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Impact of community tracer teams on treatment outcomes among tuberculosis patients in South Africa
BACKGROUND: Tuberculosis (TB) indicators in South Africa currently remain well below global targets. In 2008, the National Tuberculosis Program (NTP) implemented a community mobilization program in all nine provinces to trace TB patients that had missed a treatment or clinic visit. Implementation si...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3490985/ https://www.ncbi.nlm.nih.gov/pubmed/22871071 http://dx.doi.org/10.1186/1471-2458-12-621 |
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author | Bronner, Liza E Podewils, Laura J Peters, Annatjie Somnath, Pushpakanthi Nshuti, Lorna van der Walt, Martie Mametja, Lerole David |
author_facet | Bronner, Liza E Podewils, Laura J Peters, Annatjie Somnath, Pushpakanthi Nshuti, Lorna van der Walt, Martie Mametja, Lerole David |
author_sort | Bronner, Liza E |
collection | PubMed |
description | BACKGROUND: Tuberculosis (TB) indicators in South Africa currently remain well below global targets. In 2008, the National Tuberculosis Program (NTP) implemented a community mobilization program in all nine provinces to trace TB patients that had missed a treatment or clinic visit. Implementation sites were selected by TB program managers and teams liaised with health facilities to identify patients for tracing activities. The objective of this analysis was to assess the impact of the TB Tracer Project on treatment outcomes among TB patients. METHODS: The study population included all smear positive TB patients registered in the Electronic TB Registry from Quarter 1 2007-Quarter 1 2009 in South Africa. Subdistricts were used as the unit of analysis, with each designated as either tracer (standard TB program plus tracer project) or non-tracer (standard TB program only). Mixed linear regression models were utilized to calculate the percent quarterly change in treatment outcomes and to compare changes in treatment outcomes from Quarter 1 2007 to Quarter 1 2009 between tracer and non-tracer subdistricts. RESULTS: For all provinces combined, the percent quarterly change decreased significantly for default treatment outcomes among tracer subdistricts (−0.031%; p < 0.001) and increased significantly for successful treatment outcomes among tracer subdistricts (0.003%; p = 0.03). A significant decrease in the proportion of patient default was observed for all provinces combined over the time period comparing tracer and non-tracer subdistricts (p = 0.02). Examination in stratified models revealed the results were not consistent across all provinces; significant differences were observed between tracer and non-tracer subdistricts over time in five of nine provinces for treatment default. CONCLUSIONS: Community mobilization of teams to trace TB patients that missed a clinic appointment or treatment dose may be an effective strategy to mitigate default rates and improve treatment outcomes. Additional information is necessary to identify best practices and elucidate discrepancies across provinces; these findings will help guide the NTP in optimizing the adoption of tracing activities for TB control. |
format | Online Article Text |
id | pubmed-3490985 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-34909852012-11-07 Impact of community tracer teams on treatment outcomes among tuberculosis patients in South Africa Bronner, Liza E Podewils, Laura J Peters, Annatjie Somnath, Pushpakanthi Nshuti, Lorna van der Walt, Martie Mametja, Lerole David BMC Public Health Research Article BACKGROUND: Tuberculosis (TB) indicators in South Africa currently remain well below global targets. In 2008, the National Tuberculosis Program (NTP) implemented a community mobilization program in all nine provinces to trace TB patients that had missed a treatment or clinic visit. Implementation sites were selected by TB program managers and teams liaised with health facilities to identify patients for tracing activities. The objective of this analysis was to assess the impact of the TB Tracer Project on treatment outcomes among TB patients. METHODS: The study population included all smear positive TB patients registered in the Electronic TB Registry from Quarter 1 2007-Quarter 1 2009 in South Africa. Subdistricts were used as the unit of analysis, with each designated as either tracer (standard TB program plus tracer project) or non-tracer (standard TB program only). Mixed linear regression models were utilized to calculate the percent quarterly change in treatment outcomes and to compare changes in treatment outcomes from Quarter 1 2007 to Quarter 1 2009 between tracer and non-tracer subdistricts. RESULTS: For all provinces combined, the percent quarterly change decreased significantly for default treatment outcomes among tracer subdistricts (−0.031%; p < 0.001) and increased significantly for successful treatment outcomes among tracer subdistricts (0.003%; p = 0.03). A significant decrease in the proportion of patient default was observed for all provinces combined over the time period comparing tracer and non-tracer subdistricts (p = 0.02). Examination in stratified models revealed the results were not consistent across all provinces; significant differences were observed between tracer and non-tracer subdistricts over time in five of nine provinces for treatment default. CONCLUSIONS: Community mobilization of teams to trace TB patients that missed a clinic appointment or treatment dose may be an effective strategy to mitigate default rates and improve treatment outcomes. Additional information is necessary to identify best practices and elucidate discrepancies across provinces; these findings will help guide the NTP in optimizing the adoption of tracing activities for TB control. BioMed Central 2012-08-07 /pmc/articles/PMC3490985/ /pubmed/22871071 http://dx.doi.org/10.1186/1471-2458-12-621 Text en Copyright ©2012 Bronner 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 Bronner, Liza E Podewils, Laura J Peters, Annatjie Somnath, Pushpakanthi Nshuti, Lorna van der Walt, Martie Mametja, Lerole David Impact of community tracer teams on treatment outcomes among tuberculosis patients in South Africa |
title | Impact of community tracer teams on treatment outcomes among tuberculosis patients in South Africa |
title_full | Impact of community tracer teams on treatment outcomes among tuberculosis patients in South Africa |
title_fullStr | Impact of community tracer teams on treatment outcomes among tuberculosis patients in South Africa |
title_full_unstemmed | Impact of community tracer teams on treatment outcomes among tuberculosis patients in South Africa |
title_short | Impact of community tracer teams on treatment outcomes among tuberculosis patients in South Africa |
title_sort | impact of community tracer teams on treatment outcomes among tuberculosis patients in south africa |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3490985/ https://www.ncbi.nlm.nih.gov/pubmed/22871071 http://dx.doi.org/10.1186/1471-2458-12-621 |
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