In the previous study, a checklist was developed to assess the readiness of healthcare organizations to introduce innovative medical technologies; this study continues that work. Objective. To perform expert validation of the checklist and assess the importance of factors of the index of innovative readiness of a healthcare organization. Material and methods. The object of the expert evaluation was a checklist for assessing 17 factors that determine the readiness of a healthcare organization to introduce innovations. Sixty-five experts completed an expert questionnaire, and assessed the significance of each factor in points from 1 to 5, where 1 point was the lowest significance and 5 points was the highest. The average score for each factor, standard deviation, Kendall’s coefficient of concordance (W), and Cronbach alpha coefficient were calculated to determine the internal consistency of the expert questionnaire. The non-parametric Friedman test was used to assess the statistical significance of the differences (threshold significance level p<0.05). Results. The factor “Readiness and interest of the management of a healthcare organization” had the highest average significance (4.133 points; the total weight coefficient was 1.160). Next in descending order of importance were “Availability of all necessary consumables” (3.933 points; total weight coefficient 1.156), “Availability of the necessary “heavy” equipment,” and “In the absence of the necessary equipment, the possibility of its acquisition within 6 to 12 months” (each received an estimate of 3.911 points; total weight coefficient 1.258). Kendall’s coefficient of concordance W was 0.29548 (p<0.000001), Cronbach alpha coefficient was 0.93241. The validity of the previously proposed interpretation of the index of innovation readiness of the settings was confirmed by 56 of 65 experts (86.15%). A healthcare organization is recognized as ready to introduce innovative medical technology with an index of 8 points or more. Positive answers must be obtained for at least one item from each section, and one more positive answer should be given for any additional item. Fifty-nine (90.77%) out of 65 experts considered the proposed index of innovation readiness of the settings and the checklist for its calculation to be valid and ready for practical use. Conclusion. The checklist developed and validated by experts is a new tool for planning the introduction of new medical technologies in healthcare organizations.

Objective. To analyze the results of developing a neural network dialogue system for the formation of relevant responses to written requests of the population to a medical institution. Material and methods. The study was conducted at the Volga District Medical Center of the FMBA of Russia. The authors used a pre-trained Bidirectional Encoder Representations from Transformers (BERT) model. As part of the study, a phased approach to fine-tuning the BERT model was used: adaptation in everyday vocabulary (Yandex/geo-reviews), optimization using loss functions (TripletLoss, ArccosMarginLoss), and classification using the SVM method. The dataset (2.623 records) was divided into training and test samples in a proportion of 8/2. Results. Citizens’ requests were classified using a feedback database of 2.623 records and divided into 18 categories. Categories with fewer than 20 entries were removed due to a lack of representativeness. It was found that messages have a substantial semantic overlap between categories. A single email could simultaneously contain several requests belonging to different categories. When the entry contained several similar but multidirectional statements, it resulted in a model failure. To avoid this, it was decided to use sets of templates that the model could offer the operator to facilitate the preparation of a response to a patient’s request. Conclusion. The study results present compelling evidence that it is currently not feasible to completely exclude human participation in the full-fledged dialogue between artificial intelligence and a patient. The technological imperfection of modern artificial intelligence platforms does not yet allow solving the problems of subtle differentiation of a semantically complex message and its emotional coloring, thus preventing their wide autonomous use. However, they can already significantly facilitate the work of medical personnel in remote interaction with the served population.

Objective. To obtain a summary estimate of the prevalence of postpartum depression (PPD) in the Russian Federation using a systematic review with a meta-analysis. Material and methods. The search for studies was conducted in two Russian and five foreign electronic bibliographic databases. The systematic review included studies on women living in the Russian Federation who gave birth to a child within 12 months; it also describes a methodology for identifying PPD and quantitative indicators of the prevalence of PPD among study participants. In a meta-analysis of 51 studies including over 12.800 participants, the overall prevalence of PPD was calculated using the DerSimonian-Laird random effects model. Additionally, the PPD prevalence was calculated separately in subgroups of studies that used different diagnostic tools at different periods and with different methodological quality. Results. The overall prevalence of PPD In Russia for all included studies is 34.47% (95% CI 29.14—39.81%), and for the last 5 years, from 2020 to 2024, 43.50% (95% CI 35.5—51.5%). The meta-regression results showed a statistically significant positive association between the year of publication and the prevalence of PPD (regression coefficient +0.019, p=0.004). Results are consistent: the resulting prevalence of PPD is not critically dependent on any single study. The prevalence of PPD among women with complicated pregnancy and childbirth was slightly higher than among women without it, but there were no statistically significant differences: 48.9% (95% CI 26.5—71.4%) vs. 42.3% (95% CI 33.5—51.1%; z=0.54; p=0.59). In high-quality studies, the mean prevalence of PPD was 5.7% lower than in the others, but this difference was not statistically significant. The cumulative PPD prevalence in studies assessed by the Edinburgh PPD Scale (EPDS) with a threshold value of ≥10 points was 49.6% (95% CI 39.3- 59.7%). Conclusion. In the Russian Federation, there is a high prevalence of postpartum depression, especially in studies performed over the past 5 years, from 2020 to 2024, which supports the need to develop measures for its detection, prevention, and treatment.

Objective. To evaluate the economic feasibility of expanding the use of netakimab for the treatment of adult patients with moderate to severe psoriasis vulgaris compared to other biologics and small molecules used in the health care settings of the Russian Federation. Material and methods. Costs were calculated according to the dosing regimen approved in the Russian Federation for all considered treatment options for adults with moderate to severe psoriasis vulgaris. The analysis used the registered prices inlcuding VAT of the manufacturer, including value-added tax. If generics or biosimilars were available, the calculation was based on the minimum registered prices. Results. Netakimab is the least costly in treating psoriasis vulgaris compared to other biologics and small molecules with comparable or superior efficacy assessed using PASI 75 and PASI 90. To achieve costs equal to those required for the treatment of psoriasis vulgaris with netakimab for 2 years, it is necessary to reduce the cost of competitors by 30—74%, which corresponds to the provision of 0.4 to 2.8 additional packages free of charge for each package purchased. Conclusion. Expanding the use of netakimab for treating adult patients with moderate to severe psoriasis vulgaris will reduce the cost of the Russian health care system, with comparable or higher clinical efficacy compared to other genetically engineered biological drugs and small molecules. Netakimab can be considered the drug of choice.

The problem of publication bias and ways to minimize it is addressed based on a non-systematic literature search and review. Publication bias is the tendency to publish original research with the achieved statistical significance of the results (p<0.05). Consequently, in the aggregate of accumulated data, there is a shift towards positive results, while the results of studies with negative results are not published for several reasons. This bias poses a significant risk for both patients and the medical community, as well as for scientific departments and the entire healthcare system. The current status quo, which shapes the socially expected result from researchers, can contribute to data manipulation to obtain statistical significance in scientific papers. The problem of publication bias is particularly relevant in theses, where the requirements for scientific novelty often lead to a situation where authors of theses focus on finding any differences between groups. Even if they have no meaningful practical value, these differences are often highlighted as the study’s main finding. In this context, there may be a temptation to present results that are not true, which further exacerbates the bias problem and reduces confidence in the results of scientific research. In order to reduce the impact of publication bias, the decision to publish the results of a study should be separated from the statistical significance of the results obtained and be focused on the purpose of the study and the correctness of its methodology. For theses, the requirements should also shift from the search for any differences to the study’s methodological quality, emphasizing the publication of those results that the authors initially planned. This approach will avoid the artificial focus on insignificant differences and reduce the risk of publication bias, ensuring greater transparency and reliability of scientific data.

Objective. To assess the social and economic damage caused by the elevated low-density lipoprotein cholesterol (LDL-C) in the Russian Federation population from the state’s standpoint. Material and methods. Based on the ESSE-RF study data on the LDL-C level and the literature data on the corresponding relative risk, the population attributable fraction (PAF) of this risk factor for coronary heart disease (CHD) and ischemic stroke in the population under the age of 65 years was calculated. The social and economic damage caused by LDL-C is modeled as a proportion equal to the PAF of the CHD and ischemic stroke socio-economic burden in Russia for this age group. The probable damage value associated with LDL-C in persons 65 years and older was also calculated. Results. Elevated LDL-C levels in persons younger than 65 years account for more than half of ischemic stroke and CHD, including myocardial infarction, as well as a reduction in life expectancy by 0.7 years in males and 0.3 years in females. The annual medical costs associated with these diseases amounted to 51.4 billion rubles, and the social costs amounted to 29.0 billion rubles. The annual damage to gross domestic product (GDP) is estimated at 209.1 billion rubles. Considering all the lost «economically active» years, the GDP damage exceeds 1 trillion rubles. The estimated contribution of LDL-C to the annual damage associated with coronary heart disease and ischemic stroke in the age group of individuals 65 years and older is estimated at 78.9 billion rubles, including 62.5 billion rubles in medical and social care costs. Conclusion. Significant socio-economic damage caused by elevated low-density lipoprotein cholesterol levels indicates the need for preventive measures to control this risk factor, starting at a young age.

Objective. To develop an integral antimicrobial therapy quality index (AMTQI) using the multi-criteria decision analysis (MCDA) methodology and to validate the calculation models in an in-hospital setting. Materials and methods. Based on the content analysis and expert questionnaires, a set of criteria for assessing the quality of antimicrobial therapy (AMT), assessment scales were developed, and weight coefficients (WC) were calculated using the direct weighting (DW) method and the indirect method of Potentially All Pairwise RanKings of all possible Alternatives (PAPRIKA). Based on the obtained WCs, a simple linear aggregation model (SLAM) with two sets of WCs (DW and PAPRIKA) and a multi-attribute value theory (MAVT) with a set of PAPRIKA WCs were created. Model validation and scenario sensitivity analysis were performed on 10 case histories of patients in an inpatient department. Results. A list of 12 AMT quality criteria was created; the WC criteria using DW were comparable, while the PAPRIKA method showed more differences between the WCs. When calculating AMTQI, the comparability of the assessment for each AMT case was found (mean SLAM (DW) value was 73.3±26.2, SLAM (PAPRIKA) 73.0±24.9, and MAVT (PAPRIKA) 72.1±25.1 points). The result rankings were the same in the SLAM models and differed in the two patients in the MAVT. All models demonstrated robustness for 8 of the 12 criteria in the scenario sensitivity analysis. Conclusion. A MCDA method can be used to develop a model of an AMTQI based on a comprehensive set of universal criteria, with the SLAM and MAVT models appearing comparable. However, the results obtained need to be confirmed using more data. The AMTQI can be used in the internal and external audit of quality control of medical care in healthcare organizations.

Objective. To develop the best approach to digitizing clinical guidelines in the Russian Federation. Material and methods. An analytical study was conducted at the N.N. Petrov National Medical Research Center for Oncology of the Ministry of Health of Russia using the clinical guidelines “Ovarian cancer/fallopian tube cancer/primary peritoneal cancer.” The methods of flowcharts and notation Business Process Model and Notation (BPMN) 2.0 were used to describe the algorithms and processes. Results. During the digitization, algorithms for treating patients were created with triggers, logical gateways, tasks, and threads. Two documents were obtained: a graphical version of the process display and a machine-readable description of the process in XML format, which can be used in medical information systems. Conclusion. A methodology based on the coding of specific medical services, drug treatment regimens, and surgical interventions is proposed to digitize clinical guidelines, ensure a full-fledged representation of the patient management algorithm, and use it in medical information systems. Further development of the methodology should aim to use universal markup languages and develop tools convenient for doctors to use.

The content and/or weight coefficients of diagnosis-related groups (DRG) for payment for inpatient and day medical care for 2025 have been updated. Following clinical guidelines, changes have been made to the DRG in payment for drug therapy for malignant neoplasms in adults and treatment of transient ischemic attacks, vascular cerebral syndromes, cerebral hemorrhage, and cerebral infarction. For cerebrovascular disorders, the actualization resulted in a significant increase in the payment tariff. Weight coefficients of DRG to pay for the treatment of chronic viral hepatitis B and C using genetically engineered biological agents and selective immunosuppressants, as well as in vitro fertilization, were recalculated. New groups were formed according to the following profiles: “medical rehabilitation,” “neurology” (three DRGs for complex neurological diseases), “ophthalmology” (intravitreal administration of drugs), and a group “daily hospitalization for diagnostic purposes” was added.

Early diagnosis and treatment of type 1 diabetes mellitus. Issues of clinical feasibility, organization, and accessibility of medical care. Resolution on the results of the Expert Council held on December 17, 2024, Moscow.