Using Technology to Address Disparities and Promote Healthcare Equity in Type 1 Diabetes Registry

Not Applicable

Recruiting

• Conditions: Diabetes Mellitus, Type 1

• Registration Number: NCT06899984
• Lead Sponsor: University of Chicago

Brief Summary

This study is being done to see if using technology, with the help of a Patient Navigator, can help address disparities, improve outcomes, and promote healthcare equity in type 1 diabetes.

Detailed Description

Patients with T1D require an individualized care plan with ongoing education and support. A recent qualitative study of young adults with T1D and end-stage renal disease revealed that childhood environment, education, socio-economic status, and other determinants contributed to disengagement from treatment regimens and the development of microvascular complications early in life1. Providing participants with real-time CGMS will inform daily decision making.

This is an interventional study using prescribed real-time CGMS together with feedback and support from a Patient Navigator in patients with T1D. The aims of this study include the following.

Aim 1: To incorporate real-time CGMS and patient navigation support into the care of adolescent and adult patients with T1D and one of the following: 1.) two or more hospitalizations for DKA in the last five years or 2.) two or more hemoglobin A1c values over 10% in the last two years.

Aim 2: To collect information from participants regarding health outcomes, experiences with health care, and changes, if any, in diabetes self-management practices, diabetes distress, and diabetes health-related quality of life.

Study Timeline

• Study Start: 2020-11-20
• Status Verified: 2025-03
• Study First Submitted: 2025-03-11
• Study First Submitted QC: 2025-03-27
• Last Update Submitted: 2025-03-27
• Study First Posted: 2025-03-28
• Last Update Posted: 2025-03-28
• Primary Completion: 2026-06
• Study Completion: 2026-12

Recruitment & Eligibility

• Status: RECRUITING
• Sex: All
• Target Recruitment: 150

Inclusion Criteria

• Males or females age 14 to 64 years
• Clinical diagnosis of type 1 diabetes (T1D)
• Two or more hospitalizations with diabetic ketoacidosis (DKA) within the past 5 years or hemoglobin A1c greater than 10% on two or more laboratory samples in the last 2 years.
• Informed Consent
• Has a CGMS or a prescription for a CGMS as part of their clinical care as part of their clinical care

Exclusion Criteria

• Inability or unwillingness to share CGMS data with the study team

Study & Design

• Study Type: INTERVENTIONAL
• Study Design: SINGLE_GROUP

Primary Outcome Measures

Name	Time	Method
Change in CGM Utilization	Baseline to Month 48	Use of CGMS (Continuous Glucose Monitor) device measured by the percentage of time during a month that a participant is using their CGM.

Secondary Outcome Measures

Name	Time	Method
Change in diabetes health-related quality of life	Baseline to Month 48	Diabetes Quality of Life Brief Clinical Inventory (Possible range of scores is 15 to 75, with higher scores indicating a negative perspective of the problem's frequency and level of dissatisfaction) will be analyzed. Multilevel models using full information maximum likelihood estimation will be conducted to examine diabetes health-related quality of life changes over time.
Diabetes distress changes measured by PAID	Baseline to Month 48	PAID (scale; 0-4) (Possible range of scores is 0 to 100, with higher scores reflecting greater emotional distress) will be analyzed. Multilevel models using full information maximum likelihood estimation will be conducted to examine changes in diabetes distress in adults over time.
Diabetes distress changes measured by PAID-T	Baseline to Month 48	PAID-T(scale; 1-6) (Possible range of scores is 26-156, with higher scores indicating greater emotional distress) will be analyzed. Multilevel models using full information maximum likelihood estimation will be conducted to examine changes in diabetes distress in teens over time.
Change in diabetes self-management practices	Baseline to Month 48	SCI-R (scale; never to always) (For scoring, items are averaged and converted to a 0 to 100 point scale, with higher scores indicating higher levels of self-care) will be analyzed. Multilevel models using full information maximum likelihood estimation will be conducted to examine changes in diabetes self-management practices over time.

Trial Locations

Locations (1)

University of Chicago; 🇺🇸 Chicago, Illinois, United States