The DERMACLEAR study: Verification results of a natural language processing system in dermatology

Background: Accurately determining the epidemiology of dermatological diseases such as hidradenitis suppurativa (HS), psoriasis (PsO), chronic urticaria (CU) and/or atopic dermatitis (AD) is challenging due to variations in prevalence and disease severity in the reported literature. Objectives: The...

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Autores: Ortiz de Frutos, Francisco Javier, Giménez Arnau, Ana M., Puig, Lluís, Silvestre, Juan Francisco, Serra, Esther, Salgado Boquete, Laura, García-Patos Briones, Vicente, Estebaranz, Jose L. L., Notario, Jaime, Martín Santiago, Ana, Pontevia, Gabriel M., Martín, Víctor, Guinea, Guillermo, Terradas, Pau, Daudén, Esteban
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2023
País:España
Institución:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositorio:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:2445/214819
Acceso en línea:https://hdl.handle.net/2445/214819
Access Level:acceso abierto
Palabra clave:Aprenentatge automàtic
Dermatologia
Machine learning
Dermatology
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spelling The DERMACLEAR study: Verification results of a natural language processing system in dermatologyOrtiz de Frutos, Francisco JavierGiménez Arnau, Ana M.Puig, LluísSilvestre, Juan FranciscoSerra, EstherSalgado Boquete, LauraGarcía-Patos Briones, VicenteEstebaranz, Jose L. L.Notario, JaimeMartín Santiago, AnaPontevia, Gabriel M.Martín, VíctorGuinea, GuillermoTerradas, PauDaudén, EstebanAprenentatge automàticDermatologiaMachine learningDermatologyBackground: Accurately determining the epidemiology of dermatological diseases such as hidradenitis suppurativa (HS), psoriasis (PsO), chronic urticaria (CU) and/or atopic dermatitis (AD) is challenging due to variations in prevalence and disease severity in the reported literature. Objectives: The DERMACLEAR study aims to use natural language processing (NLP) to assess the proportions of patients with HS, PsO, CU and/or AD, and obtain information on patient profiles, patient journeys, and disease and healthcare burden in Spain. Here, the study design and objectives of the DERMACLEAR study are described and the precision of the NLP system used is assessed. Methods: This study will retrospectively collect patient information from electronic health records (EHRs) at dermatology departments from seven tertiary hospitals in Spain. The NLP system was developed by IOMED Medical Solutions and was verified internally (IOMED scientific team) and externally (principal investigators of each hospital) to determine its precision in identifying patients with HS, PsO, CU and/or AD. Furthermore, internal verification was performed on other medical variables relevant to the study. Results: To date, the DERMACLEAR study has retrospectively collected data from 54,458 patients with HS, PsO, CU and/or AD (HS: 5045; PsO: 32,559; CU: 8397; AD: 12,492). The average precision of the NLP system to identify patients diagnosed with HS, PsO, CU, and/or AD across all hospitals exceeded 95% via external and internal verification. Conclusions: Results from the DERMACLEAR study will increase the real-world evidence of clinical practice, obtaining a large amount of information on patients with the studied diseases. The NLP system used is precise in identifying patients diagnosed with HS, PsO, CU and/or AD, and other medical variables from EHRs, highlighting that it is a valid system to use in the DERMACLEAR study.Wiley2024202420232024info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersion11 p.application/pdfhttps://hdl.handle.net/2445/214819Articles publicats en revistes (Institut d'lnvestigació Biomèdica de Bellvitge (IDIBELL))reponame:Recercat. Dipósit de la Recerca de Catalunyainstname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)InglésReproducció del document publicat a: https://doi.org/10.1002/jvc2.217JEADV Clinical Practice, 2023, vol. 2, num. 4, p. 775-785https://doi.org/10.1002/jvc2.217cc by (c) Ortiz de Frutos, Francisco J. et al., 2023http://creativecommons.org/licenses/by/3.0/es/info:eu-repo/semantics/openAccessoai:recercat.cat:2445/2148192026-05-29T05:05:01Z
dc.title.none.fl_str_mv The DERMACLEAR study: Verification results of a natural language processing system in dermatology
title The DERMACLEAR study: Verification results of a natural language processing system in dermatology
spellingShingle The DERMACLEAR study: Verification results of a natural language processing system in dermatology
Ortiz de Frutos, Francisco Javier
Aprenentatge automàtic
Dermatologia
Machine learning
Dermatology
title_short The DERMACLEAR study: Verification results of a natural language processing system in dermatology
title_full The DERMACLEAR study: Verification results of a natural language processing system in dermatology
title_fullStr The DERMACLEAR study: Verification results of a natural language processing system in dermatology
title_full_unstemmed The DERMACLEAR study: Verification results of a natural language processing system in dermatology
title_sort The DERMACLEAR study: Verification results of a natural language processing system in dermatology
dc.creator.none.fl_str_mv Ortiz de Frutos, Francisco Javier
Giménez Arnau, Ana M.
Puig, Lluís
Silvestre, Juan Francisco
Serra, Esther
Salgado Boquete, Laura
García-Patos Briones, Vicente
Estebaranz, Jose L. L.
Notario, Jaime
Martín Santiago, Ana
Pontevia, Gabriel M.
Martín, Víctor
Guinea, Guillermo
Terradas, Pau
Daudén, Esteban
author Ortiz de Frutos, Francisco Javier
author_facet Ortiz de Frutos, Francisco Javier
Giménez Arnau, Ana M.
Puig, Lluís
Silvestre, Juan Francisco
Serra, Esther
Salgado Boquete, Laura
García-Patos Briones, Vicente
Estebaranz, Jose L. L.
Notario, Jaime
Martín Santiago, Ana
Pontevia, Gabriel M.
Martín, Víctor
Guinea, Guillermo
Terradas, Pau
Daudén, Esteban
author_role author
author2 Giménez Arnau, Ana M.
Puig, Lluís
Silvestre, Juan Francisco
Serra, Esther
Salgado Boquete, Laura
García-Patos Briones, Vicente
Estebaranz, Jose L. L.
Notario, Jaime
Martín Santiago, Ana
Pontevia, Gabriel M.
Martín, Víctor
Guinea, Guillermo
Terradas, Pau
Daudén, Esteban
author2_role author
author
author
author
author
author
author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv Aprenentatge automàtic
Dermatologia
Machine learning
Dermatology
topic Aprenentatge automàtic
Dermatologia
Machine learning
Dermatology
description Background: Accurately determining the epidemiology of dermatological diseases such as hidradenitis suppurativa (HS), psoriasis (PsO), chronic urticaria (CU) and/or atopic dermatitis (AD) is challenging due to variations in prevalence and disease severity in the reported literature. Objectives: The DERMACLEAR study aims to use natural language processing (NLP) to assess the proportions of patients with HS, PsO, CU and/or AD, and obtain information on patient profiles, patient journeys, and disease and healthcare burden in Spain. Here, the study design and objectives of the DERMACLEAR study are described and the precision of the NLP system used is assessed. Methods: This study will retrospectively collect patient information from electronic health records (EHRs) at dermatology departments from seven tertiary hospitals in Spain. The NLP system was developed by IOMED Medical Solutions and was verified internally (IOMED scientific team) and externally (principal investigators of each hospital) to determine its precision in identifying patients with HS, PsO, CU and/or AD. Furthermore, internal verification was performed on other medical variables relevant to the study. Results: To date, the DERMACLEAR study has retrospectively collected data from 54,458 patients with HS, PsO, CU and/or AD (HS: 5045; PsO: 32,559; CU: 8397; AD: 12,492). The average precision of the NLP system to identify patients diagnosed with HS, PsO, CU, and/or AD across all hospitals exceeded 95% via external and internal verification. Conclusions: Results from the DERMACLEAR study will increase the real-world evidence of clinical practice, obtaining a large amount of information on patients with the studied diseases. The NLP system used is precise in identifying patients diagnosed with HS, PsO, CU and/or AD, and other medical variables from EHRs, highlighting that it is a valid system to use in the DERMACLEAR study.
publishDate 2023
dc.date.none.fl_str_mv 2023
2024
2024
2024
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/2445/214819
url https://hdl.handle.net/2445/214819
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Reproducció del document publicat a: https://doi.org/10.1002/jvc2.217
JEADV Clinical Practice, 2023, vol. 2, num. 4, p. 775-785
https://doi.org/10.1002/jvc2.217
dc.rights.none.fl_str_mv cc by (c) Ortiz de Frutos, Francisco J. et al., 2023
http://creativecommons.org/licenses/by/3.0/es/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv cc by (c) Ortiz de Frutos, Francisco J. et al., 2023
http://creativecommons.org/licenses/by/3.0/es/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 11 p.
application/pdf
dc.publisher.none.fl_str_mv Wiley
publisher.none.fl_str_mv Wiley
dc.source.none.fl_str_mv Articles publicats en revistes (Institut d'lnvestigació Biomèdica de Bellvitge (IDIBELL))
reponame:Recercat. Dipósit de la Recerca de Catalunya
instname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
instname_str Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
reponame_str Recercat. Dipósit de la Recerca de Catalunya
collection Recercat. Dipósit de la Recerca de Catalunya
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,812455

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