Prospects for digital solution implementation in organization of processes aimed at early detection of psoriatic arthritis in patients with psoriasis.

The national healthcare system is undergoing its digital transformation, aiming at improving the effectiveness and quality of medical care in the Russian Federation. Psoriasis, a disease at intersection of two specialties, dermatovenereology and rheumatology, is of interest in terms of possibility of improving patient outcomes using digital technologies. A i m : to analyze the possibility of digital approach to processes targeted to early detection of psoriatic arthritis in patients with psoriasis. Materials and methods: bibliographic, analytical, mathematical modeling methods. Results. Psoriasis is one of the most common severe chronic skin diseases. Besides skin manifestation, damage of joints, spine and entheses develops in up to 42% of patients, leading to worsening of patients’ prognoses and quality of life, and increasing disability rates and medical costs. Every fourth Russian patient has clinically significant delay in diagnosis of psoriatic arthritis. Meanwhile early detection and initiation of treatment of psoriatic arthritis can improve clinical and functional outcomes of patients. The time interval between the onset of psoriasis and psoriatic arthritis in most patients makes relevant a risk-oriented approach to the management of such patients. This approach is possible through introduction into dermatological clinical practice of developed and validated predictive models that allow to calculate individual quantitative assessments of probability and time till psoriatic arthritis onset in adult patients with moderate or severe psoriasis. These models are available in calculation, graphical and/or tabular forms. Considering the relevance of an issue, digital development priority and the level of digital maturity of the national healthcare system achieved to date, technological capabilities and examples of successful practical implementation, the optimal form for their effective practical implementation of these predictive models seems to be digital. Conclusions. The implementation of predictive models into clinical practice in the form of medical decision support system will automate the receipt of prognoses for patients by medical workers. It will facilitate personalized predictive approach to medical care in order to improve its quality and prompt early psoriatic arthritis detection. Artificial intelligence technologies are promising for further of predictive models improvement.