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An artificial intelligence based app for skin cancer detection evaluated in a population based setting

Artificial intelligence (AI) based algorithms for classification of suspicious skin lesions have been implemented in mobile phone apps (mHealth), but their effect on healthcare systems is undocumented. In 2019, a large Dutch health insurance company offered 2.2 million adults free access to an mHeal...

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Autores principales: Smak Gregoor, Anna M., Sangers, Tobias E., Bakker, Lytske J., Hollestein, Loes, Uyl – de Groot, Carin A., Nijsten, Tamar, Wakkee, Marlies
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10199884/
https://www.ncbi.nlm.nih.gov/pubmed/37210466
http://dx.doi.org/10.1038/s41746-023-00831-w
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author Smak Gregoor, Anna M.
Sangers, Tobias E.
Bakker, Lytske J.
Hollestein, Loes
Uyl – de Groot, Carin A.
Nijsten, Tamar
Wakkee, Marlies
author_facet Smak Gregoor, Anna M.
Sangers, Tobias E.
Bakker, Lytske J.
Hollestein, Loes
Uyl – de Groot, Carin A.
Nijsten, Tamar
Wakkee, Marlies
author_sort Smak Gregoor, Anna M.
collection PubMed
description Artificial intelligence (AI) based algorithms for classification of suspicious skin lesions have been implemented in mobile phone apps (mHealth), but their effect on healthcare systems is undocumented. In 2019, a large Dutch health insurance company offered 2.2 million adults free access to an mHealth app for skin cancer detection. To study the impact on dermatological healthcare consumption, we conducted a retrospective population-based pragmatic study. We matched 18,960 mHealth-users who completed at least one successful assessment with the app to 56,880 controls who did not use the app and calculated odds ratios (OR) to compare dermatological claims between both groups in the first year after granting free access. A short-term cost-effectiveness analysis was performed to determine the cost per additional detected (pre)malignancy. Here we report that mHealth-users had more claims for (pre)malignant skin lesions than controls (6.0% vs 4.6%, OR 1.3 (95% CI 1.2–1.4)) and also a more than threefold higher risk of claims for benign skin tumors and nevi (5.9% vs 1.7%, OR 3.7 (95% CI 3.4–4.1)). The costs of detecting one additional (pre)malignant skin lesion with the app compared to the current standard of care were €2567. Based on these results, AI in mHealth appears to have a positive impact on detecting more cutaneous (pre)malignancies, but this should be balanced against the for now stronger increase in care consumption for benign skin tumors and nevi.
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spelling pubmed-101998842023-05-22 An artificial intelligence based app for skin cancer detection evaluated in a population based setting Smak Gregoor, Anna M. Sangers, Tobias E. Bakker, Lytske J. Hollestein, Loes Uyl – de Groot, Carin A. Nijsten, Tamar Wakkee, Marlies NPJ Digit Med Article Artificial intelligence (AI) based algorithms for classification of suspicious skin lesions have been implemented in mobile phone apps (mHealth), but their effect on healthcare systems is undocumented. In 2019, a large Dutch health insurance company offered 2.2 million adults free access to an mHealth app for skin cancer detection. To study the impact on dermatological healthcare consumption, we conducted a retrospective population-based pragmatic study. We matched 18,960 mHealth-users who completed at least one successful assessment with the app to 56,880 controls who did not use the app and calculated odds ratios (OR) to compare dermatological claims between both groups in the first year after granting free access. A short-term cost-effectiveness analysis was performed to determine the cost per additional detected (pre)malignancy. Here we report that mHealth-users had more claims for (pre)malignant skin lesions than controls (6.0% vs 4.6%, OR 1.3 (95% CI 1.2–1.4)) and also a more than threefold higher risk of claims for benign skin tumors and nevi (5.9% vs 1.7%, OR 3.7 (95% CI 3.4–4.1)). The costs of detecting one additional (pre)malignant skin lesion with the app compared to the current standard of care were €2567. Based on these results, AI in mHealth appears to have a positive impact on detecting more cutaneous (pre)malignancies, but this should be balanced against the for now stronger increase in care consumption for benign skin tumors and nevi. Nature Publishing Group UK 2023-05-20 /pmc/articles/PMC10199884/ /pubmed/37210466 http://dx.doi.org/10.1038/s41746-023-00831-w Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Smak Gregoor, Anna M.
Sangers, Tobias E.
Bakker, Lytske J.
Hollestein, Loes
Uyl – de Groot, Carin A.
Nijsten, Tamar
Wakkee, Marlies
An artificial intelligence based app for skin cancer detection evaluated in a population based setting
title An artificial intelligence based app for skin cancer detection evaluated in a population based setting
title_full An artificial intelligence based app for skin cancer detection evaluated in a population based setting
title_fullStr An artificial intelligence based app for skin cancer detection evaluated in a population based setting
title_full_unstemmed An artificial intelligence based app for skin cancer detection evaluated in a population based setting
title_short An artificial intelligence based app for skin cancer detection evaluated in a population based setting
title_sort artificial intelligence based app for skin cancer detection evaluated in a population based setting
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10199884/
https://www.ncbi.nlm.nih.gov/pubmed/37210466
http://dx.doi.org/10.1038/s41746-023-00831-w
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