Integrating Artificial Intelligence Into International Classification of Functioning, Disability, and Health Coding: Effectiveness of a Mobile Application for Patient Questionnaires

The advancement of digital health technologies has significantly transformed clinical workflows, enabling the integration of mobile applications into routine medical practice. Smartphones and tablets equipped with specialized software have transformed methods of accessing medical information, communication between medical staff and patients, and approaches to healthcare delivery. As a result, there has been an improvement in clinical efficiency and optimization of doctors' working time.

Modern mobile applications in healthcare cover a wide range of functions, including medical reference books and drug databases, health monitoring applications, telemedicine services, and remote patient monitoring applications. Proper use of such applications demonstrates effectiveness in improving the quality of patient care and reducing appointment times. Moreover, the widespread adoption of smartphones among various age groups, including the elderly, contributes to the integration of mobile applications in the rehabilitation process. This opens up opportunities for effective control of treatment and rehabilitation processes in a remote format, which is particularly relevant for rural areas and regions with a shortage of medical personnel.

At the current stage, one of the key challenges faced by doctors is limited patient appointment time, especially in conditions of staff shortages and high load on the medical system. In Kazakhstan, general practitioners are allocated 15 minutes per patient appointment, while narrow specialists have 20 minutes. During this short period, the doctor must conduct patient interviews, perform examinations, and complete all necessary medical documentation. This significantly complicates the possibility of in-depth patient assessment and increases the risk of medical errors, especially when there is insufficient time for comprehensive clinical decisions.

Of particular interest in this context are developments using artificial intelligence (AI) technologies. They have the potential to accelerate diagnostics, support decision-making, and improve diagnostic accuracy, particularly in disease classification according to the ICF. However, the efficacy of AI-driven tools in functional health classification remains underexplored, particularly in real-world clinical settings. Research in this area could provide important data on how well artificial intelligence handles ICF diagnoses and how useful its recommendations can be for doctors.

The International Classification of Functioning, Disability and Health is a fundamental tool of modern medicine that has significantly expanded the traditional approach to patient assessment. Its fundamental value lies in its holistic view of human health, overcoming the limitations of the classical medical model, which focuses primarily on diagnoses and pathophysiological disorders. The ICF offers a universal standardised language for specialists worldwide, ensuring effective communication between representatives of different medical disciplines. In contrast to the disease-oriented diagnostic classification of ICD, the ICF focuses on the functional capacity of the individual, which is crucial for planning and evaluating the effectiveness of rehabilitation interventions. Its relevance also extends to various areas of clinical practice, including geriatrics, where it helps to comprehensively assess the condition of elderly patients; neurology, where it is used in stroke, brain injury and neurodegenerative diseases; orthopaedics and traumatology to assess functional limitations after injury; and psychiatry, paediatrics and social medicine (18-20). The ICF is particularly valuable in the context of health and insurance systems, where it serves as a basis for decisions about coverage and resource allocation.