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Adaptation and performance of a mobile application for early detection of cutaneous leishmaniasis
BACKGROUND: Detection and management of neglected tropical diseases such as cutaneous leishmaniasis present unmet challenges stemming from their prevalence in remote, rural, resource constrained areas having limited access to health services. These challenges are frequently compounded by armed confl...
Autores principales: | , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7904137/ https://www.ncbi.nlm.nih.gov/pubmed/33571192 http://dx.doi.org/10.1371/journal.pntd.0008989 |
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author | Rubiano, Luisa Alexander, Neal D. E. Castillo, Ruth Mabel Martínez, Álvaro José García Luna, Jonny Alejandro Arango, Juan David Vargas, Leonardo Madriñán, Patricia Hurtado, Lina-Rocío Orobio, Yenifer Rojas, Carlos A. del Corral, Helena Navarro, Andrés Gore Saravia, Nancy Aronoff-Spencer, Eliah |
author_facet | Rubiano, Luisa Alexander, Neal D. E. Castillo, Ruth Mabel Martínez, Álvaro José García Luna, Jonny Alejandro Arango, Juan David Vargas, Leonardo Madriñán, Patricia Hurtado, Lina-Rocío Orobio, Yenifer Rojas, Carlos A. del Corral, Helena Navarro, Andrés Gore Saravia, Nancy Aronoff-Spencer, Eliah |
author_sort | Rubiano, Luisa |
collection | PubMed |
description | BACKGROUND: Detection and management of neglected tropical diseases such as cutaneous leishmaniasis present unmet challenges stemming from their prevalence in remote, rural, resource constrained areas having limited access to health services. These challenges are frequently compounded by armed conflict or illicit extractive industries. The use of mobile health technologies has shown promise in such settings, yet data on outcomes in the field remain scarce. METHODS: We adapted a validated prediction rule for the presumptive diagnosis of CL to create a mobile application for use by community health volunteers. We used human-centered design practices and agile development for app iteration. We tested the application in three rural areas where cutaneous leishmaniasis is endemic and an urban setting where patients seek medical attention in the municipality of Tumaco, Colombia. The application was assessed for usability, sensitivity and inter-rater reliability (kappa) when used by community health volunteers (CHV), health workers and a general practitioner, study physician. RESULTS: The application was readily used and understood. Among 122 screened cases with cutaneous ulcers, sensitivity to detect parasitologically proven CL was >95%. The proportion of participants with parasitologically confirmed CL was high (88%), precluding evaluation of specificity, and driving a high level of crude agreement between the app and parasitological diagnosis. The chance-adjusted agreement (kappa) varied across the components of the risk score. Time to diagnosis was reduced significantly, from 8 to 4 weeks on average when CHV conducted active case detection using the application, compared to passive case detection by health facility-based personnel. CONCLUSIONS: Translating a validated prediction rule to a mHealth technology has shown the potential to improve the capacity of community health workers and healthcare personnel to provide opportune care, and access to health services for underserved populations. These findings support the use of mHealth tools for NTD research and healthcare. |
format | Online Article Text |
id | pubmed-7904137 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-79041372021-03-02 Adaptation and performance of a mobile application for early detection of cutaneous leishmaniasis Rubiano, Luisa Alexander, Neal D. E. Castillo, Ruth Mabel Martínez, Álvaro José García Luna, Jonny Alejandro Arango, Juan David Vargas, Leonardo Madriñán, Patricia Hurtado, Lina-Rocío Orobio, Yenifer Rojas, Carlos A. del Corral, Helena Navarro, Andrés Gore Saravia, Nancy Aronoff-Spencer, Eliah PLoS Negl Trop Dis Research Article BACKGROUND: Detection and management of neglected tropical diseases such as cutaneous leishmaniasis present unmet challenges stemming from their prevalence in remote, rural, resource constrained areas having limited access to health services. These challenges are frequently compounded by armed conflict or illicit extractive industries. The use of mobile health technologies has shown promise in such settings, yet data on outcomes in the field remain scarce. METHODS: We adapted a validated prediction rule for the presumptive diagnosis of CL to create a mobile application for use by community health volunteers. We used human-centered design practices and agile development for app iteration. We tested the application in three rural areas where cutaneous leishmaniasis is endemic and an urban setting where patients seek medical attention in the municipality of Tumaco, Colombia. The application was assessed for usability, sensitivity and inter-rater reliability (kappa) when used by community health volunteers (CHV), health workers and a general practitioner, study physician. RESULTS: The application was readily used and understood. Among 122 screened cases with cutaneous ulcers, sensitivity to detect parasitologically proven CL was >95%. The proportion of participants with parasitologically confirmed CL was high (88%), precluding evaluation of specificity, and driving a high level of crude agreement between the app and parasitological diagnosis. The chance-adjusted agreement (kappa) varied across the components of the risk score. Time to diagnosis was reduced significantly, from 8 to 4 weeks on average when CHV conducted active case detection using the application, compared to passive case detection by health facility-based personnel. CONCLUSIONS: Translating a validated prediction rule to a mHealth technology has shown the potential to improve the capacity of community health workers and healthcare personnel to provide opportune care, and access to health services for underserved populations. These findings support the use of mHealth tools for NTD research and healthcare. Public Library of Science 2021-02-11 /pmc/articles/PMC7904137/ /pubmed/33571192 http://dx.doi.org/10.1371/journal.pntd.0008989 Text en © 2021 Rubiano 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 Rubiano, Luisa Alexander, Neal D. E. Castillo, Ruth Mabel Martínez, Álvaro José García Luna, Jonny Alejandro Arango, Juan David Vargas, Leonardo Madriñán, Patricia Hurtado, Lina-Rocío Orobio, Yenifer Rojas, Carlos A. del Corral, Helena Navarro, Andrés Gore Saravia, Nancy Aronoff-Spencer, Eliah Adaptation and performance of a mobile application for early detection of cutaneous leishmaniasis |
title | Adaptation and performance of a mobile application for early detection of cutaneous leishmaniasis |
title_full | Adaptation and performance of a mobile application for early detection of cutaneous leishmaniasis |
title_fullStr | Adaptation and performance of a mobile application for early detection of cutaneous leishmaniasis |
title_full_unstemmed | Adaptation and performance of a mobile application for early detection of cutaneous leishmaniasis |
title_short | Adaptation and performance of a mobile application for early detection of cutaneous leishmaniasis |
title_sort | adaptation and performance of a mobile application for early detection of cutaneous leishmaniasis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7904137/ https://www.ncbi.nlm.nih.gov/pubmed/33571192 http://dx.doi.org/10.1371/journal.pntd.0008989 |
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