Novel Automated Self-adjusting Subcutaneous Insulin Algorithm Improves Glycemic Control and Physician Efficiency in...

Area of Science:

• Clinical Medicine
• Medical Technology
• Endocrinology

Background:

• Hyperglycemia is prevalent in hospitalized patients, negatively impacting outcomes like mortality and hospital costs.
• Inpatient glycemic control is difficult due to factors like variable nutrition, acute illness, and labor-intensive monitoring.
• Effective management of blood glucose levels in hospitals remains a significant clinical challenge.

Purpose of the Study:

• To compare the efficacy and safety of a novel automated subcutaneous insulin algorithm (SQIA) against conventional physician-driven insulin dosing.
• To evaluate the impact of the SQIA on glycemic control and physician efficiency in hospitalized patients.
• To assess the reduction in severe hyperglycemia and hypoglycemia events with automated insulin management.

Main Methods:

• A retrospective cross-sectional analysis was performed at UCSF hospitals from September 2020 to September 2021.
• Point-of-care glucose measurements were compared between patients on SQIA and conventional insulin dosing.
• Physician efficiency was assessed by tracking the number of insulin orders placed or modified.

Main Results:

• The SQIA group showed a trend towards a higher proportion of glucose in range (71.0% vs 69.0%).
• SQIA significantly reduced severe hyperglycemia (5.8% vs 7.2%), hypoglycemia (0.8% vs 1.2%), and severe hypoglycemia (0.3% vs 0.5%).
• Physician order modifications decreased by over 12-fold with the SQIA compared to conventional dosing.

Conclusions:

• The automated subcutaneous insulin algorithm (SQIA) effectively reduced severe hyperglycemia and hypoglycemia in hospitalized patients.
• SQIA demonstrated improved patient safety by minimizing dangerous glucose fluctuations.
• The algorithm significantly enhanced physician efficiency, reducing the burden of insulin order management.