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

Author:

Ortiz de Frutos Francisco J.1,Giménez‐Arnau Ana M.2ORCID,Puig Lluís3ORCID,Silvestre Juan F.4,Serra Esther3,Salgado‐Boquete Laura5,García‐Patos Vicente6,Estebaranz Jose L. L.7,Notario Jaime89,Martin‐Santiago Ana10,Pontevia Gabriel M.11,Martín Víctor12,Guinea Guillermo12,Terradas Pau12,Daudén Esteban13ORCID

Affiliation:

1. Hospital Universitario 12 de Octubre Universidad Complutense Madrid Spain

2. Department of Dermatology, Hospital del Mar‐IMIM Universitat Pompeu Fabra Barcelona Spain

3. Servicio de Dermatología, IIB SANT PAU Hospital de la Santa Creu i Sant Pau Barcelona Spain

4. Hospital General Universitario Dr Balmis Alicante Spain

5. Complejo Hospitalario Universitario de Pontevedra Pontevedra Spain

6. Hospital Universitari Vall d'Hebron Barcelona Spain

7. Hospital Universitario Fundación Alcorcón Madrid Spain

8. Hospital de Bellvitge Barcelona Spain

9. Hospitalet de Llobregat Barcelona Spain

10. Hospital Universitari Son Espases Palma de Mallorca Spain

11. IOMED Medical Solutions Barcelona Spain

12. Novartis Farmacéutica S.A Barcelona Spain

13. Department of Dermatology, Hospital Universitario de la Princesa Instituto de Investigación Sanitaria (IIS‐HP) Madrid Spain

Abstract

AbstractBackgroundAccurately 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.ObjectivesThe 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.MethodsThis 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.ResultsTo 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.ConclusionsResults 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.

Funder

Novartis Farmacéutica

Publisher

Wiley

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