RESUMO
AIMS: Mobile Airways Sentinel NetworK (MASK) belongs to the Fondation Partenariale MACVIA-LR of Montpellier, France and aims to provide an active and healthy life to rhinitis sufferers and to those with asthma multimorbidity across the life cycle, whatever their gender or socio-economic status, in order to reduce health and social inequities incurred by the disease and to improve the digital transformation of health and care. The ultimate goal is to change the management strategy in chronic diseases. METHODS: MASK implements ICT technologies for individualized and predictive medicine to develop novel care pathways by a multi-disciplinary group centred around the patients. STAKEHOLDERS: Include patients, health care professionals (pharmacists and physicians), authorities, patient's associations, private and public sectors. RESULTS: MASK is deployed in 23 countries and 17 languages. 26,000 users have registered. EU GRANTS 2018: MASK is participating in EU projects (POLLAR: impact of air POLLution in Asthma and Rhinitis, EIT Health, DigitalHealthEurope, Euriphi and Vigour). LESSONS LEARNT: (i) Adherence to treatment is the major problem of allergic disease, (ii) Self-management strategies should be considerably expanded (behavioural), (iii) Change management is essential in allergic diseases, (iv) Education strategies should be reconsidered using a patient-centred approach and (v) Lessons learnt for allergic diseases can be expanded to chronic diseases.
RESUMO
BACKGROUND: Collecting data on the localization of users is a key issue for the MASK (Mobile Airways Sentinel networK: the Allergy Diary) App. Data anonymization is a method of sanitization for privacy. The European Commission's Article 29 Working Party stated that geolocation information is personal data.To assess geolocation using the MASK method and to compare two anonymization methods in the MASK database to find an optimal privacy method. METHODS: Geolocation was studied for all people who used the Allergy Diary App from December 2015 to November 2017 and who reported medical outcomes. Two different anonymization methods have been evaluated: Noise addition (randomization) and k-anonymity (generalization). RESULTS: Ninety-three thousand one hundred and sixteen days of VAS were collected from 8535 users and 54,500 (58.5%) were geolocalized, corresponding to 5428 users. Noise addition was found to be less accurate than k-anonymity using MASK data to protect the users' life privacy. DISCUSSION: k-anonymity is an acceptable method for the anonymization of MASK data and results can be used for other databases.