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Review
. 2018 Oct 25:8:45.
doi: 10.1186/s13601-018-0227-6. eCollection 2018.

MASK 2017: ARIA digitally-enabled, integrated, person-centred care for rhinitis and asthma multimorbidity using real-world-evidence

J Bousquet  1   2   3 , S Arnavielhe  4 , A Bedbrook  1 , M Bewick  5 , D Laune  4 , E Mathieu-Dupas  4 , R Murray  6 , G L Onorato  1 , J L Pépin  7   8 , R Picard  9 , F Portejoie  1 , E Costa  10 , J Fonseca  11   12 , O Lourenço  13 , M Morais-Almeida  14 , A Todo-Bom  15 , A A Cruz  16   17 , J da Silva  18 , F S Serpa  19 , M Illario  20 , E Menditto  21 , L Cecchi  22 , R Monti  23 , L Napoli  24 , M T Ventura  25 , G De Feo  26 , D Larenas-Linnemann  27 , M Fuentes Perez  28 , Y R Huerta Villabolos  28 , D Rivero-Yeverino  29 , E Rodriguez-Zagal  30 , F Amat  31   32 , I Annesi-Maesano  33 , I Bosse  34 , P Demoly  35 , P Devillier  36 , J F Fontaine  37 , J Just  31   32 , T P Kuna  38 , B Samolinski  39 , A Valiulis  40   41 , R Emuzyte  42 , V Kvedariene  43 , D Ryan  44   45 , A Sheikh  46 , P Schmidt-Grendelmeier  47 , L Klimek  48   49 , O Pfaar  48   49 , K C Bergmann  50   51 , R Mösges  52   53 , T Zuberbier  50   51 , R E Roller-Wirnsberger  54 , P Tomazic  55 , W J Fokkens  56 , N H Chavannes  57 , S Reitsma  56 , J M Anto  58   59   60   61 , V Cardona  62 , T Dedeu  63   64 , J Mullol  65   66 , T Haahtela  67 , J Salimäki  68 , S Toppila-Salmi  67 , E Valovirta  69   70 , B Gemicioğlu  71 , A Yorgancioglu  72   73 , N Papadopoulos  74   75 , E P Prokopakis  76 , S Bosnic-Anticevich  77 , R O'Hehir  78   79 , J C Ivancevich  80 , H Neffen  81 , E Zernotti  82 , I Kull  83 , E Melen  84   85 , M Wickman  86 , C Bachert  87 , P Hellings  3   88   89 , S Palkonen  90 , C Bindslev-Jensen  91 , E Eller  91 , S Waserman  92 , M Sova  93 , G De Vries  94 , M van Eerd  94 , I Agache  95 , T Casale  96 , M Dykewickz  97 , R N Naclerio  98 , Y Okamoto  99 , D V Wallace  100 ; MASK study group
Collaborators, Affiliations
Review

MASK 2017: ARIA digitally-enabled, integrated, person-centred care for rhinitis and asthma multimorbidity using real-world-evidence

J Bousquet et al. Clin Transl Allergy. .

Erratum in

Abstract

mHealth, such as apps running on consumer smart devices is becoming increasingly popular and has the potential to profoundly affect healthcare and health outcomes. However, it may be disruptive and results achieved are not always reaching the goals. Allergic Rhinitis and its Impact on Asthma (ARIA) has evolved from a guideline using the best evidence-based approach to care pathways suited to real-life using mobile technology in allergic rhinitis (AR) and asthma multimorbidity. Patients largely use over-the-counter medications dispensed in pharmacies. Shared decision making centered around the patient and based on self-management should be the norm. Mobile Airways Sentinel networK (MASK), the Phase 3 ARIA initiative, is based on the freely available MASK app (the Allergy Diary, Android and iOS platforms). MASK is available in 16 languages and deployed in 23 countries. The present paper provides an overview of the methods used in MASK and the key results obtained to date. These include a novel phenotypic characterization of the patients, confirmation of the impact of allergic rhinitis on work productivity and treatment patterns in real life. Most patients appear to self-medicate, are often non-adherent and do not follow guidelines. Moreover, the Allergy Diary is able to distinguish between AR medications. The potential usefulness of MASK will be further explored by POLLAR (Impact of Air Pollution on Asthma and Rhinitis), a new Horizon 2020 project using the Allergy Diary.

Keywords: ARIA; App; Asthma; Care pathways; MASK; Rhinitis; mHealth.

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Figures

Fig. 1
Fig. 1
Allergy Diary screens relating to Visual Analogue Scale and medications (from Bousquet et al. [26])
Fig. 2
Fig. 2
Correlation between Visual Analog Scale (VAS) global measured and nasal symptoms (VAS nose) (unpublished)
Fig. 3
Fig. 3
Transfer of patient information on a computer and printed information (from Bousquet et al. [46]
Fig. 4
Fig. 4
Clinical decision support systems consensus for allergic rhinitis (from Bousquet et al. [28])
Fig. 5
Fig. 5
CDSS digitalization (submitted)
Fig. 6
Fig. 6
Impact of allergic rhinitis depending on the number of symptoms (from Bousquet et al. [33])
Fig. 7
Fig. 7
Correlation between VAS work and VAS global measured, nose, eye and asthma (Bousquet unpublished)
Fig. 8
Fig. 8
Impact of symptoms on work, school and daily activities (from Bousquet et al. [33])
Fig. 9
Fig. 9
VAS levels in severe rhinitis depending on multimorbidity (from Bousquet et al. [60])
Fig. 10
Fig. 10
Treatments received in MAS (from Bousquet et al. [59])
See this image and copyright information in PMC

References

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