Continuous Glucose Monitoring for High-Risk Type 2 Diabetes in the Hospital (Cyber GEMS) (Cyber GEMS)

Continuous Glucose Monitoring for High-Risk Type 2 Diabetes in the Hospital: Cloud-Based Real-Time Glucose Evaluation and Management System (Cyber GEMS)

Given the known serious consequences of uncontrolled blood sugars during hospitalization, this research plans to study an alternative seamlessly integrated continuous glucose monitoring (CGM) system in the hospital to test a dynamic and digitized, team-based approach to glucose management in an underserved and understudied, yet high-risk population. A digital dashboard will facilitate real-time, remote monitoring of a large volume of patients simultaneously; automatically identify and prioritize patients for intervention; and will detect any and all potentially dangerous hypoglycemic episodes in a hospital environment. The study will focus on clinical metrics of glucose control and infection that are in-line with patient priorities and US hospital quality initiatives.

Study Overview

• Status: Completed
• Conditions: Type 2 Diabetes
• Intervention / Treatment: Device: Dexcom G6 Continous Glucose Monitoring Management; Device: Usual Care - Blinded Continuous Glucose Monitoring Management

Detailed Description

There is strong evidence that poor glycemic control in the hospital is common. Given the known consequences of uncontrolled blood sugars during a hospitalization (e.g., infection, serious neurological and cardiac complications, mortality, longer lengths of stay, readmissions, higher healthcare costs), health systems devote significant resources to developing protocols for improving glucometrics. Despite the widespread use and demonstrated effectiveness of continuous glucose monitoring (CGM) for ambulatory glucose management, CGMs is not routinely used in US hospitals. Therefore, the long-term goal to develop Cloud-Based Real-Time Glucose Evaluation and Management System (Cyber GEMS) is to provide an effective, real-time solution to augment existing processes, to provide a valuable test of real-world effectiveness, while capitalizing on standardized algorithms to facilitate sustainability and scalability to other systems and at-risk populations. The intervention will enable hospital care teams to take immediate steps based on the 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 study is a randomized controlled trial, defined as a Phase II/III definitive clinical trial that in turn establishes efficacy and effectiveness of this intervention. Aim 1 will establish the effectiveness of Cyber GEMS versus Usual Care (UC) in increasing the % time patients are in-range and decreasing % time in hypoglycemia and severe hyperglycemia during hospitalization. Aim 2 will evaluate the effectiveness of Cyber GEMS versus UC in decreasing hospital-acquired infection risk. A digital dashboard will facilitate real-time, wireless transmission of glucose data of a large volume of patients simultaneously; automatically identify and prioritize patients for intervention; and detect potentially dangerous hypoglycemic episodes - all at a reduced burden than current methods of stratification and review. The uninterrupted coverage, and efficient and remote diabetes specialist oversight in Cyber GEMS is a scalable, novel, team-based approach to maximize the use of continuously streaming CGM data for optimal glucose management.

• Study Type: Interventional
• Enrollment (Actual): 518
• Phase: Not Applicable

Contacts and Locations

Study Locations

• United States
  • California
    • Chula Vista, California, United States, 91910
      • Scripps Mercy Hospital

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years and older (Adult, Older Adult)
• Accepts Healthy Volunteers: No

Description

Inclusion Criteria:

• Documented previous or current Type 2 Diabetes (T2D) diagnosis as defined by either diagnosis in the chart or an HbA1c > or = to 6.5% in the last 90 days
• Either on subcutaneous (SQ) insulin orders, or greater than two serum or Point of Care (POC) glucose > or = 200 mg/dL in most recent 24 hours of admission

Exclusion Criteria:

• Anticipated length of stay < 24 hours;
• Current or anticipated ICU placement;
• Does not speak English or Spanish;
• Known allergy to adhesives;
• Current participation in any medication or device research study;
• Pregnant;
• Any other condition that Multiple Principal Investigator (MPI) Philis-Tsimikas or the attending physician deems contraindicated

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Treatment
• Allocation: Randomized
• Interventional Model: Parallel Assignment
• Masking: Single

Number of Arms

2

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Experimental: Continuous Glucose Monitoring; Research Assistants (RAs) will verbally administer baseline survey and insert Dexcom G6 CGM, before unveiling the group assignment. CGM data will be transmitted from bedside iPhone to web-based platforms for: (1) Real-Time Management (via iPad-based FOLLOW app used by bedside RN and Digital Dashboard used by remote monitoring team) and (2) Clinical Optimization (via CLARITY, a Diabetes RN Coordinator will conduct remote clinical management of patients from a central, Scripps Diabetes Hub). A post-CGM satisfaction survey will be administered and compensation provided when CGM is removed prior to discharge or within 2 weeks following discharge. The CGM readings will be used to make recommendations for insulin adjustment and glucose management. After discharge, CGM data will be downloaded from a HIPPA-compliant, web-based CGM data management tool, and saved in Excel. The Data Analyst, blinded to condition, will routinely screen CGM data and merge individual spreadsheets for analysis.	Device: Dexcom G6 Continous Glucose Monitoring Management; CGM data will be transmitted from the bedside iPhone to web-based platforms for: (1) Real-Time Management (via iPad-based FOLLOW app used by bedside RN and Digital Dashboard used by the remote monitoring team) and (2) Clinical Optimization (via CLARITY, by which a Diabetes RN Coordinator will conduct remote clinical management of patients from a central, Scripps Diabetes Hub.
Active Comparator: Usual Care; RAs will verbally administer a baseline survey and insert the Dexcom G6 CGM. before unveiling the group assignment. CGM data will be blinded 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 if not eating). Glucose management in UC is designed to minimize differences between groups, aside from CGM monitoring, A post-CGM satisfaction survey will be administered and compensation provided when the CGM is removed prior to discharge or within 2 weeks following discharge. After discharge, CGM data will be downloaded from a HIPPA-compliant, web-based CGM data management tool, and saved in individual Excel spreadsheets. The study Data Analyst, blinded to study condition, will routinely screen CGM data and merge individual spreadsheets for analysis.	Device: Usual Care - Blinded Continuous Glucose Monitoring Management; CGM data will be blinded 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 if not eating). Glucose management in UC is designed to minimize differences between groups, aside from CGM monitoring.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Percent time in range	Participants will have their percent time in range calculated following a minimum CGM data collection period of 12 hours and expressed as a percentage where: Percent Time in Range= 100 (Number readings in range (70-200mg/dL)/Total number of readings from CGM). Number of readings will be used in calculation, which scale directly with time.	Immediately following intervention completion
Percent time spent in hypoglycemia and percent time in severe hyperglycemia	Our second outcome will be assessed by the same methods as the first, but instead looking at Percent Time in Severe Hyperglycemic Range (>300mg/dL) and Percent Time in Hypoglycemic Range (<70mg/dL).	Immediately following intervention completion
Infection Rate	Rates of hospital-acquired infection are defined as skin wound or surgical site, central line-associated bloodstream infection, urinary tract infection, bacteremia, clostridium difficile infection, or pneumonia not present at admission. Unadjusted incidence rates among study participants will be compared between intervention and control groups via Chi-Square test of two proportions.	Immediately following intervention completion

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Glucose Variability	Using CGM data, glucose variability will be determined by first calculating the coefficient of variation for each participant, dividing the standard deviation of the glucose readings of that participant, by the mean of those readings and multiplying by 100 to get a percentage. Mean coefficients of variation will be compared between intervention and control groups by a students t test.	Immediately following intervention completion
Electronic Medical Record (EMR) - Derived Outcomes: HbA1C	Additional metrics of glycemic control will be captured for each study participant from the EMR including: HbA1C. Like primary outcome analyses, group mean differences of each variable will be assessed unadjusted with a students t-test utilized to detect between-group differences.	Immediately following intervention completion
Electronic Medical Record (EMR) - Derived Outcome: fasting POC blood glucose	Additional metrics of glycemic control will be captured for each study participant from the EMR including fasting point-of-care (POC) blood glucose measurements (mg/dL). Like primary outcome analyses, group mean differences of each variable will be assessed unadjusted with a students t-test utilized to detect between-group differences.	Immediately following intervention completion

Other Outcome Measures

Outcome Measure	Measure Description	Time Frame
Process Indicators (Reach): Enrollment Characteristics	To examine enrollment rate, demographic characteristics of eligible patients will be compared between those who enroll versus decline; where continuous measures will be compared between groups will be compared between groups by Chi-Square tests.	Immediately following intervention completion
Process Indicators (Reach): Representative Characteristics	To examine generalizability of our sample, distribution of demographics in our sample will be compared to expected distributions of our target population through Chi-square tests.	Immediately following intervention completion
Process Indicators (Reach): CGM wear time	Median time on CGM will also be compared between Cyber GEMs and UC groups using a Mann-Whitney test.	Immediately following intervention completion
Process Indicators (Reach): Withdrawal rate	We do not plan to statistically assess reasons for withdrawal due to an anticipated low number of withdrawals, but all reasons will be recorded and descriptively quantified where applicable.	Immediately following intervention completion
Process Indicators (Efficacy): Impact of time on CGM	A generalized linear model will be used to assess whether time on CGM relates to changes in the percent time in primary and secondary outcome ranges over time.	Immediately following intervention completion
Process Indicators (Efficacy): Negative outcomes	Unintended negative outcomes will be recorded and descriptively analyzed.	Immediately following intervention completion
Process Indicators (Adoption): Perceptions of CGM	Results of semi-structured interviews will be qualitatively, descriptively analyzed to reveal perceptions of CGM implementation efficacy, challenges, satisfaction, and benefits.	Immediately following intervention completion
Process Indicators (Adoption): Clinical perceptions of glucose management	Descriptively assess physicians pre- and post study perceptions and knowledge of and identified barriers to successful inpatient glucose control via the Inpatient Glucose Management Questionnaire (IGCQ).	Immediately following intervention completion
Process Indicators (Implementation): Alarm actions	# of alarms for glucose managed by the Clinical Transfer Center (Cyber GEMS only) will be quantified for percent adherence to protocol by: # of times Clinical Transfer Center notified bedside Registered Nurse (RN) / # of qualifying alarms. Rates of follow-up POC testing at bedside will be analyzed/statistically tested by fitting a linear model with # of alarms.	Immediately following intervention completion
Process Indicators (Implementation): CGM satisfaction	CGM satisfaction will be determined using a modified CGM Satisfaction Scale. Questions regarding comfort/interruption, given in both arms and mean overall scores compared by unpaired students t-tests.	Immediately following intervention completion
Process Indicators (Maintenance): Enrollment progress	Number of participants will be continuously monitored by the Data Analyst throughout the study period and tracked against projected numbers for enrollment.	Immediately following intervention completion
Process Indicators (Maintenance): Stakeholder and advisory board feedback	Feedback from Stakeholders and Community Advisory Board members will be descriptively analyzed.	Immediately following intervention completion

Collaborators and Investigators

• Sponsor: Scripps Whittier Diabetes Institute
• Collaborators: National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
• Investigators: Principal Investigator: Addie Fortmann, PhD, Scripps Whittier Diabetes Institute; Principal Investigator: Athena Philis-Tsimikas, MD, Scripps Whittier Diabetes Institute

Study record dates

Study Major Dates

• Study Start (Actual): April 19, 2022
• Primary Completion (Actual): December 17, 2025
• Study Completion (Actual): December 17, 2025

Study Registration Dates

• First Submitted: November 11, 2021
• First Submitted That Met QC Criteria: March 23, 2022
• First Posted (Actual): April 1, 2022

Study Record Updates

• Last Update Posted (Actual): March 9, 2026
• Last Update Submitted That Met QC Criteria: March 5, 2026
• Last Verified: March 1, 2026

More Information

Terms related to this study

• Keywords: Type 2 Diabetes; Hospital; Continous Glucose Monitoring
• Additional Relevant MeSH Terms: Endocrine System Diseases; Metabolic Diseases; Glucose Metabolism Disorders; Diabetes Mellitus; Nutritional and Metabolic Diseases; Diabetes Mellitus, Type 2
• Other Study ID Numbers: R01DK124427 (U.S. NIH Grant/Contract)

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No