CGM in Utah Valley

Diabetes Mellitus, Type 2 Clinical Trial

— CGM  

Official title:

Expanding Continuous CGM Usage to Improve Outcomes in a Shorter Duration in Utah Valley Clinics

Clinical Trial Details — Status: Not yet recruiting

Administrative data

• NCT number: NCT04313803
• Other study ID #: IHC IRB#: 1051315
• Status: Not yet recruiting
• Start date: April 1, 2020
• Est. completion date: April 30, 2021

Study information

• Verified date: March 2020
• Source: Intermountain Health Care, Inc.
• Contact: Elizabeth Joy, MD, MPH
• Phone: (801) 442-3721
• Email: liz.joy[@]imail.org
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

The purpose of this study is to replicate the positive impact observed in IRB #1050955, but conduct this over a shorter period to potentially maximize patient outcomes and make care more affordable. Intermountain intends to build a diabetes program with CGM based on the findings. Senior stakeholders, clinicians and operators are aligned on this vision including the Community Based Care triad, Executive Leadership Team, and our Diabetes Prevention Program.

Description:

Overview

Approximately 30 million Americans, or 9% of the population has diabetes, a condition in which a person does not make enough insulin, or the body cannot use its own to effectively manage blood glucose levels. Improper diabetes management is associated with severe comorbidities which include: heart disease, stroke, kidney disease, ocular problems, dental disease, nerve damage, and vascularity issues. The epidemic continues to challenge systems like Intermountain Healthcare, an accountable care organization (ACO), since diabetes cost $327 billion per year (representing $1 in every $7 dollars spent) on healthcare in the United States. Furthermore, people with diagnosed diabetes incur average medical expenditures of $16,752 per year, of which about $9,601 is directly attributed to diabetes. New treatment options are needed to manage population health, especially with 84 million adults having been diagnosed with prediabetes diabetes.

In an effort to reduce the physical, economic and social burden of diabetes, several healthcare systems have evaluated the use of telehealth to monitor glucose levels. In a previous metanalysis, the authors demonstrated that telehealth interventions produced a small, but significant improvement in hemoglobin A1c (HbA1c) levels compared with usual care (mean difference: -0.55, 95% CI: -0.73 to − 0.36). The Ontario Health Technology Advisory Committee also showed that the blood glucose home telemonitoring technologies they used yielded a statistically significant reduction in HbA1c of ~0.50% in comparison to usual care when used adjunctively to a broader telemedicine initiative for adults with type 2 diabetes.

1.2 Previous Work

Intermountain Healthcare conducted a pilot study in the Reimagine Primary Care (RPC) clinics to evaluate if six months of CGM could improve patient outcomes (IRB #1050955). A total of 99 patients remained enrolled for the full time period (n=50 CGM, n=49 standard of care (SOC)), and data showed a improvement in glucose levels, less primary care and specialty appointments, a reduction in emergency department (ED) encounters, less labs ordered, and a cumulative body mass index (BMI) improvement. Furthermore, nearly all participants reported being willing to engage in another future pilot, and the vast improvements were attributed to subjects use of real-time data.

Primary analyses

Cost of care for fee-for-value patients (specifically PMPM savings)

Secondary analyses

Frequency of hypoglycemic events, healthcare utilization per count of inpatient/outpatient visits, cost of care, current HEDIS performance on diabetes and behavioral health measures, coding specificity for diabetes, emergency department visit per 1000 rate, overall and for patients with diabetes.

Power analyses

Data from IRB #1050955 has shown significant changes in cost, care and utilization with only a sample of 50 CGM users. The effect size is currently being calculated by the study statistician, but most of the outcome variables comparing CGM to standard of care device were p<0.05. Given that this will now include a much larger population, and 30x participant increase, the investigators will have sufficient power to deduce differences should they occur.

Recruitment information / eligibility

• Status: Not yet recruiting
• Enrollment: 1500
• Est. completion date: April 30, 2021
• Est. primary completion date: October 30, 2020
• Accepts healthy volunteers: Accepts Healthy Volunteers
• Gender: All
• Age group: 18 Years to 80 Years

Eligibility

Inclusion Criteria:

• Patients (18-80 years of age) with type ll diabetes, having an HbA1c =6.5%, treated within five Intermountain Healthcare Utah Valley clinics. Patients must have access to a smart phone to download applications, have Bluetooth capabilities for data sharing, and log/view their continuous glucose monitor (CGM) data.

Exclusion Criteria:

• Patients who are pregnant, not classified as having diabetes based on A1c levels, and age = 17 or = 81 years, or diagnosis of dementia.

Related Conditions & MeSH terms

• Diabetes
• Diabetes Mellitus
• Diabetes Mellitus, Type 2

Intervention

Device:
• CGM
Dexcom CGM system

Locations

Country	Name	City	State
n/a

Sponsors (2)

Lead Sponsor	Collaborator
Intermountain Health Care, Inc.	DexCom, Inc.

References & Publications (4)

Ekhlaspour L, Mondesir D, Lautsch N, Balliro C, Hillard M, Magyar K, Radocchia LG, Esmaeili A, Sinha M, Russell SJ. Comparative Accuracy of 17 Point-of-Care Glucose Meters. J Diabetes Sci Technol. 2017 May;11(3):558-566. doi: 10.1177/1932296816672237. Epub 2016 Oct 3. — View Citation

Fong Y, Rue H, Wakefield J. Bayesian inference for generalized linear mixed models. Biostatistics. 2010 Jul;11(3):397-412. doi: 10.1093/biostatistics/kxp053. Epub 2009 Dec 4. — View Citation

Lee PA, Greenfield G, Pappas Y. The impact of telehealth remote patient monitoring on glycemic control in type 2 diabetes: a systematic review and meta-analysis of systematic reviews of randomised controlled trials. BMC Health Serv Res. 2018 Jun 26;18(1):495. doi: 10.1186/s12913-018-3274-8. — View Citation

Verkuilen J. Explanatory Item Response Models: A Generalized Linear and Nonlinear Approach by P. de Boeck and M. Wilson and Generalized Latent Variable Modeling: Multilevel, Longitudinal and Structural Equation Models by A. Skrondal and S. Rabe-Hesketh. Psychometrika. 2006 Jun;71(2):415-418. doi: 10.1007/s11336-005-1333-7. — View Citation

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Cost of care for fee-for-value patients (specifically PMPM savings)	For each patient, measure total variable cost of associated healthcare services and visits. Then compare the distribution of costs between randomized groups using the Wilcoxon rank-sum test, a non-parametric analogue of Student's t-test.	1 April 2020 - 30 April 2021
Secondary	The count of primary care, specialist, and emergency department visits or hospital stays for those using CGM compared to historical utilization and the broader T2DM cohort within Intermountain Healthcare.	Frequency of hypoglycemic events and healthcare utilization per count of inpatient/outpatient and emergency department visits per 1000 rate, overall and for patients with diabetes	1 April 2020 - 30 April 2021
Secondary	Evaluation of HEDIS performance for those using CGM compared to historical utilization and the broader T2DM cohort within Intermountain Healthcare.	Current HEDIS performance on diabetes and behavioral health measures	1 April 2020 - 30 April 2021