Clinical Decision Support With Continuous Glucose Monitoring Data for Managing Type 2 Diabetes (TRACTION-PC)

HealthPartners Institute

Status: Invitation-only

Conditions: Type 2 Diabetes

Treatments: Other: Continuous Glucose Monitoring Clinical Decision Support

Study type: Observational

Funder types: Other

Identifiers

NCT07394075

7-25-ICTSPC-413 (Other Grant/Funding Number)

25-011

Details and patient eligibility

About

The goal of this project is to see if an electronic health record (EHR)-based smart order set with continuous glucose monitoring data to provide decision support can improve blood sugar management in people with type 2 diabetes (T2D) using insulin.

Full description

Develop and test an electronic health record (EHR)-based smart order set to provide decision support by combining retrospective CGM data and a novel tool called Clinician CGM Guided Management (CCGM) that incorporates elements of the American Diabetes Association/European Association for the Study of Diabetes (ADA/EASD) Algorithm and established principles of insulin titration in T2D to improve glycemic management in people with T2D using insulin who are managed in primary care.

A current quality improvement (QI) project within the care system will improve CGM data access to primary care providers (PCPs) through cloud-based and EHR resources, to enhance data availability at the time of clinical interactions. This care system integration QI project will generate an order set to help clinicians order CGM devices, consolidate clinic cloud access portals, create care pathways to optimize availability of CGM data at the time of clinical interactions. While this quality improvement project will improve the ease of initiating CGM devices and obtaining CGM data organizationally, for this research project an enhanced, smart order set (CGM-SOS) will be created to supplement the existing order set and will be available to study clinics to help with decision support regarding management of non-insulin and insulin therapies for individuals managed at the clinics involved in this research project. By integrating CGM-based decision support directly into the EHR setting, the hope is to dramatically improve the accessibility of guidance regarding medication in insulin management for PCPs involved in this project.

The availability of CGM data allows for rapid evaluation and adjustment of therapies, which provides an opportunity for improvement in "cycle time" in titration of medications. Based on a cadence of clinical visits every 2-4 weeks for individuals not meeting glycemic goals, a six-month study timeframe should allow adequate time for optimization of glycemic therapies in T2D. Additionally, significant glycemic improvement in this timeframe would improve upon current practices in primary care settings, in which intensification and advancement of therapies can often be delayed for months or years because of issues related to care delivery in primary care settings.

Enrollment: 150 estimated patients

Sex: All

Ages: 18 to 75 years old

Volunteers: No Healthy Volunteers

Inclusion criteria

• Type 2 diabetes
• A1c greater than 7.5%
• On insulin therapy
• Use CGM for glycemic monitoring

Exclusion criteria

• Pregnancy
• Use of insulin pump or automated insulin delivery system
• Active cancer (other than nonmelanoma skin cancer or low-grade prostate cancer being followed with observation)
• Cognitive barriers requiring assistance of a surrogate or caregiver for insulin management