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Electronic Clinical Decision Support System for allergic rhinitis management: MASK e‐CDSS
Author(s) -
Courbis AnneLise,
Murray Ruth Brigid,
Arnavielhe Sylvie,
Caimmi Davide,
Bedbrook Anna,
Van Eerd Michiel,
De Vries Govert,
Dray Gerard,
Agache Ioana,
MoraisAlmeida Mario,
Bachert Claus,
Bergmann Karl Christian,
BosnicAnticevich Sinthia,
Brozek Jan,
Bucca Caterina,
Camargos Paulo,
Caica Giorgio Walter,
Carr Warner,
Casale Thomas,
Fonseca Joao A.,
Haahtela Tari,
Kalayci Omer,
Klimek Ludger,
Kuna Piotr,
Kvedariene Violeta,
Larenas Linnemann Desiree,
Lieberman Phil,
Mullol Joaquim,
Ohehir Robyn,
Papadopoulos Nikolaos,
Price David,
Ryan Dermot,
Samolinski Boleslaw,
Simons F. Estelle,
Tomazic Peter,
Triggiani Massimo,
Valiulis Arunas,
Valovirta Erkka,
Wagenmann Martin,
Wickman Magnus,
Yorgancioglu Arzu,
Bousquet Jean
Publication year - 2018
Publication title -
clinical and experimental allergy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.462
H-Index - 154
eISSN - 1365-2222
pISSN - 0954-7894
DOI - 10.1111/cea.13230
Subject(s) - clinical decision support system , computer science , medicine , mhealth , decision support system , artificial intelligence , nursing , psychological intervention
Summary 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].