MON-685 Decision Support in Electronic Health Records as a Tool to Improve Care for Patients with Obesity

Abstract Disclosure: O. Derevyanko: None. D. Tatiana: None. E. Ipatova: None. S. Zaira: None. R. Tatiana: None. F. Dmitry: None. Background & Aims: Obesity is a major global public health challenge, with rising prevalence and significant associated risks, including cardiovascular disease, diabetes, and musculoskeletal disorders. Despite its widespread impact, obesity is often underdiagnosed and inadequately managed, partly due to knowledge gaps and inconsistent application of guidelines among healthcare professionals. While specialists such as endocrinologists, nutritionists, and bariatric surgeons play a central role in obesity management, there is a growing need for general practitioners (GPs), internists, and primary care providers to have a deeper understanding of the condition. This is particularly critical given the increasing prevalence of obesity and its complications, which contribute to substantial morbidity, mortality, and healthcare costs. This study aimed to evaluate the quality of obesity care for women in Russia and assess the impact of an Electronic Health Record (EHR) system with integrated decision support on improving diagnosis, treatment, and overall management. Methods: We analyzed 1,819 EHRs of women with obesity from the Fomin Clinic across 12 Russian cities, comparing data before and after the implementation of a decision support system. The records were divided into two groups: 904 pre-implementation and 915 post-implementation. Care quality was evaluated on a 100-point scale, assessing diagnostics, nutritional counseling, physical activity recommendations, and treatment adherence. The decision support system was based on guidelines from the Endocrine Society, Russian Endocrinology Association, the Russian Association for the Study of Obesity, and the World Health Organization (WHO). Results: The average care quality score improved significantly from 39 before implementation to 88 after six months of using the decision support system. Conclusions: The integration of decision support into EHRs is a highly effective tool for enhancing the quality of obesity care. It refines diagnosis, treatment, and overall management, demonstrating its potential to address gaps in obesity care across diverse healthcare settings in Russia. Presentation: Monday, July 14, 2025