Clinical Decision Support With Continuous Glucose Monitoring Data for Managing Type 2 Diabetes
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- The protocol lists: Continuous Glucose Monitoring Clinical Decision Support.
- Who it may be relevant to
- Registry conditions: Type 2 Diabetes. Basic parameters: 18 years — 75 years · All.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- United States
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
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Official title
Translating Continuous Glucose Monitoring (CGM) Data Into Action to Improve Management of Insulin-Treated T2D in Primary Care
Overview
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.
Detailed 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.
Interventions
- Other Continuous Glucose Monitoring Clinical Decision Support
Retrospective CGM data is combined with a readily available EHR-based smart order set tool to assist with guidance and decision support for participants with type 2 diabetes on insulin.
Primary outcome measures
- Change in % glucose management indicator (GMI%) [Time frame: From baseline to 6 months]
Secondary outcome measures (2)
- Change in % time in range (TIR%) [Time frame: From baseline to 6 months]
- Change in % time below range (TBR%) [Time frame: From baseline to 6 months]
Eligibility criteria
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
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Healthy volunteers: No
Study design
- Observational model
- Case-only
Study locations
United States · 1 center
- HealthPartners Medical Group — Minneapolis
Publications
- Simonson GD, Martens TW, Carlson AL, Bergenstal RM. Primary Care and Diabetes Technologies and Treatments. Diabetes Technol Ther. 2025 Mar;27(S1):S141-S156. doi: 10.1089/dia.2025.8810.gds. No abstract available. PMID 40094500
- Martens TW, Simonson GD, Bergenstal RM. Using continuous glucose monitoring data in daily clinical practice. Cleve Clin J Med. 2024 Oct 1;91(10):611-620. doi: 10.3949/ccjm.91a.23090. PMID 39353661
- Martens TW. Roadmap to the Effective Use of Continuous Glucose Monitoring in Primary Care. Diabetes Spectr. 2023 Fall;36(4):306-314. doi: 10.2337/dsi23-0001. Epub 2023 Nov 15. PMID 37982066
- Martens T, Beck RW, Bailey R, Ruedy KJ, Calhoun P, Peters AL, Pop-Busui R, Philis-Tsimikas A, Bao S, Umpierrez G, Davis G, Kruger D, Bhargava A, Young L, McGill JB, Aleppo G, Nguyen QT, Orozco I, Biggs W, Lucas KJ, Polonsky WH, Buse JB, Price D, Bergenstal RM; MOBILE Study Group. Effect of Continuous Glucose Monitoring on Glycemic Control in Patients With Type 2 Diabetes Treated With Basal Insulin PMID 34077499
- Beck RW, Riddlesworth TD, Ruedy K, Ahmann A, Haller S, Kruger D, McGill JB, Polonsky W, Price D, Aronoff S, Aronson R, Toschi E, Kollman C, Bergenstal R; DIAMOND Study Group. Continuous Glucose Monitoring Versus Usual Care in Patients With Type 2 Diabetes Receiving Multiple Daily Insulin Injections: A Randomized Trial. Ann Intern Med. 2017 Sep 19;167(6):365-374. doi: 10.7326/M16-2855. Epub 2017 Au PMID 28828487
- Rodriguez P, San Martin VT, Pantalone KM. Therapeutic Inertia in the Management of Type 2 Diabetes: A Narrative Review. Diabetes Ther. 2024 Mar;15(3):567-583. doi: 10.1007/s13300-024-01530-9. Epub 2024 Jan 25. PMID 38272993
- Okemah J, Peng J, Quinones M. Addressing Clinical Inertia in Type 2 Diabetes Mellitus: A Review. Adv Ther. 2018 Nov;35(11):1735-1745. doi: 10.1007/s12325-018-0819-5. Epub 2018 Oct 29. PMID 30374807
- Fang M, Wang D, Coresh J, Selvin E. Trends in Diabetes Treatment and Control in U.S. Adults, 1999-2018. N Engl J Med. 2021 Jun 10;384(23):2219-2228. doi: 10.1056/NEJMsa2032271. PMID 34107181
Identifiers
NCT: NCT07394075 · 25-011 · 7-25-ICTSPC-413