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.
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 Type
INTERVENTIONAL
Allocation
NA
Purpose
PREVENTION
Masking
NONE
Enrollment
150
Patient Navigator will provide additional support to participants using their standard of care CGM device.
University of Chicago
Chicago, Illinois, United States
Change in CGM Utilization
Use of CGMS (Continuous Glucose Monitor) device measured by the percentage of time during a month that a participant is using their CGM.
Time frame: Baseline to Month 48
Change in diabetes health-related quality of life
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.
Time frame: Baseline to Month 48
Diabetes distress changes measured by PAID
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.
Time frame: Baseline to Month 48
Diabetes distress changes measured by PAID-T
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.
Time frame: Baseline to Month 48
Change in diabetes self-management practices
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.
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Time frame: Baseline to Month 48