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Improving TB case notification and treatment coverage through data use

BACKGROUND: This was a study on national TB data. OBJECTIVE: To assess improvement in TB case notification and treatment coverage through improved data use for action in Nigeria DESIGN: We analysed pre- and post-intervention secondary TB programme data comprising data on increased supervisory visits...

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Autores principales: Chijioke-Akaniro, O. O., Ubochioma, E., Omoniyi, A., Fashade, O., Olarewaju, O., Asuke, S., Aniwada, E. C., Uwaezuoke, A. N., Sseskitooleko, J., Workneh, N., Masini, E., Morris, B., Lawanson, A., Anyaike, C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: International Union Against Tuberculosis and Lung Disease 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9484588/
https://www.ncbi.nlm.nih.gov/pubmed/36160725
http://dx.doi.org/10.5588/pha.22.0001
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author Chijioke-Akaniro, O. O.
Ubochioma, E.
Omoniyi, A.
Fashade, O.
Olarewaju, O.
Asuke, S.
Aniwada, E. C.
Uwaezuoke, A. N.
Sseskitooleko, J.
Workneh, N.
Masini, E.
Morris, B.
Lawanson, A.
Anyaike, C.
author_facet Chijioke-Akaniro, O. O.
Ubochioma, E.
Omoniyi, A.
Fashade, O.
Olarewaju, O.
Asuke, S.
Aniwada, E. C.
Uwaezuoke, A. N.
Sseskitooleko, J.
Workneh, N.
Masini, E.
Morris, B.
Lawanson, A.
Anyaike, C.
author_sort Chijioke-Akaniro, O. O.
collection PubMed
description BACKGROUND: This was a study on national TB data. OBJECTIVE: To assess improvement in TB case notification and treatment coverage through improved data use for action in Nigeria DESIGN: We analysed pre- and post-intervention secondary TB programme data comprising data on increased supervisory visits, incentives for health workers, DOTS expansion, outreaches and geo-code monitoring. Trend analysis was performed using Cochran-Armitage χ(2) test for linear trends. RESULTS: Case-finding increased from 104,904 cases in 2017 to 138,591 in 2020. There was an increase of 2.0% from 2017 to 2018, 13.0% in 2018 to 2019 and 15.0% in 2019 to 2020 (P < 0.001). Facility DOTS coverage increased from 7,389 facilities in 2017 to 17,699 in 2020. There was an increase of 30.0% in 2018, 31.0% in 2019 and 40.0% in 2020 (P < 0.001). The number of reporting facilities increased from 5,854 in 2017 to 12,775 in 2020. Compared with 2017, there were an increase of 20.0% in 2018, 38.0% in 2019 and 32.0% in 2020 (P < 0.001). Treatment coverage rate increased from 24% in 2018 to 27% in 2019 and 30% in 2020. CONCLUSION: TB service expansion, improved monitoring and the use of data for decision making are key in increasing TB treatment coverage.
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spelling pubmed-94845882022-09-24 Improving TB case notification and treatment coverage through data use Chijioke-Akaniro, O. O. Ubochioma, E. Omoniyi, A. Fashade, O. Olarewaju, O. Asuke, S. Aniwada, E. C. Uwaezuoke, A. N. Sseskitooleko, J. Workneh, N. Masini, E. Morris, B. Lawanson, A. Anyaike, C. Public Health Action Original Articles BACKGROUND: This was a study on national TB data. OBJECTIVE: To assess improvement in TB case notification and treatment coverage through improved data use for action in Nigeria DESIGN: We analysed pre- and post-intervention secondary TB programme data comprising data on increased supervisory visits, incentives for health workers, DOTS expansion, outreaches and geo-code monitoring. Trend analysis was performed using Cochran-Armitage χ(2) test for linear trends. RESULTS: Case-finding increased from 104,904 cases in 2017 to 138,591 in 2020. There was an increase of 2.0% from 2017 to 2018, 13.0% in 2018 to 2019 and 15.0% in 2019 to 2020 (P < 0.001). Facility DOTS coverage increased from 7,389 facilities in 2017 to 17,699 in 2020. There was an increase of 30.0% in 2018, 31.0% in 2019 and 40.0% in 2020 (P < 0.001). The number of reporting facilities increased from 5,854 in 2017 to 12,775 in 2020. Compared with 2017, there were an increase of 20.0% in 2018, 38.0% in 2019 and 32.0% in 2020 (P < 0.001). Treatment coverage rate increased from 24% in 2018 to 27% in 2019 and 30% in 2020. CONCLUSION: TB service expansion, improved monitoring and the use of data for decision making are key in increasing TB treatment coverage. International Union Against Tuberculosis and Lung Disease 2022-09-21 2022-09-21 /pmc/articles/PMC9484588/ /pubmed/36160725 http://dx.doi.org/10.5588/pha.22.0001 Text en https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution Licence CC-BY 4.0 (https://creativecommons.org/licenses/by/4.0/) published by The Union (www.theunion.org (http://www.theunion.org) ).
spellingShingle Original Articles
Chijioke-Akaniro, O. O.
Ubochioma, E.
Omoniyi, A.
Fashade, O.
Olarewaju, O.
Asuke, S.
Aniwada, E. C.
Uwaezuoke, A. N.
Sseskitooleko, J.
Workneh, N.
Masini, E.
Morris, B.
Lawanson, A.
Anyaike, C.
Improving TB case notification and treatment coverage through data use
title Improving TB case notification and treatment coverage through data use
title_full Improving TB case notification and treatment coverage through data use
title_fullStr Improving TB case notification and treatment coverage through data use
title_full_unstemmed Improving TB case notification and treatment coverage through data use
title_short Improving TB case notification and treatment coverage through data use
title_sort improving tb case notification and treatment coverage through data use
topic Original Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9484588/
https://www.ncbi.nlm.nih.gov/pubmed/36160725
http://dx.doi.org/10.5588/pha.22.0001
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