Relevance. Examining spatial and temporal variations in child morbidity rates allows for the timely identification of problematic situations in this domain and the concentration of efforts on their prevention.

The purpose of the study: is to analyze morbidity indicators of the child population aged 0–17 years in the Gomel Region for the period 2014–2023.

Materials and methods. The study used data from annual reports on child morbidity in the Gomel Region for 2014–2023. The research employed analytical and statistical methods, including the calculation of intensive and extensive indicators of primary and overall morbidity, along with an analysis of their dynamics. Student’s t-test was used to assess the statistical significance of differences; differences were considered statistically significant at p ≤ 0.05.

Results. During the analyzed period, a statistically significant increase in both primary and overall morbidity among the child population of the Gomel Region was recorded, particularly in 2023 compared to 2020. Respiratory diseases rank first in the nosological structure of both primary and overall morbidity. Diseases of the skin and subcutaneous tissue occupy the second rank in the primary morbidity structure and the third in the overall morbidity structure. Infectious and parasitic diseases rank third in the primary morbidity structure and fifth in the overall morbidity structure. In the overall morbidity structure, diseases of the eye and adnexa are in second place, whereas in the primary morbidity structure they rank fifth. Injuries, poisonings, and certain other consequences of external causes hold the fourth position in the primary morbidity structure, while diseases of the musculoskeletal system and connective tissue occupy the fourth position in overall morbidity. The peak of child morbidity in the Gomel Region was noted in 2021, which was driven by an almost twofold rise in infectious and parasitic diseases, presumably due to the COVID-19 pandemic.

Conclusion. The data obtained can be used to develop a set of measures for the prevention, early diagnosis of diseases and borderline conditions, as well as for organizing dispensary observation of children, including those who have had COVID-19.

Relevance. Type 2 diabetes mellitus (T2DM) remains one of the leading medical and social problems in modern healthcare, characterized by a steady increase in prevalence, a high frequency of cardiovascular complications, and a significant economic burden. In recent years, more and more data indicate the clinical and pathogenetic heterogeneity of DM2, which casts doubt on its consideration as a homogeneous disease and justifies the need for more detailed epidemiological and phenotypic analysis.

The purpose of the study: assessment of the dynamics and age-related characteristics of type 2 diabetes mellitus first identified in the Republic of Uzbekistan in the period 2022–2024 against the background of the implementation of population screening, as well as determining the epidemiological context for the possible existence of various phenotypes of DM2.

Materials and methods. A retrospective descriptive epidemiological study was conducted based on aggregated data from official statistics on newly identified cases of type 2 diabetes mellitus in 2022–2024. The analysis was performed taking into account age (18–29, 30–59, ≥60 years), gender, and the region of residence. The proportion of age groups and morbidity rates per 100,000 population were calculated.

Results. In Uzbekistan, a steady increase in the prevalence and incidence of diabetes mellitus has been observed, especially pronounced after the introduction of screening since 2022. More than 60% of all new cases of AD2 annually occur in working-age individuals aged 30–59, indicaing a significant socio-economic burden. The proportion of patients ≥60 years old consistently increased (37.5% to 39.4%), reflecting the “aging” of the identified structure. Morbidity in the ≥60 age group exceeded the indicators of the 30–59 age group by more than 2.5 times and was characterized by pronounced regional variability. The proportion of young patients aged 18–29 remained low, however, during the observation period, a trend towards growth was noted, which indicates the «youthing» of DM2.

Conclusion. The identified age and regional characteristics of newly diagnosed type 2 diabetes form the prerequisites for the existence of various population phenotypes of the disease in Uzbekistan and justify the need for further clinical and functional studies, taking into account modern phenotypic classifications.

Relevance. Evaluation of the health system and its individual areas or activities is the most important basis for strategic and operational-tactical planning, as well as a tool for analysis and control at all levels of management decision-making: federal, regional and municipal. Assessment of the effectiveness and/or effectiveness of medical examinations as the largest preventive measure seems appropriate from both objective (based on statistical data) and subjective (based on survey data) points of view. The study attempts to evaluate the opinion of specialists directly responsible for collecting statistical data.

The purpose of the study: to analyze the opinion of specialists responsible for collecting and providing statistical data in the subjects of the Russian Federation on the medical examination of the adult population, including in terms of registration of statistical data.

Materials and methods. The study was conducted using a questionnaire method using specially designed questionnaires. The analysis of the obtained data is carried out by the method of structural description. Statistical data processing was carried out using Microsoft Office Excel programs.

Results. The results of a survey of specialists responsible for collecting and providing statistical data in the regions of the Russian Federation are presented. The respondents assessed the preventive direction in healthcare, as well as the degree of influence of medical examinations of certain groups of the adult population on public health. An opinion was expressed on the various components of the medical examination technology, as well as on the regulatory framework for medical examinations, including those related to the collection and accounting of statistical data. A number of questions were devoted to the degree of reliability of data on behavioral and nutritional-behavioral risk factors for the development of chronic non-communicable diseases.

Conclusion. Despite a number of objective and subjective problems, medical examination is a promising strategic measure to achieve a state of complete physical, spiritual and social well-being of citizens of the Russian Federation. At the same time, according to experts responsible for collecting and providing statistical data on medical examinations at the level of subjects, there is a need to improve information and methodological support for medical examinations of certain groups of the adult population and adjust regulatory legal acts regulating the procedures for conducting and collecting statistical data on medical examinations.

Relevance. The modern healthcare system is entering a stage of deep digital transformation, with artificial intelligence becoming a key tool. The development of algorithms, the growth of computing power and the accumulation of large amounts of medical information have made it possible to move from theoretical models to real digital solutions in clinical and management practice. From a managerial point of view, artificial intelligence opens up new opportunities for analyzing big data, predicting the needs of the population for medical care, optimizing patient routing and resource allocation. The use of intelligent analytical platforms helps to increase the efficiency of medical organizations, reduce the administrative burden and implement the principles of quality management. From a clinical perspective, artificial intelligence is becoming a tool for improving the accuracy of diagnosis, early detection of diseases, personalization of treatment and evaluation of the effectiveness of therapy. Machine learning algorithms are actively used in radiology, cardiology, oncology and telemedicine, providing an additional level of expert support to the doctor and reducing the likelihood of diagnostic errors. Special attention is paid to issues of ethics, clinical verification of results, protection of personal data and preservation of the leading role of the doctor as a responsible decision-making subject. The article examines the organizational, professional and socio-cultural aspects of the use of artificial intelligence in healthcare in the Republic of Uzbekistan.

The purpose of the study: to summarize modern approaches to the use of artificial intelligence in healthcare, evaluate the clinical and managerial possibilities of its use, identify limitations and ethical aspects.

Materials and methods. An analytical review of international publications (WHO, NEJM, JAMA, Nature Medicine, and others), as well as regulatory documents on digital healthcare, was conducted. A descriptive and analytical method was used to summarize data on clinical and managerial applications of artificial intelligence.

Results. The use of artificial intelligence is highly effective in the following areas: medical image analysis (computer and magnetic resonance imaging, X-ray); disease prediction (cardiovascular, oncological, endocrine); clinical decision support; monitoring of chronic patients; patient flow management; optimization of healthcare resources. In a management context, artificial intelligence makes it possible to analyze large amounts of data, predict the burden on the healthcare system, and increase the efficiency of resource allocation. Despite its high productivity, its implementation is accompanied by a number of limitations. The main problems are the quality of the source data, the risk of algorithmic errors, and limited interpretability of the models. Ethical issues are of particular importance: the protection of personal data, the transparency of algorithms and the preservation of the role of the doctor as a subject of decision-making. Artificial intelligence does not replace clinical thinking, but acts as a tool to enhance it. Thus, a new healthcare model based on the use of digital technologies is being formed.

Conclusion. Artificial intelligence is an important tool for healthcare transformation, improving the quality of medical care and management efficiency. Its application requires the development of digital infrastructure, the training of medical personnel and the formation of a new ethical and legal model.

Relevance. Relevance. In the context of the transformation of social standards in healthcare and the strengthening of international legal frameworks, this study focuses on the importance of minimum social guarantees. Social standards are becoming a key tool for planning and optimizing the resources of the healthcare system, which makes them particularly important in achieving universal health coverage.

The purpose of the study: to analyze the evolution of social standards in the healthcare system of the Russian Federation, to trace their trans- formation into the structure of the State Guarantee Program and to substantiate their key importance for ensuring universal access to medical care, including taking into account international experience.

Materials and methods. The methodological basis of the study was a comparative institutional analysis supplemented by methods of regulatory analysis and historical retrospect. The empirical base was formed based on the study of official regulations, reports of ministries of health and compulsory health insurance funds, publications of international organizations (WHO, Organization for Economic Cooperation and Development, ILO, World Bank), etc.

Results. The article examines the evolution of social standards in healthcare in the Russian Federation from the regional standards of the 1990s to the modern Program of state guarantees. Based on a comparative analysis of international experience (the Republic of Belarus, the Kyrgyz Republic, Great Britain, Germany) and a historical retrospective of Russian legislation, key approaches to the formation of guaranteed volumes of medical care have been identified. Special attention is paid to the transformation of social standards into those of the State Guarantee Program, the expansion of their list and their importance for ensuring universal access to medical care for citizens. The importance of social standards for calculating the necessary resources is substantiated, taking into account the specifics of the organization of the healthcare system, including procedures for providing medical care and regulations on the organization of types of medical care. The directions of improving the methodology for calculating standards to increase the availability and quality of medical care are proposed.

Conclusion. The study shows the key role of social standards in ensuring universal access to medical care in the Russian Federation. In order to realize the constitutional right of citizens to health protection, it is necessary to further improve the system of standards and their financial support as an element of national security.