Introduction: This study highlights the importance of access to treatment services and medicines. Research has shown that a significant portion of direct expenses for individuals who are not covered by health insurance is allocated to treatment, diagnostics, and medication costs, indicating issues with the accessibility and quality of health services.
According to the World Health Organization recommendations, if out-of-pocket health expenses exceed 25% of total health financing, it heightens the risk of deepening poverty and creates inequalities related to income.
Although policies and programs aimed at increasing access to subsidized medicines are being implemented, the expected outcomes and actual implementation of these initiatives have not fully met the health needs of the entire population.
Therefore, addressing these issues is essential. For instance, improving the regulation of medicine prices, ensuring adequate supply, and enhancing the subsidy system may be necessary steps moving forward. Methods: This study was conducted using a cross sectional design, employing methods such as document analysis, comparative study, and synthesis.
The list of discounted medicines provided by the health insurance fund includes 650 items from 161 manufacturers across 40 countries. Among these medicines, 7% have expired registration, 9% have been removed from registration, 11% are out of stock, and 73% are supplied normally. Of the medicines listed, 7% are domestic, and 93% are imported, with 39% coming from Asian countries and 54% from European countries, indicating a high reliance on imports for medicine supply and accessibility. A study of the medicines supplied by the pharmaceutical supply organizations shows that 16.5% of the prices are above the maximum price set by the health insurance fund, indicating the need for establishing medicine prices based on research and evidence. Conclusion Out of the 650 types of medicines registered in the list of subsidized medicines, 27% are in a status of expired, removed, or out of stock. The price from the pharmaceutical supply organizations exceeds the upper limit of the subsidized medicine prices set by the insurance fund, covering 83.5% of the total group of medicines.
Therefore, it is necessary to update the list of subsidized medicines from the health insurance fund based on research and evidence.

Abstract Over the past decade, Big Data and Artificial Intelligence (AI) have emerged as transformative forces in healthcare, particularly in pharmaceutical policy, regulation, and drug safety surveillance. These technologies enable the systematic collection, integration, and analysis of large-scale and heterogeneous data, thereby strengthening evidence-based decision-making across the pharmaceutical lifecycle. International experience demonstrates that the integration of AI and Big Data supports early detection of adverse drug reactions (ADRs), enhances pharmacovigilance systems, automates regulatory processes, and accelerates drug discovery and development. AI-driven methods, including machine learning and natural language processing (NLP), facilitate the identification of latent patterns and risk signals from diverse data sources such as clinical trials, Real World Evidence (RWE), electronic health records, and spontaneous reporting systems.
Despite these global advances, the application of AI and Big Data within Mongolia’s pharmaceutical policy and regulatory framework remains limited. Key challenges include fragmented and poorly integrated data sources, insufficient data standardization, underdeveloped information technology infrastructure, limited human resource capacity, and gaps in legal and ethical governance. International initiatives offer valuable reference models for addressing these challenges. The World Health Organization’s VigiBase employs AI and NLP techniques to identify global ADR trends, the U.S. Food and Drug Administration’s Sentinel Initiative integrates RWE to support proactive drug safety monitoring, and the Republic of Korea’s Disease Control and Prevention Agency has implemented an NLP-based pharmacovigilance system for automated risk detection.
This study aims to assess the applicability of Big Data and AI in Mongolia’s pharmaceutical policy and regulatory system through a comparative analysis of international best practices and the identification of key implementation gaps. The findings emphasize the need for integrated data systems, harmonized standards, localized AI application models, and robust regulatory and ethical frameworks. Overall, the study highlights the potential of Big Data and AI to modernize pharmaceutical policy and regulation in Mongolia and provides evidence-based directions for sustainable implementation aligned with international best practices.

Introduction: University students encounter multiple academic, psychosocial, and environmental stressors during their transition to higher education. Nursing students may be particularly vulnerable because of concurrent academic and clinical demands. Objective: To identify the relationships among perceived stress, social support, and psychological anxiety among nursing students. Methods: A cross-sectional quantitative study was conducted among first- to fourth-year nursing students at the International University of Ulaanbaatar. After excluding 16 incomplete questionnaires, 119 valid responses were analyzed using descriptive statistics, reliability testing, and correlation analysis in SPSS version 26.
Participants had a mean age of 22.39±5.60 years, and 86.6% were female. The mean item scores were 3.15±0.40 for perceived stress, 4.11±0.78 for social support, and 2.35±0.39 for total anxiety. Perceived stress was positively correlated with total anxiety (r=.310, p=.001), personal anxiety (r=.307, p=.001), and situational anxiety (r=.261, p=.004), and negatively correlated with age (r=-.213, p=.020). Social support was not significantly correlated with perceived stress (r=.015, p=.872) but was negatively correlated with total anxiety (r=-.253, p=.005) and personal anxiety (r=-.334, p<.001). Conclusion Students’ perceived stress was associated with anxiety. Higher social support was related to lower anxiety, although a direct relationship between social support and perceived stress was not observed in this sample.

Introduction: Higher education plays a crucial role in the development and progress of a country. The refinement and effective implementation of the legal environment directly influence the quality and accessibility of the sector.
The purpose of higher education is to contribute to social and economic development, to advance innovative ideas, research, and creativity, and to prepare ethical citizens capable of working and living in multicultural environments. Since the enactment of the Law on Education, Mongolia has amended it more than 20 times. Due to global trends in educational development, changes in teaching methods, content, and learning environments, as well as increased learning opportunities through information and communication technologies, there is a growing societal demand to provide quality education that meets the needs and interests of citizens. Therefore, it is essential to continuously improve and refine the legal and policy environment.
Studying the legal framework of higher education institutions is a fundamental step toward enhancing the sector’s development and quality. Evaluating how laws are implemented helps improve the effectiveness of legal regulations and policy enforcement.
A job description is an official document that defines the functions of a specific position and certifies the required education, profession, qualifications, experience, and skills of the employee carrying out those duties. In today’s society, the operations of any organization especially educational institutions must be organized within the legal framework and based on internal rules, regulations, and job descriptions.
The implementation and compliance of these documents have a direct impact on organizational performance. As there is a need to assess the legal basis and consistency of the regulations, rules, and job descriptions at the Mongolian University of Pharmaceutical Sciences (MUPS), this study is grounded in identifying the current situation and improving legal frameworks accordingly. Materials and Methods: A total of 250 internal legal documents of MUPS were reviewed using the Compliance Matrix method. Data were processed and analyzed using Microsoft Excel and SPSS version 23. Statistical significance was considered at p<0.05. Conclusion While the legal compliance of MUPS’s internal regulations and job descriptions is at a moderate level, several documents need to be revised and aligned with current legal reforms. It is also essential to promptly develop missing job descriptions in accordance with relevant standards.