MACVIA clinical decision algorithm in adolescents and adults with allergic rhinitis

The selection of pharmacotherapy for patients with allergic rhinitis (AR) depends on several factors, including age, prominent symptoms, symptom severity, control of AR, patient preferences, and cost. Allergen exposure and the resulting symptoms vary, and treatment adjustment is required. Clinical d...

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Detalhes bibliográficos
Autores: Bousquet, Jean, MASK study group, Antó i Boqué, Josep Maria, Sunyer Deu, Jordi
Formato: artículo
Estado:Versión publicada
Fecha de publicación:2016
País:España
Recursos: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:10230/28356
Acesso em linha:http://hdl.handle.net/10230/28356
http://dx.doi.org/10.1016/j.jaci.2016.03.025
Access Level:acceso abierto
Palavra-chave:Allergic rhinitis
Conjuctivitis
Allergic Rhinitis and its Impact on Asthma
MACVIA-LR
Information and communication technology
Clinical decision support system
Descrição
Resumo:The selection of pharmacotherapy for patients with allergic rhinitis (AR) depends on several factors, including age, prominent symptoms, symptom severity, control of AR, patient preferences, and cost. Allergen exposure and the resulting symptoms vary, and treatment adjustment is required. Clinical decision support systems (CDSSs) might be beneficial for the assessment of disease control. CDSSs should be based on the best evidence and algorithms to aid patients and health care professionals to jointly determine treatment and its step-up or step-down strategy depending on AR control. Contre les MAladies Chroniques pour un VIeillissement Actif en Languedoc-Roussillon (MACVIA-LR [fighting chronic diseases for active and healthy ageing]), one of the reference sites of the European Innovation Partnership on Active and Healthy Ageing, has initiated an allergy sentinel network (the MACVIA-ARIA Sentinel Network). A CDSS is currently being developed to optimize AR control. An algorithm developed by consensus is presented in this article. This algorithm should be confirmed by appropriate trials.