Technological Advances in Glucose Management in Older Adults
Status: | Recruiting |
---|---|
Conditions: | Endocrine, Diabetes, Diabetes |
Therapuetic Areas: | Endocrinology |
Healthy: | No |
Age Range: | 65 - Any |
Updated: | 8/19/2018 |
Start Date: | March 30, 2017 |
End Date: | January 1, 2022 |
Contact: | Christine Slyne |
Email: | christine.slyne@joslin.harvard.edu |
Phone: | 617-309-4683 |
This is a study to assess the effectiveness of CGM (Continuous Glucose Monitor), enhanced by
a diabetes management platform (DMP), collectively called enhanced CGM (eCGM), in the care of
older patients with T1D. The DMP includes an automated data transfer from CGM,
insulin-delivery devices, and activity tracker to a clinical decision support system (CDS)
that provides dosing adjustment recommendations based on that data to the healthcare team. In
addition, the DMP includes on-demand education for patients and caregivers, and an interface
for communication between providers, patients, and their caregivers.
a diabetes management platform (DMP), collectively called enhanced CGM (eCGM), in the care of
older patients with T1D. The DMP includes an automated data transfer from CGM,
insulin-delivery devices, and activity tracker to a clinical decision support system (CDS)
that provides dosing adjustment recommendations based on that data to the healthcare team. In
addition, the DMP includes on-demand education for patients and caregivers, and an interface
for communication between providers, patients, and their caregivers.
Hypoglycemia is a major and often devastating complication of T1D in the elderly. CGM has
been shown to reduce the risk for hypoglycemia in adults with T1D including some more
functional patients over 65 years old. However, the Medicare population is heterogeneous and
may have age-related clinical and functional impairments that can impact self-care. These
patients will require additional targeted guidance and support to fully realize the potential
benefits of CGM. To address these age-specific barriers which could limit the effective use
of CGM, in our planned RCT (Specific Aim 1) the use of CGM will be coupled with the DMP
(Diabetes Management Platform), a tablet-based technology platform ( termed enhanced CGM
(eCGM)). The CGM, insulin delivery, and activity data uploaded from the DMP will be analyzed
by the clinical decision support system (CDS), which will provide insulin dosing
recommendations to the study physicians, who will then accept or reject changes in therapy.
The use of the DMP is expected to help the less technologically proficient Medicare patients
to derive benefit from CGM. Specific Aim 2 will involve extensive mixed methods research
(including semi-structured interviews of patients and caregivers) directed at making an
in-depth assessment of barriers to the use of diabetes technology in older adults. This
investigation will provide the evidence-base for future improvements in both the technology
and clinical approach to the training of older adults and their caregivers. Specific Aim 3
will involve a cost-effectiveness analysis of the technology system (CGM with DMP = enhanced
CGM [eCGM]) used in the trial as well as quality of life measures, providing a foundation for
decision-making on coverage.
been shown to reduce the risk for hypoglycemia in adults with T1D including some more
functional patients over 65 years old. However, the Medicare population is heterogeneous and
may have age-related clinical and functional impairments that can impact self-care. These
patients will require additional targeted guidance and support to fully realize the potential
benefits of CGM. To address these age-specific barriers which could limit the effective use
of CGM, in our planned RCT (Specific Aim 1) the use of CGM will be coupled with the DMP
(Diabetes Management Platform), a tablet-based technology platform ( termed enhanced CGM
(eCGM)). The CGM, insulin delivery, and activity data uploaded from the DMP will be analyzed
by the clinical decision support system (CDS), which will provide insulin dosing
recommendations to the study physicians, who will then accept or reject changes in therapy.
The use of the DMP is expected to help the less technologically proficient Medicare patients
to derive benefit from CGM. Specific Aim 2 will involve extensive mixed methods research
(including semi-structured interviews of patients and caregivers) directed at making an
in-depth assessment of barriers to the use of diabetes technology in older adults. This
investigation will provide the evidence-base for future improvements in both the technology
and clinical approach to the training of older adults and their caregivers. Specific Aim 3
will involve a cost-effectiveness analysis of the technology system (CGM with DMP = enhanced
CGM [eCGM]) used in the trial as well as quality of life measures, providing a foundation for
decision-making on coverage.
Inclusion Criteria:
- Patients with age ≥ 65 years
- Community-living
- Clinical diagnosis of T1D
- On multiple insulin injections (≥3 injection/s day) or insulin pump.
Exclusion Criteria:
- Use of real-time CGM in past 2 years
- A1c > 10% (since individuals with very poor glycemic control usually have barriers to
optimal self-care that preclude effective use of technology)
- Use of insulin pump that cannot be uploaded for CDS
- Unable or unwilling to perform task needed for study participation during the run-in
period
- Severe vision or hearing impairment that could interfere with study tasks
- Need to use acetaminophen on regular basis (since can interfere with CGM accuracy)
- Living in an institutional setting (e.g. group homes, nursing homes)
- Terminal diseases with life expectancy < 1 year (e.g. malignancy)
- Severe comorbidities that prevent completing outcome measurements (e.g. severe
dementia, severe vision impairment, severe functional disabilities, inability to
perform basic activities of daily living)
- Alcohol or other drug abuse
- Conditions that impact wear of CGM (e.g. CHF with edema, skin conditions); and
- End stage renal insufficiency (eGFR<30), or on dialysis (since impact of fluid shift
on sensor lag not clearly understood).
We found this trial at
1
site
One Joslin Place
Boston, Massachusetts 02215
Boston, Massachusetts 02215
617-309-2400
Principal Investigator: Medha N Munshi, MD
Phone: 617-632-8676
Joslin Diabetes Center Joslin Diabetes Center, located in Boston, Massachusetts, is the world's largest diabetes...
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