative, Pretoria, Gauteng, South Africa (formerly)
LSTM: Liverpool School of Tropical Medicine, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND
6 Department of Paediatrics and Child Health, University of Pretoria, Pretoria, Gauteng, South Africa
10 Division of Public Health and Health Systems, Department
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BackLink https://www.ncbi.nlm.nih.gov/pubmed/39561133$$D View this record in MEDLINE/PubMed
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Copyright Copyright: © 2024 Odendaal et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
COPYRIGHT 2024 Public Library of Science
2024 Odendaal et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
2024 Odendaal et al 2024 Odendaal et al
2024 Odendaal et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
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– notice: 2024 Odendaal et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
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License Copyright: © 2024 Odendaal et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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Competing Interests: NO authors have competing interests The authors have declared that no competing interests exist.
TC and XH are joint senior authors on this work.
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Snippet Many maternal and neonatal deaths can be avoided if quality healthcare is provided. To this end, the South African National Department of Health implemented a...
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SubjectTerms Advisors
Analysis
Biology and Life Sciences
COVID-19
COVID-19 - epidemiology
Female
Health care
Health care facilities
Health care reform
Health services
HIV
Hospitals
Human immunodeficiency virus
Humans
Infant mortality
Infant, Newborn
Infants
Infants (Newborn)
Longitudinal Studies
Maternal health services
Maternal Health Services - organization & administration
Maternal Health Services - standards
Medical care
Medical personnel
Medical research
Medicine and Health Sciences
Mothers
Neonates
Neonatology
Optimization
Participation
Patient outcomes
People and Places
Performance enhancement
Performance evaluation
Pregnancy
Public health
Qualitative analysis
Qualitative Research
Quality control
Quality Improvement
Quality management
SARS-CoV-2
Social Sciences
South Africa - epidemiology
Stillbirth
Team leaders
Teams
Work groups
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Title Good practices to optimise the performance of maternal and neonatal quality improvement teams: Results from a longitudinal qualitative evaluation in South Africa, before, and during COVID-19
URI https://www.ncbi.nlm.nih.gov/pubmed/39561133
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https://pubmed.ncbi.nlm.nih.gov/PMC11575831
https://doaj.org/article/46bc2fadad224c23bd3bd403279ef06f
http://dx.doi.org/10.1371/journal.pone.0314024
Volume 19
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