Digital technologies for an improved management of respiratory allergic diseases: 10 years of clinical studies using an online platform for patients and physicians

Abstract

Background: Digital health technologies carry the great potential of assisting physicians in making well-informed diagnostic and therapeutic decisions. In allergy care, electronic clinical diaries have been recently used to prospectively collect patient data and improve diagnostic precision.

Objective: This review summarizes the clinical and scientific experience we gathered over 10 years of using a digital platform for patients suffering from seasonal allergic rhinitis.

Methods: The mobile application and back-office of AllergyMonitor (TPS software production, Rome, Italy) enable patients to record their daily allergy symptoms as well as drug and immunotherapy intake plus possible side effects in a customizable way. The results can be accessed by the patient and attending physician as concise reports via a smartphone or computer. This technology has been used in several clinical studies and routine practice since 2009.

Results: Our studies showed that A) the etiological diagnosis of SAR may be supported by matching prospectively registered symptoms with pollen counts; B) it is possible to perform a short-term prediction of SAR-symptoms at individual level; C) the adherence to daily symptom monitoring can remain high (> 80%) throughout several weeks when prescribed and thoroughly explained by the treating doctor; D) the use of mobile technology can improve adherence to symptomatic drugs as well as allergen-specific immunotherapy and E) the choice of the correct symptom-severity-score is critical at patient level, but not at group level.

Conclusion: The studies and clinical practice based on the use of AllergyMonitor have proven the reliability and positive impact of a digital platform including an electronic diary (eDiary) on the diagnostic precision of SAR in poly-sensitized patients as well as patient adherence to both, drug therapy and allergen immunotherapy.

Keywords: Digital; E-diary; Mobile health; Pollen; Precision medicine.

Fig. 1

Screenshot examples of the front end of AllergyMonitor app. On a daily basis, the user fills a short and visually enhanced questionnaire about his symptoms of the eyes, nose and lungs, as well as a visual analogue scale on his/her general condition. Once activated by the doctor via the back-office, the user is also enabled to record his/her daily medication intake, adherence to sublingual immunotherapy and potentially occurring side effects. In order to provide a summary and feedback to the user, all entered data can be easily accessed within the app in summarized graphs showing the evolution of symptoms over time

Fig. 2

Screenshots of the doctor’s AllergyMonitor back-office. Via his/her back-office, the doctor is able to access a breakdown of all recorded data as well as individual patient reports accessible as different symptom (and medication) scores and matched to local pollen monitoring data. A messaging system between doctor and patient based on e-mail, chat or SMS (short message service) facilitates direct communication. The back-office enables the doctor to configure each patient’s front end individually by entering for example symptomatic drugs or adding an immunotherapy intake and side effects monitoring

Fig. 3

AllergyMonitor report: an example referring to a pediatric patient. The software generates a printable report for the user. The report is divided into several sections, as follows: a) doctor’s prescription: recommended monitoring period, pharmacotherapy, allergen-specific immune-therapy; b) symptoms vs pollen counts: graphs illustrating the time-trends of selected symptom severity scores and pollen counts; c) medication diary: table illustrating the intake of drugs and/or SLIT during the monitoring period; d) statistical summary: a series of indexes summarizing the patient’s adherence to symptom recording, as well as drug and SLIT intake; e) space for the doctor’s comments: marked empty space for comments and notes from the treating physician

Fig. 4

Trajectories of symptom severity vs pollen counts in two pediatric patients (a: patient 1; b: patient 2) from Ascoli Piceno with allergic rhinitis, and similar allergic profile, according to SPT and CRD. Data on severity of symptoms – collected with AllergyMonitor – have been reported as Rhinoconjunctivitis Total Symptom Score (RTSS). Pollen counts (grains/m3) were obtained from the local pollen trap. Reprinted with permission from [12]

Fig. 5

Adherence (%) by reporting day and study center. It is possible to describe three phases (indicated by light background color): the 1st phase (a), lasting 6 days, during which adherence falls from 100 to 90%; the 2nd phase (b), lasting approximately 20 days, during which adherence fluctuates until reaching 88%; the 3rd phase (c) during which it declines to 80%. Reprinted with permission from [22]

Fig. 6

Impact of a eDiary on (a) medication adherence and (b) knowledge on disease. a) Adherence to daily medication with nasal corticosteroid (Mometasone) in children with Seasonal Allergic Rhinitis following usual care or being monitored with AllergyMonitor. b) Frequency of correct answers to knowledge test taken before and after the recording of symptoms connected to bits of information on allergic rhinoconjunctivitis provided via AllergyMonitor after every registration. Reprinted with permission from [15]

Fig. 7

Impact of a eDiary on adherence to SLIT. Adherence to SLIT medication in children with Seasonal Allergic Rhinitis following usual care or being monitored with AllergyMonitor. Reprinted with permission from [26]

Fig. 8

Parallel evaluation of multiple disease severity scores. Trajectories of normalized mean daily values of six disease severity scores in (a) 76 Italian, and (b) 29 German children with grass pollen-related seasonal allergic rhinitis, during the grass pollen season. Reprinted with permission from [14]

Fig. 9

Symptom monitoring of a pediatric patient with SAR during grass pollen SLIT. RTSS and pollen trajectories before starting SLIT (a) and after 1 (b), 2 (c) and 3 years of SLIT (d)