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Geographic analysis of latent tuberculosis screening: A health system approach

BACKGROUND: Novel approaches are required to better focus latent tuberculosis infection (LTBI) efforts in low-prevalence regions. Geographic information systems, used within large health systems, may provide one such approach. METHODS: A retrospective, cross-sectional design was used to integrate US...

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Autores principales: Bonnewell, John P., Farrow, Laura, Dicks, Kristen V., Cox, Gary M., Stout, Jason E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7652260/
https://www.ncbi.nlm.nih.gov/pubmed/33166372
http://dx.doi.org/10.1371/journal.pone.0242055
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author Bonnewell, John P.
Farrow, Laura
Dicks, Kristen V.
Cox, Gary M.
Stout, Jason E.
author_facet Bonnewell, John P.
Farrow, Laura
Dicks, Kristen V.
Cox, Gary M.
Stout, Jason E.
author_sort Bonnewell, John P.
collection PubMed
description BACKGROUND: Novel approaches are required to better focus latent tuberculosis infection (LTBI) efforts in low-prevalence regions. Geographic information systems, used within large health systems, may provide one such approach. METHODS: A retrospective, cross-sectional design was used to integrate US Census and Duke Health System data between January 1, 2010 and October 31, 2017 and examine the relationships between LTBI screening and population tuberculosis risk (assessed using the surrogate measure of proportion of persons born in tuberculosis-endemic regions) by census tract. RESULTS: The median proportion of Duke patients screened per census tract was 0.01 (range 0–0.1, interquartile range 0.01–0.03). The proportion of Duke patients screened within a census tract significantly but weakly correlated with the population risk. Furthermore, patients residing in census tracts with higher population tuberculosis risk were more likely to be screened with TST than with an IGRA (p<0.001). CONCLUSION: The weak correlation between patient proportion screened for LTBI and our surrogate marker of population tuberculosis risk suggests that LTBI screening efforts should be better targeted. This type of geography-based analysis may serve as an easily obtainable benchmark for LTBI screening in health systems with low tuberculosis prevalence.
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spelling pubmed-76522602020-11-18 Geographic analysis of latent tuberculosis screening: A health system approach Bonnewell, John P. Farrow, Laura Dicks, Kristen V. Cox, Gary M. Stout, Jason E. PLoS One Research Article BACKGROUND: Novel approaches are required to better focus latent tuberculosis infection (LTBI) efforts in low-prevalence regions. Geographic information systems, used within large health systems, may provide one such approach. METHODS: A retrospective, cross-sectional design was used to integrate US Census and Duke Health System data between January 1, 2010 and October 31, 2017 and examine the relationships between LTBI screening and population tuberculosis risk (assessed using the surrogate measure of proportion of persons born in tuberculosis-endemic regions) by census tract. RESULTS: The median proportion of Duke patients screened per census tract was 0.01 (range 0–0.1, interquartile range 0.01–0.03). The proportion of Duke patients screened within a census tract significantly but weakly correlated with the population risk. Furthermore, patients residing in census tracts with higher population tuberculosis risk were more likely to be screened with TST than with an IGRA (p<0.001). CONCLUSION: The weak correlation between patient proportion screened for LTBI and our surrogate marker of population tuberculosis risk suggests that LTBI screening efforts should be better targeted. This type of geography-based analysis may serve as an easily obtainable benchmark for LTBI screening in health systems with low tuberculosis prevalence. Public Library of Science 2020-11-09 /pmc/articles/PMC7652260/ /pubmed/33166372 http://dx.doi.org/10.1371/journal.pone.0242055 Text en © 2020 Bonnewell et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Bonnewell, John P.
Farrow, Laura
Dicks, Kristen V.
Cox, Gary M.
Stout, Jason E.
Geographic analysis of latent tuberculosis screening: A health system approach
title Geographic analysis of latent tuberculosis screening: A health system approach
title_full Geographic analysis of latent tuberculosis screening: A health system approach
title_fullStr Geographic analysis of latent tuberculosis screening: A health system approach
title_full_unstemmed Geographic analysis of latent tuberculosis screening: A health system approach
title_short Geographic analysis of latent tuberculosis screening: A health system approach
title_sort geographic analysis of latent tuberculosis screening: a health system approach
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7652260/
https://www.ncbi.nlm.nih.gov/pubmed/33166372
http://dx.doi.org/10.1371/journal.pone.0242055
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