CGM in Utah Valley
CGM
Expanding Continuous CGM Usage to Improve Outcomes in a Shorter Duration in Utah Valley Clinics
1 other identifier
observational
1,500
0 countries
N/A
Brief 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.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for all trials
Started Apr 2020
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
First Submitted
Initial submission to the registry
March 13, 2020
CompletedFirst Posted
Study publicly available on registry
March 18, 2020
CompletedStudy Start
First participant enrolled
April 1, 2020
CompletedPrimary Completion
Last participant's last visit for primary outcome
October 30, 2020
CompletedStudy Completion
Last participant's last visit for all outcomes
April 30, 2021
CompletedMarch 18, 2020
March 1, 2020
7 months
March 13, 2020
March 17, 2020
Conditions
Keywords
Outcome Measures
Primary Outcomes (1)
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 Outcomes (2)
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.
1 April 2020 - 30 April 2021
Evaluation of HEDIS performance for those using CGM compared to historical utilization and the broader T2DM cohort within Intermountain Healthcare.
1 April 2020 - 30 April 2021
Study Arms (3)
American Fork
CGM usage months 1 and 3
Central Orem
CGM usage for month 1
North Canyon, Saratoga Springs, and Lehi
CGM usage for 1-3 months
Interventions
Eligibility Criteria
Patients with type II diabetes treated at Intermountain Healthcare
You may qualify if:
- 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.
You may not qualify if:
- Patients who are pregnant, not classified as having diabetes based on A1c levels, and age ≤ 17 or ≥ 81 years, or diagnosis of dementia.
Contact the study team to confirm eligibility.
Sponsors & Collaborators
- Intermountain Health Care, Inc.lead
- DexCom, Inc.collaborator
Related Publications (4)
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.
PMID: 29940936BACKGROUNDEkhlaspour 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.
PMID: 27697848BACKGROUNDVerkuilen 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. No abstract available.
PMID: 28197954BACKGROUNDFong 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.
PMID: 19966070BACKGROUND
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Study Officials
- PRINCIPAL INVESTIGATOR
Elizabeth Joy, MD, MPH
Intermountain Health Care, Inc.
- STUDY DIRECTOR
Brad Isaacson, PhD, MBA, MSF, PMP
Intermountain Health Care, Inc.
Central Study Contacts
Study Design
- Study Type
- observational
- Observational Model
- COHORT
- Time Perspective
- PROSPECTIVE
- Sponsor Type
- OTHER
- Responsible Party
- SPONSOR
Study Record Dates
First Submitted
March 13, 2020
First Posted
March 18, 2020
Study Start
April 1, 2020
Primary Completion
October 30, 2020
Study Completion
April 30, 2021
Last Updated
March 18, 2020
Record last verified: 2020-03
Data Sharing
- IPD Sharing
- Will not share