Dr. Jae Hoon Moon is a Professor of Endocrinology at Seoul National University Bundang Hospital and CTO & Co-founder of Thyroscope Inc., a digital-health company developing AI-powered solutions for thyroid diseases. He obtained his MD, MSc, and PhD from Yonsei University College of Medicine and completed his fellowship in endocrinology at Severance Hospital.
Dr. Moon’s research focuses on thyroid cancer, Graves’ disease, and the application of artificial intelligence and wearable data in endocrine disease management. He has authored more than 120 peer-reviewed publications. He previously served as a Professional Scientific Collaborator at the Scripps Research Translational Institute (Digital Medicine Team, CA, USA).
He is an active member of the Korean Endocrine Society, Korean Thyroid Association, and Korean Diabetes Association, and has received multiple national and international awards for his contributions to thyroid research and digital medicine.
20 MARCH
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Session |
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13:50
15:20
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AI in Endocrinology
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Argon ChenTaiwan
Speaker
Advancement in AI Applications to Thyroid Nodule Detection and Diagnosis
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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.
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201DE
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