Related Experiment Video
Updated: Jun 4, 2026

Improving IV Insulin Administration in a Community Hospital
Published on: June 11, 2012
Modeling Glucose Homeostasis and Insulin Dosing in an Intensive Care Unit using Dynamic Bayesian Networks
Senthil K Nachimuthu1, Anthony Wong, Peter J Haug
1Department of Biomedical Informatics, University of Utah;
Abstract:
Adequate control of serum glucose in critically ill patients is a complex problem requiring continuous monitoring and intervention, which have a direct effect on clinical outcomes. Understanding temporal relationships can help to improve our knowledge of complex disease processes and their response to treatment. We discuss a Dynamic Bayesian Network (DBN) model that we created using the open-source Projeny toolkit to represent various clinical variables and the temporal and atemporal relationships underlying insulin and glucose homeostasis. We evaluated this model by comparing the DBN model's insulin dose predictions against those of a rule-based protocol (eProtocol-insulin) currently used in the ICU. The results suggest that the DBN model's predictions are as effective as or better than those of the rule-based protocol. The limitations of our methods are discussed, with a brief note on their generalizability.
Related Concept Videos
Glucose Homeostasis: Pancreatic Islets and Insulin Secretion
Insulin and C-peptide are co-secreted in...
Glucose Homeostasis: Regulation of Blood Glucose
During fasting, when blood glucose levels are low, the pancreas secretes glucagon. it...
Hypoglycemia and Glucagon
Hormones Regulating Blood Glucose
In addition to accelerating glucose uptake and utilization, insulin has...
Impact of Pharmacokinetic–Pharmacodynamic Models: Regulatory Decisions
SBAR II: Application of SBAR
SBAR Report from a Nurse to a Health Care Provider
S: "Hello, Dr. Smith. This is Jane, RN, from the Med Surg unit. I am calling to tell you about Ms. White in Room 210, who is experiencing increased pain and redness at her incision site. Her recent...

