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Abstract Number: 0116
MACHINE LEARNING-BASED PREDICTION OF HYPERGLYCEMIA IN HOSPITALIZED PATIENTS WITH DIABETES: AN EIGHT-YEAR STUDY OF EHR RECORDS ACROSS 19 HOSPITAL SITES
SHM Converge 2025
Background: Individuals with diabetes have a 2–3 fold higher hospitalization rate compared to those without diabetes. During hospitalization, individuals with diabetes frequently experience elevated blood glucose levels (or, hyperglycemia) (1), which can increase monitoring by nurses and hospitalists, length of stay, and healthcare cost. Therefore, we sought to develop a machine learning model to predict [...]
Abstract Number: 0164
PREDICTING HYPOGLYCEMIA USING MACHINE LEARNING IN HOSPITALIZED PATIENTS WITH DIABETES: A LARGE-SCALE STUDY ACROSS 19 HOSPITALS (2017-2024)
SHM Converge 2025
Background: Hypoglycemia occurs frequently in hospitalized adults with diabetes, and is associated with adverse clinical events, increased use of rapid response teams, prolonged hospital length of stay, and higher healthcare costs (1). Identifying risk of hypoglycemia in hospitalized adults is vital to preventing adverse events and maximizing patient safety. However, there are no tools/models to [...]
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