Automatic market research of mobile health apps for the self-management of allergic rhinitis

Use of Technology to Improve Adherence in Allergy/Immunology

The integration of technology into health care has shown significant promise in enhancing patient adherence, particularly in the field of allergy/immunology. This article explores the multifaceted approaches through which digital health interventions can be used to improve adherence rates among patients with allergic diseases and immunologic disorders. By reviewing recent advancements in telemedicine, mobile health applications, wearable devices, and digital reminders, as well as smart inhalers, we aim to provide a comprehensive overview of how these technologies can support patients in managing their conditions. The analysis highlights the role of personalized digital health plans, which, through the use of artificial intelligence and machine learning algorithms, can offer tailored advice, monitor symptoms, and adjust treatment protocols in real time. Moreover, the article discusses the impact of electronic health records and patient portals in fostering a collaborative patient-provider relationship, thereby enhancing communication and adherence. The integration of these technologies has been shown to not only improve clinical outcomes but also increase patient satisfaction and engagement.

Concepts for the Development of Person-Centered, Digitally Enabled, Artificial Intelligence-Assisted ARIA Care Pathways (ARIA 2024)

The traditional healthcare model is focused on diseases (medicine and natural science) and does not acknowledge patients' resources and abilities to be experts in their own lives based on their lived experiences. Improving healthcare safety, quality, and coordination, as well as quality of life, is an important aim in the care of patients with chronic conditions. Person-centered care needs to ensure that people's values and preferences guide clinical decisions. This paper reviews current knowledge to develop (1) digital care pathways for rhinitis and asthma multimorbidity and (2) digitally enabled, person-centered care.1 It combines all relevant research evidence, including the so-called real-world evidence, with the ultimate goal to develop digitally enabled, patient-centered care. The paper includes (1) Allergic Rhinitis and its Impact on Asthma (ARIA), a 2-decade journey, (2) Grading of Recommendations, Assessment, Development and Evaluation (GRADE), the evidence-based model of guidelines in airway diseases, (3) mHealth impact on airway diseases, (4) From guidelines to digital care pathways, (5) Embedding Planetary Health, (6) Novel classification of rhinitis and asthma, (7) Embedding real-life data with population-based studies, (8) The ARIA-EAACI (European Academy of Allergy and Clinical Immunology) strategy for the management of airway diseases using digital biomarkers, (9) Artificial intelligence, (10) The development of digitally enabled, ARIA person-centered care, and (11) The political agenda. The ultimate goal is to propose ARIA 2024 guidelines centered around the patient to make them more applicable and sustainable.

Concurrent validity, cut-offs and ability to change of patient-reported outcome measures for rhinitis and asthma in MASK-air®

Patient-reported outcome measures (PROMs) are used to assess a patient's health status at a particular point in time. They are essential in the development of person-centred care. This paper reviews studies performed on PROMs for assessing AR and asthma control, in particular VAS scales that are included in the app MASK-air® (Mobile Airways Sentinel networK) for asthma and rhinitis. VASs were initially developed on paper and pencil and tested for their criterion validity, cut-offs and responsiveness. Then, a multicentric, multinational, double-blind, placebo-controlled, randomised control trial (DB-PC-RCT) using an electronic VAS form was carried out. Finally, with the development of MASK-air® in 2015, previously validated VAS questions were adapted to the digital format and further methodologic evaluations were performed. VAS for asthma, rhinitis, conjunctivitis, work and EQ-5D are included in the app. Additionally, two control-medication scores for allergic symptoms of asthma (e-DASTHMA) were validated for their criterion validity, cut-offs and responsiveness.

Digitally-enabled, person-centred care (PCC) in allergen immunotherapy: An ARIA-EAACI Position Paper

In rhinitis and asthma, several mHealth apps have been developed but only a few have been validated. However, these apps have a high potential for improving person-centred care (PCC), especially in allergen immunotherapy (AIT). They can provide support in AIT initiation by selecting the appropriate patient and allergen shared decision-making. They can also help in (i) the evaluation of (early) efficacy, (ii) early and late stopping rules and (iii) the evaluation of (carried-over) efficacy after cessation of the treatment course. Future perspectives have been formulated in the first report of a joint task force (TF)-Allergic Rhinitis and Its Impact on Asthma (ARIA) and the European Academy of Allergy and Clinical Immunology (EAACI)-on digital biomarkers. The TF on AIT now aims to (i) outline the potential of the clinical applications of mHealth solutions, (ii) express their current limitations, (iii) make proposals regarding further developments for both clinical practice and scientific purpose and (iv) suggest which of the tools might best comply with the purpose of digitally-enabled PCC in AIT.

Conception and pilot testing of a self-management health application for patients with pollen-related allergic rhinitis and allergic asthma-the APOLLO app

It has been shown that pollen information services are an important self-management tool for patients with pollen-related allergic rhinitis (AR) and allergic asthma (AA). This study aimed to design an online application for patients with AR and AA, which supports patients to better manage their disease as well as to evaluate the app and present the first results of the pilot study. The pollen data were obtained from the electronic pollen information network of Bavaria, Germany. Participants were asked to fill in their allergy-related complaints in the app over a 60-day period. Subsequently, the app was evaluated. Indices and diagrams visualized the participants' individual complaints as well as the daily pollen concentration in the air. In order to motivate participants to complete the app on a daily basis, we used elements of gamification. Two thirds of the participants (N = 46) reported feeling better informed about pollen counts and their allergy when using the app. The app's simple and comprehensible design was rated positively. More than 80% of the participants would recommend the app to their family and friends. The app can be a tool for patients with AR and AA to better understand their disease.

Beyond ARIA: Will e-diaries replace retrospective questionnaires in measuring the severity of allergic rhinitis in clinical research and daily practice?

Retrospective questionnaires are used since decades to assess the severity and/or control of allergic diseases. Applications on smartphones have recently facilitated the use of prospective clinical diaries, based on questionnaires filled every day by the patient. Once limited to clinical trials, these e-diaries, based on validated disease control scores and visual analogue scales, permit a quantitative day-by-day measure free of recall bias. Given the advantages of this procedure, its use could be extended to the daily clinical practice. E-diaries may facilitate (1) a more precise identification of the culprit allergen in the diagnostic work-up of poly-sensitized patients, (2) the stratification of patients for treatment, (3) the follow-up of the patients under treatment for optimized shared decision-making, and (4) a careful assessment of preventive therapies. While a few apps are being used in scientific studies, consensus on their use in daily practice should be reached and guidelines for specialists should be elaborated by scientific associations.

Digitally-enabled, patient-centred care in rhinitis and asthma multimorbidity: The ARIA-MASK-air® approach

MASK-air® , a validated mHealth app (Medical Device regulation Class IIa) has enabled large observational implementation studies in over 58,000 people with allergic rhinitis and/or asthma. It can help to address unmet patient needs in rhinitis and asthma care. MASK-air® is a Good Practice of DG Santé on digitally-enabled, patient-centred care. It is also a candidate Good Practice of OECD (Organisation for Economic Co-operation and Development). MASK-air® data has enabled novel phenotype discovery and characterisation, as well as novel insights into the management of allergic rhinitis. MASK-air® data show that most rhinitis patients (i) are not adherent and do not follow guidelines, (ii) use as-needed treatment, (iii) do not take medication when they are well, (iv) increase their treatment based on symptoms and (v) do not use the recommended treatment. The data also show that control (symptoms, work productivity, educational performance) is not always improved by medications. A combined symptom-medication score (ARIA-EAACI-CSMS) has been validated for clinical practice and trials. The implications of the novel MASK-air® results should lead to change management in rhinitis and asthma.

Cutoff Values of MASK-air Patient-Reported Outcome Measures

BACKGROUND

In clinical and epidemiological studies, cutoffs of patient-reported outcome measures can be used to classify patients into groups of statistical and clinical relevance. However, visual analog scale (VAS) cutoffs in MASK-air have not been tested.

OBJECTIVE

To calculate cutoffs for VAS global, nasal, ocular, and asthma symptoms.

METHODS

In a cross-sectional study design of all MASK-air participants, we compared (1) approaches based on the percentiles (tertiles or quartiles) of VAS distributions and (2) data-driven approaches based on clusters of data from 2 comparators (VAS work and VAS sleep). We then performed sensitivity analyses for individual countries and for VAS levels corresponding to full allergy control. Finally, we tested the different approaches using MASK-air real-world cross-sectional and longitudinal data to assess the most relevant cutoffs.

RESULTS

We assessed 395,223 days from 23,201 MASK-air users with self-reported allergic rhinitis. The percentile-oriented approach resulted in lower cutoff values than the data-driven approach. We obtained consistent results in the data-driven approach. Following the latter, the proposed cutoff differentiating "controlled" and "partly-controlled" patients was similar to the cutoff value that had been arbitrarily used (20/100). However, a lower cutoff was obtained to differentiate between "partly-controlled" and "uncontrolled" patients (35 vs the arbitrarily-used value of 50/100).

CONCLUSIONS

Using a data-driven approach, we were able to define cutoff values for MASK-air VASs on allergy and asthma symptoms. This may allow for a better classification of patients with rhinitis and asthma according to different levels of control, supporting improved disease management.

Real-world data using mHealth apps in rhinitis, rhinosinusitis and their multimorbidities

Digital health is an umbrella term which encompasses eHealth and benefits from areas such as advanced computer sciences. eHealth includes mHealth apps, which offer the potential to redesign aspects of healthcare delivery. The capacity of apps to collect large amounts of longitudinal, real-time, real-world data enables the progression of biomedical knowledge. Apps for rhinitis and rhinosinusitis were searched for in the Google Play and Apple App stores, via an automatic market research tool recently developed using JavaScript. Over 1500 apps for allergic rhinitis and rhinosinusitis were identified, some dealing with multimorbidity. However, only six apps for rhinitis (AirRater, AllergyMonitor, AllerSearch, Husteblume, MASK-air and Pollen App) and one for rhinosinusitis (Galenus Health) have so far published results in the scientific literature. These apps were reviewed for their validation, discovery of novel allergy phenotypes, optimisation of identifying the pollen season, novel approaches in diagnosis and management (pharmacotherapy and allergen immunotherapy) as well as adherence to treatment. Published evidence demonstrates the potential of mobile health apps to advance in the characterisation, diagnosis and management of rhinitis and rhinosinusitis patients.