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Measuring adherence to antiretroviral treatment in resource-poor settings: The clinical validity of key indicators

BACKGROUND: Access to antiretroviral therapy has dramatically expanded in Africa in recent years, but there are no validated approaches to measure treatment adherence in these settings. METHODS: In 16 health facilities, we observed a retrospective cohort of patients initiating antiretroviral therapy...

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Autores principales: Ross-Degnan, Dennis, Pierre-Jacques, Marsha, Zhang, Fang, Tadeg, Hailu, Gitau, Lillian, Ntaganira, Joseph, Balikuddembe, Robert, Chalker, John, Wagner, Anita K
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2834585/
https://www.ncbi.nlm.nih.gov/pubmed/20170478
http://dx.doi.org/10.1186/1472-6963-10-42
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author Ross-Degnan, Dennis
Pierre-Jacques, Marsha
Zhang, Fang
Tadeg, Hailu
Gitau, Lillian
Ntaganira, Joseph
Balikuddembe, Robert
Chalker, John
Wagner, Anita K
author_facet Ross-Degnan, Dennis
Pierre-Jacques, Marsha
Zhang, Fang
Tadeg, Hailu
Gitau, Lillian
Ntaganira, Joseph
Balikuddembe, Robert
Chalker, John
Wagner, Anita K
author_sort Ross-Degnan, Dennis
collection PubMed
description BACKGROUND: Access to antiretroviral therapy has dramatically expanded in Africa in recent years, but there are no validated approaches to measure treatment adherence in these settings. METHODS: In 16 health facilities, we observed a retrospective cohort of patients initiating antiretroviral therapy. We constructed eight indicators of adherence and visit attendance during the first 18 months of treatment from data in clinic and pharmacy records and attendance logs. We measured the correlation among these measures and assessed how well each predicted changes in weight and CD4 count. RESULTS: We followed 488 patients; 63.5% had 100% coverage of medicines during follow-up; 2.7% experienced a 30-day gap in treatment; 72.6% self-reported perfect adherence in all clinic visits; and 19.9% missed multiple clinic visits. After six months of treatment, mean weight gain was 3.9 kg and mean increase in CD4 count was 138.1 cells/mm3. Dispensing-based adherence, self-reported adherence, and consistent visit attendance were highly correlated. The first two types of adherence measure predicted gains in weight and CD4 count; consistent visit attendance was associated only with weight gain. CONCLUSIONS: This study demonstrates that routine data in African health facilities can be used to monitor antiretroviral adherence at the patient and system level.
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spelling pubmed-28345852010-03-09 Measuring adherence to antiretroviral treatment in resource-poor settings: The clinical validity of key indicators Ross-Degnan, Dennis Pierre-Jacques, Marsha Zhang, Fang Tadeg, Hailu Gitau, Lillian Ntaganira, Joseph Balikuddembe, Robert Chalker, John Wagner, Anita K BMC Health Serv Res Research article BACKGROUND: Access to antiretroviral therapy has dramatically expanded in Africa in recent years, but there are no validated approaches to measure treatment adherence in these settings. METHODS: In 16 health facilities, we observed a retrospective cohort of patients initiating antiretroviral therapy. We constructed eight indicators of adherence and visit attendance during the first 18 months of treatment from data in clinic and pharmacy records and attendance logs. We measured the correlation among these measures and assessed how well each predicted changes in weight and CD4 count. RESULTS: We followed 488 patients; 63.5% had 100% coverage of medicines during follow-up; 2.7% experienced a 30-day gap in treatment; 72.6% self-reported perfect adherence in all clinic visits; and 19.9% missed multiple clinic visits. After six months of treatment, mean weight gain was 3.9 kg and mean increase in CD4 count was 138.1 cells/mm3. Dispensing-based adherence, self-reported adherence, and consistent visit attendance were highly correlated. The first two types of adherence measure predicted gains in weight and CD4 count; consistent visit attendance was associated only with weight gain. CONCLUSIONS: This study demonstrates that routine data in African health facilities can be used to monitor antiretroviral adherence at the patient and system level. BioMed Central 2010-02-19 /pmc/articles/PMC2834585/ /pubmed/20170478 http://dx.doi.org/10.1186/1472-6963-10-42 Text en Copyright ©2010 Ross-Degnan et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research article
Ross-Degnan, Dennis
Pierre-Jacques, Marsha
Zhang, Fang
Tadeg, Hailu
Gitau, Lillian
Ntaganira, Joseph
Balikuddembe, Robert
Chalker, John
Wagner, Anita K
Measuring adherence to antiretroviral treatment in resource-poor settings: The clinical validity of key indicators
title Measuring adherence to antiretroviral treatment in resource-poor settings: The clinical validity of key indicators
title_full Measuring adherence to antiretroviral treatment in resource-poor settings: The clinical validity of key indicators
title_fullStr Measuring adherence to antiretroviral treatment in resource-poor settings: The clinical validity of key indicators
title_full_unstemmed Measuring adherence to antiretroviral treatment in resource-poor settings: The clinical validity of key indicators
title_short Measuring adherence to antiretroviral treatment in resource-poor settings: The clinical validity of key indicators
title_sort measuring adherence to antiretroviral treatment in resource-poor settings: the clinical validity of key indicators
topic Research article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2834585/
https://www.ncbi.nlm.nih.gov/pubmed/20170478
http://dx.doi.org/10.1186/1472-6963-10-42
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