Usefulness, acceptation and feasibility of electronic medical history tool in reflux disease.

Artificial Future Gastroesophageal Head neck Intelligence Laryngology Laryngopharyngeal Medical history Otolaryngology Reflux

Journal

European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery
ISSN: 1434-4726
Titre abrégé: Eur Arch Otorhinolaryngol
Pays: Germany
ID NLM: 9002937

Informations de publication

Date de publication:
Jan 2023
Historique:
received: 09 02 2022
accepted: 19 06 2022
pubmed: 29 6 2022
medline: 7 1 2023
entrez: 28 6 2022
Statut: ppublish

Résumé

To investigate usefulness, feasibility, and patient satisfaction of an electronic pre-consultation medical history tool (EPMH) in laryngopharyngeal reflux (LPR) work-up. Seventy-five patients with LPR were invited to complete electronic medical history assessment prior to laryngology consultation. EPMH collected the following parameters: demographic and epidemiological data, medication, medical and surgical histories, diet habits, stress and symptom findings. Stress and symptoms were assessed with perceived stress scale and reflux symptom score. Duration of consultation, acceptance, and satisfaction of patients (feasibility, usefulness, effectiveness, understanding of questions) were evaluated through a 9-item patient-reported outcome questionnaire. Seventy patients completed the evaluation (93% participation rate). The mean age of cohort was 51.2 ± 15.6 years old. There were 35 females and 35 males. Patients who refused to participate (N = 5) were > 65 years old. The consultation duration was significantly lower in patients who used the EPMH (11.3 ± 2.7 min) compared with a control group (18.1 ± 5.1 min; p = 0.001). Ninety percent of patients were satisfied about EPMH easiness and usefulness, while 97.1% thought that EPMH may improve the disease management. Patients would recommend similar approach for otolaryngological or other specialty consultations in 98.6% and 92.8% of cases, respectively. The use of EPMH is associated with adequate usefulness, feasibility, and satisfaction outcomes in patients with LPR. This software is a preliminary step in the development of an AI-based diagnostic decision support tool to help laryngologists in their daily practice. Future randomized controlled studies are needed to investigate the gain of similar approaches on the traditional consultation format.

Identifiants

pubmed: 35763082
doi: 10.1007/s00405-022-07520-6
pii: 10.1007/s00405-022-07520-6
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

259-267

Informations de copyright

© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

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Auteurs

Jerome R Lechien (JR)

Department of Otolaryngology, Elsan Hospital, Paris, France. Jerome.Lechien@umons.ac.be.
Department of Otolaryngology-Head and Neck Surgery, Foch Hospital, School of Medicine, University Paris Saclay, Worth street, 40, 92150, Paris, Suresnes, France. Jerome.Lechien@umons.ac.be.
Department of Otolaryngology-Head and Neck Surgery, CHU Saint-Pierre, Brussels, Belgium. Jerome.Lechien@umons.ac.be.
Department of Human Anatomy and Experimental Oncology, Faculty of Medicine, UMONS Research Institute for Health Sciences and Technology, University of Mons (UMons), Mons, Belgium. Jerome.Lechien@umons.ac.be.

Anaïs Rameau (A)

Department of Otolaryngology-Head and Neck Surgery, Sean Parker Institute for the Voice, Weill Cornell Medicine, New York, NY, USA.

Lisa G De Marrez (LG)

Department of Otolaryngology-Head and Neck Surgery, Foch Hospital, School of Medicine, University Paris Saclay, Worth street, 40, 92150, Paris, Suresnes, France.

Gautier Le Bosse (G)

Department of Otolaryngology-Head and Neck Surgery, Foch Hospital, School of Medicine, University Paris Saclay, Worth street, 40, 92150, Paris, Suresnes, France.
Department of Artificial Intelligence Applied to Medical Structure, Special School of Mechanic and Electricity (ESME) Sudria, Paris, France.

Karina Negro (K)

Department of Otolaryngology-Head and Neck Surgery, Foch Hospital, School of Medicine, University Paris Saclay, Worth street, 40, 92150, Paris, Suresnes, France.
Department of Artificial Intelligence Applied to Medical Structure, Special School of Mechanic and Electricity (ESME) Sudria, Paris, France.

Andra Sebestyen (A)

Department of Otolaryngology-Head and Neck Surgery, Foch Hospital, School of Medicine, University Paris Saclay, Worth street, 40, 92150, Paris, Suresnes, France.

Robin Baudouin (R)

Department of Otolaryngology-Head and Neck Surgery, Foch Hospital, School of Medicine, University Paris Saclay, Worth street, 40, 92150, Paris, Suresnes, France.

Sven Saussez (S)

Department of Otolaryngology-Head and Neck Surgery, CHU Saint-Pierre, Brussels, Belgium.
Department of Human Anatomy and Experimental Oncology, Faculty of Medicine, UMONS Research Institute for Health Sciences and Technology, University of Mons (UMons), Mons, Belgium.

Stéphane Hans (S)

Department of Otolaryngology-Head and Neck Surgery, Foch Hospital, School of Medicine, University Paris Saclay, Worth street, 40, 92150, Paris, Suresnes, France.

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