A Novel Digital Self-management System Targeting Automated Prevention of Asthma

The ultimate goal for all patients is to achieve asthma control. There are various tools for evaluating a patient's asthma control, one is to use validated questionnaires e.g. Asthma Control Test (ACT) (1), another is to evaluate symptoms in patient history based on recommended characteristics from the Global Initiative for Asthma (GINA) (2). These characteristics emphasize optimal asthma control as no symptoms, undisturbed sleep, no severe exacerbations, no emergency visits, normal lung function and no limitations in daily activities.

The characteristics defining asthma control according to GINA guidelines are widely used as the golden standard for both clinical research and for asthma care (3, 4). Based on a patient's number of characteristics, GINA classifies asthma as controlled, partly controlled or uncontrolled (5). The GINA guidelines include two domains for assessment, the first is the evaluation of symptoms and the second is physician´s evaluation of patient's future risk for exacerbations. Indicators of increased health cost of asthma like e.g. health care utilization, medication and lost school/work days are associated with uncontrolled asthma (6). In addition, studies have shown that patients with lower socio-economic status are associated with more impaired asthma control (7-9), and further attention is needed to assist patients with impaired asthma control through new approaches and better management strategies.

Poor adherence to asthma management and simple practical tools for diagnosing asthma can lead to under- and over-diagnosis of asthma in primary health care (10, 11). In most cases, including in the EU, asthma patients visit their doctors less than once a year, giving healthcare providers only a snapshot of the patient's condition (12, 13). New approaches are needed to improve adherence in asthma care.

Patient education in self-management using self-monitoring of lung function and symptoms, coupled with adjustable treatment plan appear to be effective compared with other forms of asthma self-management according to a Cochrane review (14). National asthma programmes focusing on management and improving asthma care has proved to reduce the morbidity of asthma and its impact on individuals as well as on the society (15). Patient education in self-management improves health and the quality of life for people with asthma, as well as reducing health care costs (14). However, in spite of this convincing evidence on how to treat and manage asthma, there is worldwide significant discrepancy between real life practice and guidelines of asthma management (16, 17).

Clinical decision support systems for self-management Significant worldwide discrepancy exists between real life asthma practice and guidelines of management (16, 17). Self-management based on self-monitoring of lung function and symptoms, coupled with adjustable treatment plan appear to be effective compared with other forms of asthma self-management according to a Cochrane review (14). Furthermore, electronic medical records are largely implemented in asthma care, and it is feasible to enable health care providers to monitor and support patient's self-management with computer decision support systems (CDSS). Therefore, we target to improve incomplete asthma management by develop and CE-mark the novel digital self-management system Asthmatuner (Medituner AB, Sweden). The system consists of a patient smartphone application and a portable wireless spirometer for measuring lung function, and a healthcare provider user interface to prescribe treatment plan and assess patient data. The app provides patients with a daily treatment recommendation linked to patient's current status of asthma (controlled, partly- or uncontrolled asthma) (2). Recently in 2018, Asthmatuner significantly reduced asthma symptoms in children and adolescents compared to traditional management in a randomised controlled cross-over trial (18).