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Identifying models of HIV care and treatment service delivery in Tanzania, Uganda, and Zambia using cluster analysis and Delphi survey
BACKGROUND: Organization of HIV care and treatment services, including clinic staffing and services, may shape clinical and financial outcomes, yet there has been little attempt to describe different models of HIV care in sub-Saharan Africa (SSA). Information about the relative benefits and drawback...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5717830/ https://www.ncbi.nlm.nih.gov/pubmed/29207973 http://dx.doi.org/10.1186/s12913-017-2772-4 |
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author | Tsui, Sharon Denison, Julie A. Kennedy, Caitlin E. Chang, Larry W. Koole, Olivier Torpey, Kwasi Van Praag, Eric Farley, Jason Ford, Nathan Stuart, Leine Wabwire-Mangen, Fred |
author_facet | Tsui, Sharon Denison, Julie A. Kennedy, Caitlin E. Chang, Larry W. Koole, Olivier Torpey, Kwasi Van Praag, Eric Farley, Jason Ford, Nathan Stuart, Leine Wabwire-Mangen, Fred |
author_sort | Tsui, Sharon |
collection | PubMed |
description | BACKGROUND: Organization of HIV care and treatment services, including clinic staffing and services, may shape clinical and financial outcomes, yet there has been little attempt to describe different models of HIV care in sub-Saharan Africa (SSA). Information about the relative benefits and drawbacks of different models could inform the scale-up of antiretroviral therapy (ART) and associated services in resource-limited settings (RLS), especially in light of expanded client populations with country adoption of WHO’s test and treat recommendation. METHODS: We characterized task-shifting/task-sharing practices in 19 diverse ART clinics in Tanzania, Uganda, and Zambia and used cluster analysis to identify unique models of service provision. We ran descriptive statistics to explore how the clusters varied by environmental factors and programmatic characteristics. Finally, we employed the Delphi Method to make systematic use of expert opinions to ensure that the cluster variables were meaningful in the context of actual task-shifting of ART services in SSA. RESULTS: The cluster analysis identified three task-shifting/task-sharing models. The main differences across models were the availability of medical doctors, the scope of clinical responsibility assigned to nurses, and the use of lay health care workers. Patterns of healthcare staffing in HIV service delivery were associated with different environmental factors (e.g., health facility levels, urban vs. rural settings) and programme characteristics (e.g., community ART distribution or integrated tuberculosis treatment on-site). CONCLUSIONS: Understanding the relative advantages and disadvantages of different models of care can help national programmes adapt to increased client load, select optimal adherence strategies within decentralized models of care, and identify differentiated models of care for clients to meet the growing needs of long-term ART patients who require more complicated treatment management. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12913-017-2772-4) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5717830 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-57178302017-12-08 Identifying models of HIV care and treatment service delivery in Tanzania, Uganda, and Zambia using cluster analysis and Delphi survey Tsui, Sharon Denison, Julie A. Kennedy, Caitlin E. Chang, Larry W. Koole, Olivier Torpey, Kwasi Van Praag, Eric Farley, Jason Ford, Nathan Stuart, Leine Wabwire-Mangen, Fred BMC Health Serv Res Research Article BACKGROUND: Organization of HIV care and treatment services, including clinic staffing and services, may shape clinical and financial outcomes, yet there has been little attempt to describe different models of HIV care in sub-Saharan Africa (SSA). Information about the relative benefits and drawbacks of different models could inform the scale-up of antiretroviral therapy (ART) and associated services in resource-limited settings (RLS), especially in light of expanded client populations with country adoption of WHO’s test and treat recommendation. METHODS: We characterized task-shifting/task-sharing practices in 19 diverse ART clinics in Tanzania, Uganda, and Zambia and used cluster analysis to identify unique models of service provision. We ran descriptive statistics to explore how the clusters varied by environmental factors and programmatic characteristics. Finally, we employed the Delphi Method to make systematic use of expert opinions to ensure that the cluster variables were meaningful in the context of actual task-shifting of ART services in SSA. RESULTS: The cluster analysis identified three task-shifting/task-sharing models. The main differences across models were the availability of medical doctors, the scope of clinical responsibility assigned to nurses, and the use of lay health care workers. Patterns of healthcare staffing in HIV service delivery were associated with different environmental factors (e.g., health facility levels, urban vs. rural settings) and programme characteristics (e.g., community ART distribution or integrated tuberculosis treatment on-site). CONCLUSIONS: Understanding the relative advantages and disadvantages of different models of care can help national programmes adapt to increased client load, select optimal adherence strategies within decentralized models of care, and identify differentiated models of care for clients to meet the growing needs of long-term ART patients who require more complicated treatment management. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12913-017-2772-4) contains supplementary material, which is available to authorized users. BioMed Central 2017-12-06 /pmc/articles/PMC5717830/ /pubmed/29207973 http://dx.doi.org/10.1186/s12913-017-2772-4 Text en © The Author(s). 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Tsui, Sharon Denison, Julie A. Kennedy, Caitlin E. Chang, Larry W. Koole, Olivier Torpey, Kwasi Van Praag, Eric Farley, Jason Ford, Nathan Stuart, Leine Wabwire-Mangen, Fred Identifying models of HIV care and treatment service delivery in Tanzania, Uganda, and Zambia using cluster analysis and Delphi survey |
title | Identifying models of HIV care and treatment service delivery in Tanzania, Uganda, and Zambia using cluster analysis and Delphi survey |
title_full | Identifying models of HIV care and treatment service delivery in Tanzania, Uganda, and Zambia using cluster analysis and Delphi survey |
title_fullStr | Identifying models of HIV care and treatment service delivery in Tanzania, Uganda, and Zambia using cluster analysis and Delphi survey |
title_full_unstemmed | Identifying models of HIV care and treatment service delivery in Tanzania, Uganda, and Zambia using cluster analysis and Delphi survey |
title_short | Identifying models of HIV care and treatment service delivery in Tanzania, Uganda, and Zambia using cluster analysis and Delphi survey |
title_sort | identifying models of hiv care and treatment service delivery in tanzania, uganda, and zambia using cluster analysis and delphi survey |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5717830/ https://www.ncbi.nlm.nih.gov/pubmed/29207973 http://dx.doi.org/10.1186/s12913-017-2772-4 |
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