Dr.Yi-JingSheen Taiwan

Dr.Yi-JingSheen
Dr. Yi-Jing Sheen is an attending physician in the Division of Endocrinology and Metabolism at Taichung Veterans General Hospital (TCVGH), Taiwan, and an Adjunct Associate Professor in the Department of Internal Medicine at National Yang Ming Chiao Tung University. A clinician-scientist with more than two decades of experience in endocrine and metabolic medicine, she specializes in diabetes, thyroid disorders, geriatric endocrinology, and chronic metabolic diseases. Dr. Sheen earned her medical degree from China Medical University and subsequently completed a Master’s degree in Health Care Administration and a Ph.D. in Public Health at the same institution. Her clinical training was carried out at China Medical University Hospital and Taichung Hospital, Ministry of Health and Welfare, before she joined TCVGH as a research physician and later as an attending endocrinologist. She has also held key educational leadership roles, including Deputy Director of the Department of Medical Education and Director of the Post-Graduate Year (PGY) General Medicine Training Program at TCVGH. Dr. Sheen’s recent research program centers on precision diabetes care, with emphasis on hospital-wide inpatient glycemic management, early detection and risk stratification of diabetic peripheral neuropathy and diabetic retinopathy, and young-onset diabetes driven by monogenic and digenic etiologies, including MODY. Her work integrates cutting-edge diagnostic technologies—particularly short-wave infrared hyperspectral imaging—to enhance early identification of microvascular complications. In parallel, she employs large-scale clinical datasets to refine individualized metabolic care pathways. Her publications in Clinical Therapeutics, Journal of Biophotonics, and other peer-reviewed journals highlight her commitment to improving diagnostic accuracy and advancing personalized therapeutic strategies for high-risk and underserved populations. Through her clinical expertise, academic leadership, and ongoing innovation in diabetes technology and precision phenotyping, Dr. Sheen continues to advance high-quality, patient-centered metabolic care in Taiwan.

20 MARCH

Time Session
13:50
15:20
[Symposium] Artificial Intelligence and Precision Medicine (1)
AI in Endocrinology
  • Advancement in AI Applications to Thyroid Nodule Detection and Diagnosis
    Argon ChenTaiwan Speaker Advancement in AI Applications to Thyroid Nodule Detection and Diagnosis
  • Electronic Dashboard-Based Remote Glycemic Management Program Reduces Length of Stay and Readmission Rate among Hospitalized Adults
    Yi-Jing ShenTaiwan Speaker Electronic Dashboard-Based Remote Glycemic Management Program Reduces Length of Stay and Readmission Rate among Hospitalized AdultsBackground: Inpatient dysglycemia is strongly associated with prolonged length of stay (LOS), increased readmission rates, and higher healthcare costs. Traditional consultation-based models are often insufficient for institution-wide glycemic quality improvement. With advances in electronic medical records (EMRs), real-time digital surveillance offers a scalable solution. We implemented a hospital-wide remote glycemic management program to evaluate its impact on glycemic control and clinical outcomes. Methods: Building on our previously published framework, this institution-wide before-and-after study was conducted in a 1,500-bed tertiary medical center using data from 2016 to 2019 (106,528 hospitalized adults; 878,159 glucose measurements). The core intervention utilized an EMR-integrated dashboard to identify hyper-/hypoglycemia in real-time, enabling endocrinologists to provide daily virtual recommendations without formal consultation. Key components included automated risk stratification, real-time alerts, and department-specific performance feedback. Primary outcomes were LOS and 30-day readmission rates. Analyses were performed using Poisson and joinpoint regression with multivariable adjustment. Results: Program implementation resulted in consistent and clinically significant improvements in hospital-wide glycemic metrics. Rapid improvement in treat-to-target rates was observed within 3–6 months of initiating virtual recommendations. Clinical Outcomes: The program was associated with a significant reduction in LOS, independent of age, sex, and admission department. Notably, patients with high glucose variability exhibited the longest LOS, identifying glycemic instability as a key driver of resource utilization. Furthermore, 30-day readmission rates decreased significantly, particularly among patients achieving stable euglycemia. Operational Efficiency & Pandemic Resilience: As glycemic quality improved, the time required for daily virtual recommendations decreased from ~2 hours to <1 hour. The program significantly reduced the need for formal consultations. Crucially, this established remote workflow proved vital during the COVID-19 pandemic, minimizing clinician exposure and preserving personal protective equipment (PPE) while maintaining high-quality glycemic care without disruption. Conclusion: Integrating real-time EMR-based surveillance with remote endocrinologist-led intervention significantly improves inpatient glycemic control, translating into measurable reductions in LOS and 30-day readmission rates. This model has demonstrated sustained efficacy extending into the COVID-19 era and beyond, proving that an electronic dashboard-based system is a scalable, resilient, and resource-efficient strategy for modern hospital care.
  • A New Era of Managing Thyroid Eye Disease
    Jae Hoon MoonSouth Korea Speaker A New Era of Managing Thyroid Eye Disease
201DE