@IT2020: an innovative algorithm for allergen immunotherapy prescription in seasonal allergic rhinitis

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.