Development and Validation of a Machine Learning Model to Predict Near-Term Risk of Iatrogenic Hypoglycemia in Hospitalized Patients

Abstract

Inpatient hypoglycemia is a prevalent and often preventable adverse event associated with increased morbidity and mortality, length of stay, readmissions, and health care expenditures.^1-6 Considering that most patients with diabetes are hospitalized for reasons other than glucose management,^7,8 situational unawareness of the near-term risk of iatrogenic hypoglycemia may result from competing medical priorities, lack of sufficient training in glycemic pattern recognition,^9-11 or other system factors.¹² Studies^13-15 have demonstrated practitioner inertia in adjusting glucose-lowering medications before hypoglycemic events or in response to antecedent hypoglycemia.