Scripps Digital Diabetes: Cloud-Based Continuous Glucose Monitoring (CB CGM)
Scripps Digital Diabetes: Cloud-Based Continuous Glucose Monitoring (CB CGM)
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.
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.
Inclusion Criteria:
Exclusion Criteria: