Electronic Clinical Decision Support System for allergic rhinitis management: MASK e-CDSS

Anne-Lise Courbis, Ruth Brigid Murray, Sylvie Arnavielhe, Davide Caimmi, Anna Bedbrook, Michiel Van Eerd, Govert De Vries, Gerard Dray, Ioana Agache, Mario Morais-Almeida, Claus Bachert, Karl Christian Bergmann, Sinthia Bosnic-Anticevich, Jan Brozek, Caterina Bucca, Paulo Camargos, Giorgio Walter Canonica, Warner Carr, Thomas Casale, Joao A. FonsecaTari Haahtela, Omer Kalayci, Ludger Klimek, Piotr Kuna, Violeta Kvedariene, Desiree Larenas Linnemann, Phil Lieberman, Joaquim Mullol, Robyn Ohehir, Nikolaos Papadopoulos, David Price, Dermot Ryan, Boleslaw Samolinski, F. Estelle Simons, Peter Tomazic, Massimo Triggiani, Arunas Valiulis, Erkka Valovirta, Martin Wagenmann, Magnus Wickman, Arzu Yorgancioglu, Jean Bousquet

Research output: Contribution to journalArticle

22 Citations (Scopus)

Abstract

Background
Allergic rhinitis (AR ) management has changed in recent years following the switch from the concept of disease severity to the concept of disease control, publication of the AR clinical decision support system (CDSS ) and development of mobile health (m‐health) tools for patients (eg Allergy Diary ). The Allergy Diary Companion app for healthcare providers is currently being developed and will be launched in 2018. It incorporates the AR CDSS to provide evidence‐based treatment recommendations, linking all key stakeholders in AR management.

Objective
To produce an electronic version of the AR CDSS (e‐CDSS ) for incorporation into the Allergy Diary Companion, to describe the app interfaces used to collect information necessary to inform the e‐CDSS and to summarize some key features of the Allergy Diary Companion .

Methods
The steps involved in producing the e‐CDSS and incorporating it into the Allergy Diary Companion were (a) generation of treatment management scenarios; (b) expert consensus on treatment recommendations; (c) generation of electronic decisional algorithms to describe all AR CDSS scenarios; (d) digitization of these algorithms to form the e‐CDSS ; and (e) embedding the e‐CDSS into the app to permit easy user e‐CDSS interfacing.

Results
Key experts in the AR field agreed on the AR CDSS approach to AR management and on specific treatment recommendations provided by Allergy Diary Companion . Based on this consensus, decision processes were developed and programmed into the Allergy Diary Companion using Titanium Appcelerator (JavaScript) for IOS tablets. To our knowledge, this is the first time the development of any m‐health tool has been described in this transparent and detailed way, providing confidence, not only in the app, but also in the provided management recommendations.

Conclusion
The Allergy Diary Companion for providers provides guideline and expert‐endorsed AR management recommendations. [MASK paper No 32].
Original languageEnglish
Pages (from-to)1640-1653
Number of pages14
JournalClinical & experimental allergy
Volume48
Issue number12
Early online date20 Aug 2018
DOIs
Publication statusPublished - Dec 2018

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    Courbis, A-L., Murray, R. B., Arnavielhe, S., Caimmi, D., Bedbrook, A., Van Eerd, M., De Vries, G., Dray, G., Agache, I., Morais-Almeida, M., Bachert, C., Bergmann, K. C., Bosnic-Anticevich, S., Brozek, J., Bucca, C., Camargos, P., Canonica, G. W., Carr, W., Casale, T., ... Bousquet, J. (2018). Electronic Clinical Decision Support System for allergic rhinitis management: MASK e-CDSS. Clinical & experimental allergy, 48(12), 1640-1653. https://doi.org/10.1111/cea.13230