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Mobile health is the "medical and public health practice supported by mobile devices, such as mobile phones, patient monitoring devices, personal digital assistants, and other wireless devices." For example, mobile apps (such as MASK‐Air, Allergy.Monitor, Pollen, and others) have proven useful in the management of patients with allergic rhinitis. These apps can be used in the context of broader clinical decision support systems (CDSS) for enhancing allergy‐related decisions and actions with pertinent, organized clinical knowledge and patient information to improve allergy care. A CDSS targeted to control rhinitis with drugs and other interventions guiding the patient in his/her self‐ and doctor‐driven management is currently being produced and investigated by the MACVIA network. Another one, called @IT‐2020, is targeted to support etiologic diagnostics and allergen immunotherapy (AIT) prescriptions for patients with seasonal allergic rhinitis. Intensive investigation is necessary to better define the advantages and limitations of mobile‐health technology in allergology and establish guidelines for their proper use in daily practice in the context of a rapidly evolving European regulatory environment. [ABSTRACT FROM AUTHOR]

Background: Allergen immunotherapy (AIT) is the only disease‐modifying treatment in patients with seasonal allergic rhinoconjunctivitis (SAR). Its efficacy depends on the precise identification of the triggering allergen. However, diagnostics based on retrospective clinical history and sensitization to whole extracts (SWE) often leads to equivocal results. Objectives: To assess the usability and impact of a recently established algorithm for a clinical decision support system (@IT2020‐CDSS) for SAR and its diagnostic steps [anamnesis, SWE (skin prick test or serum IgE), component resolved diagnosis, CRD, and real‐time digital symptom recording, eDiary] on doctor's AIT prescription decisions. Methods: After educational training on the @IT2020‐CDSS algorithm, 46 doctors (18 allergy specialists, AS, and 28 general practitioners, GP) expressed their hypothetical AIT prescription for 10 clinical index cases. Decisions were recorded repeatedly based on different steps of the algorithm. The usability and perceived impact of the algorithm were evaluated. Results: The combined use of CRD and an eDiary increased the hypothetical AIT prescriptions, both among AS and GP (p <.01). AIT prescription for pollen and Alternaria allergy based on anamnesis and SWE was heterogeneous but converged towards a consensus by integrating CRD and eDiary information. Doctors considered the algorithm useful and recognized its potential in enhancing traditional diagnostics. Conclusions and clinical implications: The implementation of CRD and eDiary in the @IT2020‐CDSS algorithm improved consensus on AIT prescription for SAR among AS and GP. The potential usefulness of a CDSS for aetiological diagnosis of SAR and AIT prescription in real‐world clinical practice deserves further investigation. [ABSTRACT FROM AUTHOR]