Scripps Digital Diabetes: Cloud-Based Continuous Glucose Monitoring (CB CGM)

Study Overview
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Brief Summary
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Individuals with diabetes in the hospital often experience poor glycemic control, which places them at greater risk for infection, neurological and cardiac complications, mortality, longer lengths of stay, readmissions, and higher healthcare costs. There are few effective interventions for monitoring hospital glucose management therefore the long-term goal of developing Cloud-Based Real-Time Glucose Evaluation and Management System is to provide an effective, real-time continuous glucose monitoring solution necessary for clinical decision-making which can be easily managed for clinical risk 24 hrs/day. The innovative intervention will enable hospital care teams to take immediate steps based on wireless transmission of glucose data from the Dexcom G6 device, sent to a Digital Dashboard, where integration with existing real-world hospital processes can provide immediate prioritization to prevent or correct impending hypoglycemia and severe hyperglycemic events. This randomized controlled trial is defined as a Phase III/IV definitive clinical trial to establish efficacy and effectiveness of this intervention. Aim 1 will assess mean differences of % time in range between intervention and Usual Care groups to find occurrence of glucose levels that are in range at 70-200mg/dL. Aim 2 will apply the same method, using % time above range of >300mg/dL (severe hyperglycemia) and % time below range <70mg/dL (hypoglycemia). Poor glycemic control in the hospital is common and given the known consequences of uncontrolled blood sugars during a hospitalization, health systems devote significant resources to developing protocols for improving glucometrics. The likely impact of this innovative research is to have an efficient, and seamless alternative for continually monitoring glucose levels in the hospital. The Digital Dashboard facilitates real-time, remote monitoring of a large volume of patients simultaneously; automatically identifies and prioritizes patients for intervention; and will detect any and all potentially dangerous hypoglycemic episodes. The work proposed pushes the limits of these challenges by providing evidence, identified by a team-based approach to glucose management in an underserved and understudied population supplementing prior data designed to improve outcomes among high-risk patients with type 2 diabetes (T2D) and related cardio metabolic conditions. The proposed intervention is flexible, sustainable, and has high dissemination potential.

Detailed Description
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This research study is designed to address these gaps by directly comparing the values of non-blinded, real-time and remotely monitored CGM data versus standard POC testing for hospital-based glucose management. Specifically, the investigators will investigate Cloud-Based Continuous Glucose Monitoring (CB CGM) versus standard POC testing (Usual Care; UC) in increasing % time-in-range (70-200 mg/dL), and in decreasing % time in hypoglycemia (<70 mg/dL) and severe hyperglycemia (>300 mg/dL) among N=300 adults with T2D. Patients will be enrolled at Scripps Mercy Hospital San Diego, Definitive Observation Unit (DOU) located in Hillcrest. This hospital serves predominantly low income, underinsured, ethnic/racial minority population in San Diego, California (CA). Participants will be randomized either to intervention or UC using a 4:1 ratio. All participants will have a CGM inserted upon enrollment. For the UC group, CGM data will be blinded and used for evaluation only; glucose will be monitored via the hospital's standard point-of-care (POC) testing protocol. For the intervention group, CGM data will be non-blinded and transmitted to a HIPAA-compliant Digital Dashboard, which filters and prioritizes patients by clinical risk (algorithm-based) using real-time CGM data. The Digital Dashboard will be monitored 24-hours/day by site-based telemetry teams for hyper- and hypoglycemic episodes that need rapid management per protocol. A centrally-located, Diabetes Advanced Practice Nurse (APN) will also remotely monitor glucose trends on the Digital Dashboard and recommend daily insulin adjustments to optimize the therapeutic regimen. Electronic medical records (EMR) will be used to identify eligible patients, and to compare exploratory outcomes (infection rate, LOS, healthcare costs, readmissions) between intervention and usual care. Aim 1: To evaluate the effectiveness of CB CGM versus UC in increasing % time-in-range (70-200 mg/dL). Aim 2: To evaluate the effectiveness of CB CGM versus UC in decreasing % time in hypoglycemia (<70 mg/dL) and severe hyperglycemia (>300 mg/dL). Aim 3: To document the differences between CB CGM and UC in outcomes commonly affected by glycemic control in the hospital (infection rates, LOS, cost, 30-day hospital readmissions). Process Aim: To evaluate feasibility, acceptability, sustainability, and scaling potential of CB CGM from patient, nursing, and physician perspectives.

Official Title
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Scripps Digital Diabetes: Cloud-Based Continuous Glucose Monitoring (CB CGM)

Conditions
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Diabetes Mellitus, Type 2

Intervention / Treatment
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* Device: Cloud-Based Continuous Glucose Monitoring


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: ≥ 18 years of age English or Spanish speaker ≥ one of the following: diagnosis of type 2 diabetes documented in the EMR, or use of anti-hyperglycemic agent documented in the EMR, or serum or POC glucose > 200 mg/dL in the first 24 hours of admission Exclusion Criteria: Anticipated LOS < 24 hours Current or anticipated ICU placement Does not speak English or Spanish Known adhesive allergy Current participation in medication or device study Pregnant Any other condition that the PI Dr. Philis-Tsimikas or the attending physician deem contraindicated

Ages Eligible for Study
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Minimum Age: 18 Years
Maximum Age: 100 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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Design Details

Primary Purpose: Treatment
Allocation: Randomized
Intervention Model: Parallel Assignment
Interventional Model Description: This is a parallel groups, randomized controlled trial (RCT) utilizing a 4:1 (Intervention: UC) ratio. This design was selected to maximize the number of Scripps patients receiving the CB CGM intervention, while also ensuring an adequate and representative UC group for comparison purposes.
Masking: Single


Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Experimental: Intervention CB CGM<br>On CB CGM patients, CGM data will also be transmitted from the bedside smartphone to the Digital Dashboard. The Digital Dashboard will integrate CGM data for CB CGM's participants for presentation via two views: (1) Real-Time Management and (2) Clinical Optimization. Telemetry technicians to conduct site-based monitoring, and the Diabetes APN will conduct remote management of patients at the site from a central, Scripps Diabetes Hub, per below. (Note, as CGMs are not FDA-approved for in-hospital glucose management, CB CGM participants will also have their glucose monitored via the hospital's standard POC testing protocol described for UC). | Device: Cloud-Based Continuous Glucose Monitoring<br>* The CGM data will be transmitted via bluetooth to a smartphone. The smartphone will automatically transmit values to a secure cloud-based platform, which then populates to the: (1) web-based, CGM data management tool for evaluation purposes (both groups), and (2) Digital Dashboard for monitoring and intervention (intervention only).<br>|
| No Intervention: Usual Care<br>For UC, CGM data will be blinded to the care team and used for evaluation purposes only. Glucose will be monitored via the hospital's standard POC testing protocol (i.e., prior to meals and at bedtime for patients who are eating, and every 4-6 waking hours for patients who are not eating). Glucose management in UC is designed to minimize differences between groups, aside from CGM monitoring: UC (and intervention) participants' glucose levels will be managed using the glucose management protocol and the Diabetes APN will assess UC participants' POC data documented in the EMR from the previous 24-48 hours and make recommendations for changes to the basal/bolus regimen to improve glucose management. | |

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Percentage time-in-range of interstitial glucose values | Percentage time-in-range (70-200 mg/dL) of interstitial glucose values | Through duration of index hospitalization, an average of 3 days | 
| Percentage time in hypoglycemia of interstitial glucose values | Percentage time in hypoglycemia (<70 mg/dL) of interstitial glucose values | Through duration of index hospitalization, an average of 3 days | 
| Percentage time in severe hyperglycemia of interstitial glucose values | Percentage time in severe hyperglycemia (>300 mg/dL) of interstitial glucose values | Through duration of index hospitalization, an average of 3 days | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Infection rates | Infection rates in hospital | Through duration of index hospitalization, an average of 3 days | 
| Length of stay (LOS) | Length of stay in hospital | Through duration of index hospitalization, an average of 3 days | 
| Cost of hospitalization | Healthcare costs associated with stay in hospital | Through duration of index hospitalization, an average of 3 days | 
| Hospital readmission rate | Readmission to hospital within 30-days post-discharge | 30 days from the discharge date of the index hospitalization | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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Diabetes, Continuous Glucose Monitor, Blood Glucose, Cost-Effectiveness, Hospital, Diabetes Management, Technology, Remote Monitoring, Digital Dashboard, Cloud-Based, Hypoglycemia, Hyperglycemia, Real-Time, Clinical Decision-Making, Wireless Transmission