Artificial intelligence-enabled penicillin allergy delabelling: an implementation study.
antibiotic
efficiency
intolerance
machine learning
outcomes
Journal
Internal medicine journal
ISSN: 1445-5994
Titre abrégé: Intern Med J
Pays: Australia
ID NLM: 101092952
Informations de publication
Date de publication:
Nov 2023
Nov 2023
Historique:
received:
02
06
2023
accepted:
18
09
2023
medline:
27
11
2023
pubmed:
24
11
2023
entrez:
24
11
2023
Statut:
ppublish
Résumé
Inaccurate penicillin allergy labels may be delabelled following evaluation. The intervention in this study was an email-based notification system regarding the appropriateness for penicillin allergy evaluation, with a view to delabelling, as identified by a deep learning artificial intelligence algorithm. Of the intervention group (n = 59), three (5.1%) individuals had their penicillin allergies delabelled, which was significantly more than the control group (0%, P = 0.002). Further research to optimise such approaches is required.
Substances chimiques
Anti-Bacterial Agents
0
Penicillins
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
2119-2122Subventions
Organisme : Central Adelaide Local Health Network Clinical Rapid Implementation Project Scheme Grant
ID : 17075
Informations de copyright
© 2023 Royal Australasian College of Physicians.
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