Summary:
Managing blood sugar levels in hospitalized patients with complex dietary restrictions is a persistent challenge. These patients, who may be unable to eat normally due to conditions like surgery or illness, often experience hyperglycemia, a condition that affects between 25% and 50% of such individuals. This is particularly problematic for those with pre-existing diabetes, where uncontrolled blood sugar can lead to severe complications.
Dr. Robert J. Rushakoff, an endocrinologist at UCSF Health, has developed a groundbreaking solution to address this issue: the Self-Adjusting Subcutaneous Insulin Algorithm (SQIA). Integrated into the electronic medical record system, the SQIA automates the calculation of insulin doses for patients in three dietary categories: nothing by mouth (NPO), continuous tube feeds (TF), and total parenteral nutrition (TPN).
During the first three years of its full implementation, the SQIA has shown a reduction in severe hyperglycemia rates without increasing hypoglycemia, especially in patients receiving NPO and TPN diets. Unlike conventional methods where physicians manually adjust insulin doses, the SQIA allows for automatic dose adjustments based on real-time blood sugar readings and prior insulin administration. This automation has dramatically reduced the incidence of severe hyperglycemia and hypoglycemia, and has shortened hospital stays for many patients.
As UCSF Health continues to refine and expand these technologies, the SQIA has become the primary method for insulin administration in their hospitals, selected by physicians for about 80% of eligible patients.
Article written by Hospi Medica
25/06/2024
Source:
Hospi Medica
https://www.hospimedica.com/critical-care/articles/294801645/ai-automatically-determines-insulin-dosing-for-improved-blood-sugar-control-in-hospitalized-patients.html