1. Improved allergen immunotherapy prescription for seasonal allergic rhinitis: an innovative algorithm
- Author
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Paolo Maria Matricardi, Valeria Villella, Marco Di Fraia, Sveva Castelli, Mariaelisabetta Conte, Danilo Villalta, Alessandro Travaglini, Maria Antonia Brighetti, Paola Martelli, Stephanie Dramburg, Stefania Arasi, Salvatore Tripodi, Serena Perna, Ifigenia Sfika, and Pier Luigi Verardo
- Subjects
Anamnesis ,Allergen immunotherapy ,business.industry ,Combined use ,Clinical performance ,Medicine ,Usability ,In patient ,Medical prescription ,business ,Clinical decision support system ,Algorithm - Abstract
Background: Allergen immunotherapy(AIT) is the only disease-modifying treatment with long-term effects in patients with seasonal allergic rhinoconjunctivitis(SAR). Its efficacy depends on the precise identification of the pollen triggering symptoms. However, a diagnostic approach based on retrospective clinical history and sensitization to extracts often does not lead to unequivocal results. Objectives: To assess the usability and impact of a recently established algorithm for a potential clinical decision support system (@IT.2020-DSS) for pollen allergy and its diagnostic steps (including anamnesis, SPT, component resolved diagnosis, CRD, and real-time digital symptom recording, eDiary) on doctor’s AIT prescription decisions. Methods: After a concise educational training on the @IT.2020-DSS algorithm, 46 doctors (18allergy specialists, AS, and 28general practitioners, GP) expressed their hypothetical AIT prescription for 10 clinical index cases. Decisions were recorded repeatedly based on different steps of the support algorithm. The usability and perceived impact of the algorithm on individual clinical performance were evaluated. Results: The combined use of CRD and an eDiary increased the hypothetical AIT prescriptions, both among AS and GP (p
- Published
- 2020