Proof of Concept of Remote Management of Chronic Inflammatory Airway Diseases for Patient Empowerment

Chronic rhinosinusitis (CRS) is a multifactorial disease characterized by persistent symptomatic inflammation of the mucosa of the nose and paranasal sinuses, with (CRSwNP) or without (CRSsNP) the presence of nasal polyps. It affects 5 to 12% of the general population. CRS is often associated with asthma, which has a prevalence of 4% in the general population, reaching 30%-70% among patients with CRS. The current standard clinical evaluation of patients for both diseases has two main components: a subjective one (self-assessment provided by the patient), based mainly on the PROMs (Patient-Reported Outcome Measures) questionnaire, and an objective one (formulated by the clinician). Questionnaires present accuracy and response rate problems that have been investigated in the literature, finding that short questionnaires, incentives, personalization of questionnaires as well as repeat sending strategies or telephone reminders have a beneficial impact on the quantity and quality of responses. Today there are many new channels provided by technology. Among them, AI chatbots have been used in a variety of healthcare domains such as medical consultations, disease diagnosis, mental health support and, more recently, risk communications for the COVID-19 pandemic, and can offer a better way to collect questionnaires. At the same time, the recent technical solution of new non-invasive techniques for RFID radio frequency identification devices allows subjective reports to be accompanied with objective reports. The PRECISION project aims to evaluate systems for home monitoring of chronic rhinosinusitis (CRS) and asthma, two highly prevalent chronic diseases. The frequent association between the two pathological conditions is a further argument in support of the rationality of a common approach. As regards the collection of PROMs, three acquisition channels will be compared: i) AI Chatbots; ii) PhoneBot; iii) Mobile application. Data will be analyzed in relation to patient prof