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Health system determinants of tuberculosis mortality in South Africa: a causal loop model
BACKGROUND: Tuberculosis (TB) is a major public health concern in South Africa and TB-related mortality remains unacceptably high. Numerous clinical studies have examined the direct causes of TB-related mortality, but its wider, systemic drivers are less well understood. Applying systems thinking, w...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8074279/ https://www.ncbi.nlm.nih.gov/pubmed/33902565 http://dx.doi.org/10.1186/s12913-021-06398-0 |
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author | Osman, Muhammad Karat, Aaron S Khan, Munira Meehan, Sue-Ann von Delft, Arne Brey, Zameer Charalambous, Salome Hesseling, Anneke C Naidoo, Pren Loveday, Marian |
author_facet | Osman, Muhammad Karat, Aaron S Khan, Munira Meehan, Sue-Ann von Delft, Arne Brey, Zameer Charalambous, Salome Hesseling, Anneke C Naidoo, Pren Loveday, Marian |
author_sort | Osman, Muhammad |
collection | PubMed |
description | BACKGROUND: Tuberculosis (TB) is a major public health concern in South Africa and TB-related mortality remains unacceptably high. Numerous clinical studies have examined the direct causes of TB-related mortality, but its wider, systemic drivers are less well understood. Applying systems thinking, we aimed to identify factors underlying TB mortality in South Africa and describe their relationships. At a meeting organised by the ‘Optimising TB Treatment Outcomes’ task team of the National TB Think Tank, we drew on the wide expertise of attendees to identify factors underlying TB mortality in South Africa. We generated a causal loop diagram to illustrate how these factors relate to each other. RESULTS: Meeting attendees identified nine key variables: three ‘drivers’ (adequacy & availability of tools, implementation of guidelines, and the burden of bureaucracy); three ‘links’ (integration of health services, integration of data systems, and utilisation of prevention strategies); and three ‘outcomes’ (accessibility of services, patient empowerment, and socio-economic status). Through the development and refinement of the causal loop diagram, additional explanatory and linking variables were added and three important reinforcing loops identified. Loop 1, ‘Leadership and management for outcomes’ illustrated that poor leadership led to increased bureaucracy and reduced the accessibility of TB services, which increased TB-related mortality and reinforced poor leadership through patient empowerment. Loop 2, ‘Prevention and structural determinants’ describes the complex reinforcing loop between socio-economic status, patient empowerment, the poor uptake of TB and HIV prevention strategies and increasing TB mortality. Loop 3, ‘System capacity’ describes how fragmented leadership and limited resources compromise the workforce and the performance and accessibility of TB services, and how this negatively affects the demand for higher levels of stewardship. CONCLUSIONS: Strengthening leadership, reducing bureaucracy, improving integration across all levels of the system, increasing health care worker support, and using windows of opportunity to target points of leverage within the South African health system are needed to both strengthen the system and reduce TB mortality. Further refinement of this model may allow for the identification of additional areas of intervention. |
format | Online Article Text |
id | pubmed-8074279 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-80742792021-04-26 Health system determinants of tuberculosis mortality in South Africa: a causal loop model Osman, Muhammad Karat, Aaron S Khan, Munira Meehan, Sue-Ann von Delft, Arne Brey, Zameer Charalambous, Salome Hesseling, Anneke C Naidoo, Pren Loveday, Marian BMC Health Serv Res Research Article BACKGROUND: Tuberculosis (TB) is a major public health concern in South Africa and TB-related mortality remains unacceptably high. Numerous clinical studies have examined the direct causes of TB-related mortality, but its wider, systemic drivers are less well understood. Applying systems thinking, we aimed to identify factors underlying TB mortality in South Africa and describe their relationships. At a meeting organised by the ‘Optimising TB Treatment Outcomes’ task team of the National TB Think Tank, we drew on the wide expertise of attendees to identify factors underlying TB mortality in South Africa. We generated a causal loop diagram to illustrate how these factors relate to each other. RESULTS: Meeting attendees identified nine key variables: three ‘drivers’ (adequacy & availability of tools, implementation of guidelines, and the burden of bureaucracy); three ‘links’ (integration of health services, integration of data systems, and utilisation of prevention strategies); and three ‘outcomes’ (accessibility of services, patient empowerment, and socio-economic status). Through the development and refinement of the causal loop diagram, additional explanatory and linking variables were added and three important reinforcing loops identified. Loop 1, ‘Leadership and management for outcomes’ illustrated that poor leadership led to increased bureaucracy and reduced the accessibility of TB services, which increased TB-related mortality and reinforced poor leadership through patient empowerment. Loop 2, ‘Prevention and structural determinants’ describes the complex reinforcing loop between socio-economic status, patient empowerment, the poor uptake of TB and HIV prevention strategies and increasing TB mortality. Loop 3, ‘System capacity’ describes how fragmented leadership and limited resources compromise the workforce and the performance and accessibility of TB services, and how this negatively affects the demand for higher levels of stewardship. CONCLUSIONS: Strengthening leadership, reducing bureaucracy, improving integration across all levels of the system, increasing health care worker support, and using windows of opportunity to target points of leverage within the South African health system are needed to both strengthen the system and reduce TB mortality. Further refinement of this model may allow for the identification of additional areas of intervention. BioMed Central 2021-04-26 /pmc/articles/PMC8074279/ /pubmed/33902565 http://dx.doi.org/10.1186/s12913-021-06398-0 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Article Osman, Muhammad Karat, Aaron S Khan, Munira Meehan, Sue-Ann von Delft, Arne Brey, Zameer Charalambous, Salome Hesseling, Anneke C Naidoo, Pren Loveday, Marian Health system determinants of tuberculosis mortality in South Africa: a causal loop model |
title | Health system determinants of tuberculosis mortality in South Africa: a causal loop model |
title_full | Health system determinants of tuberculosis mortality in South Africa: a causal loop model |
title_fullStr | Health system determinants of tuberculosis mortality in South Africa: a causal loop model |
title_full_unstemmed | Health system determinants of tuberculosis mortality in South Africa: a causal loop model |
title_short | Health system determinants of tuberculosis mortality in South Africa: a causal loop model |
title_sort | health system determinants of tuberculosis mortality in south africa: a causal loop model |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8074279/ https://www.ncbi.nlm.nih.gov/pubmed/33902565 http://dx.doi.org/10.1186/s12913-021-06398-0 |
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