Use of Continuous Glucose Monitors in the Hospital: The Diabetes Technology Society Hospital Meeting Report 2023.

The annual Virtual Hospital Diabetes Meeting was hosted by the Diabetes Technology Society on April 14 and 15, 2023, with the goal of reviewing the progress made in the hospital use of continuous glucose monitors (CGMs). Meeting topics included (1) Nursing Issues, Protocols, Order Sets, and Staff Education for Using CGMs, (2) Implementing CGM Programs for Use in the Wards, (3) Quality Metrics and Financial Implications of CGMs in the Hospital, (4) CGMs in the Critical Care Setting, (5) Special Situations: Labor/Delivery and Hemodialysis, (6) Research Session on CGMs in the Hospital, (7) Starting a CGM on Hospitalized Patients, (8) Automated Insulin Delivery Systems in the Hospital, (9) CGMs in Children, (10) Data Integration of CGMs for Inpatient Use and Telemetry, (11) Accuracy of CGMs/Comparison with Point-of-care Blood Glucose Testing, and (12) Discharge Planning with CGMs. Outcome data as well as shared collective real-life experiences were reviewed, and expert recommendations for CGM implementation were formulated.

Continuous Glucose Monitoring in the Intensive Care Unit.

Traditionally, the care of critically ill patients with diabetes or stress hyperglycemia in the intensive care unit (ICU) demands the use of continuous intravenous insulin (CII) therapy to achieve narrow glycemic targets. To reduce the risk of iatrogenic hypoglycemia and to achieve glycemic targets during CII, healthcare providers (HCP) rely on hourly point-of-care (POC) arterial or capillary glucose tests obtained with glucose monitors. The burden of this approach, however, was evident during the beginning of the pandemic when the immediate reduction in close contact interactions between HCP and patients with COVID-19 was necessary to avoid potentially life-threatening exposures. Taking advantage of the advancements in current diabetes technologies, including continuous glucose monitoring (CGM) devices integrated with digital health tools for remote monitoring, HCP implemented novel protocols in the ICU to care for patients with COVID-19 and hyperglycemia. We provide an overview of research conducted in the ICU setting with the use of initial CGM technology to current devices and summarize our recent experience in the ICU.

Nursing Perspectives on the Use of Continuous Glucose Monitoring in the Intensive Care Unit.

BACKGROUND: The COVID-19 pandemic necessitated rapid implementation of continuous glucose monitoring (CGM) in the intensive care unit (ICU). Although rarely reported, perceptions from nursing staff who used the systems are critical for successful implementation and future expanded use of CGM in the inpatient setting. METHODS: A 22-item survey focused on CGM use was distributed to ICU nurses at two large academic medical centers in the United States in 2022. Both institutions initiated inpatient CGM in the spring of 2020 using the same CGM+point of care (POC) hybrid protocol. The survey employed a 1- to 5-point Likert scale regarding CGM sensor insertion, accuracy, acceptability, usability, training, and perceptions on workload. RESULTS: Of the 71 surveys completed, 68 (96%) nurses reported they cared for an ICU patient on CGM and 53% reported they had independently performed CGM sensor insertion. The ICU nurses overwhelmingly reported that CGM was accurate, reduced their workload, provided safer patient care, and was preferred over POC glucose testing alone. Interestingly, nearly half of nurses (49%) reported that they considered trend arrows in dosing decisions although trends were not included in the CGM+POC hybrid protocol. Nurses received training through multiple modalities, with the majority (80%) of nurses reporting that CGM training was sufficient and prepared them for its use. CONCLUSION: These results confirm nursing acceptance and preference for CGM use within a hybrid glucose monitoring protocol in the ICU setting. These data lay a blueprint for successful implementation and training strategies for future widespread use.

Implementation of Continuous Glucose Monitoring in Critical Care: A Scoping Review.

PURPOSE OF REVIEW: The aim of this review is to identify the implementation approaches, strategies, and outcomes for continuous glucose monitoring (CGM) in the intensive care unit (ICU). Medline and Web of Science databases were searched to report relevant literature published between September 12, 2016 and September 12, 2021. Implementation outcomes and strategies, defined by the Expert Recommendations for Implementing Change (ERIC) project, were extracted. RECENT FINDINGS: Of the 324 titles reviewed, 16 articles were included in the review. While no studies were identified as implementation research, 14 of 16 identified implementation strategies that aligned with ERIC definitions. Included studies described a multi-disciplinary approach. Clinical outcomes included Mean Absolute Relative Difference (MARD), ranging from 7.5 to 15.3%, and 33-71% reduction in frequency of point-of-care (POC) blood glucose monitoring (BGM) using hybrid protocols. This scoping review provides valuable insight into the process of CGM implementation in the ICU. Continued research should include implementation outcomes to inform widespread utilization.

Supporting the Use of a Person's Own Diabetes Technology in the Inpatient Setting.

The use of diabetes technology, including insulin pumps, continuous glucose monitoring devices, and automated insulin delivery systems, has increased significantly in recent years. As more people with diabetes adopt technology in the outpatient setting, we are seeing these devices more frequently in the inpatient setting. This review offers best-practice guidelines for the continuation of personal diabetes technology use in the inpatient setting. It describes policy and guideline stipulations, roles and responsibilities, and device- and brand-specific considerations. Although these devices are not approved for inpatient use by the U.S. Food and Drug Administration, there is general expert consensus that the continuation of personal diabetes devices during hospitalization is appropriate for patients who have sufficient knowledge, are not critically ill, and retain sufficient mental capacity during an acute illness. Health care systems and inpatient providers need to understand the benefits and limitations of personal diabetes technology use during hospitalization.

CGM in the Hospital: Is It Ready for Prime Time?

PURPOSE OF REVIEW: The use of continuous glucose monitoring (CGM) in the hospital setting is growing with more patients using these devices at home and when admitted to the hospital, especially during the COVID-19 pandemic. RECENT FINDINGS: Historically, most evidence for CGM use in the inpatient setting was limited to small studies utilizing outdated CGM technology and analyzing accuracy of sensor measurements. Previous studies have shown reduced sensor accuracy during extreme hypo- or hyperglycemia, rapid fluctuations of glucose, compression of the sensor itself, and in those who are critically ill. Studies that are more recent have shown CGM to have adequate accuracy and may be effective in reducing hypoglycemia in hospitalized patients; some studies have also showed improvement in time in target glycemic range. Furthermore, CGM may reduce nursing workload, cost of inpatient care, and use of personal protective equipment and face-to-face patient care especially for patients during the COVID-19 pandemic. This review will describe the evidence for use of CGM in hospitalized critically ill or non-critically ill patients, address accuracy and safety considerations, and outline paths for future implementation.

Simulation Platform Development for Diabetes and Technology Self-Management.

BACKGROUND: Specialized education is critical for optimal insulin pump use but is not widely utilized or accessible. We aimed to (1) test the usability and acceptability of A1Control, a simulation platform supporting insulin pump education, and (2) determine predictors of performance. METHOD: Rural adult insulin pump users with type 1 diabetes (T1D) participated in a mixed methods usability study in 2 separate rounds. Participants navigated 3 simulations (ie, infusion site occlusion, hypoglycemia, exercise). Net Promoter Score (NPS) and Systems Usability Scale (SUS) were administered. Semi-structured interviews and direct observation were used to assess perceived usability, acceptability and performance. Synthetic Minority Oversampling Technique was used to fit predictive models for visualization of patterns leading to good or poor A1Control performance. RESULTS: Participants (N = 13) were 28-70 years old, 10 used automated insulin delivery and 12 used continuous glucose monitoring (CGM). Mean NPS was 9.5 (range 9-10) and positive sentiment during interviews indicated very high acceptability. SUS (mean 88.5, range 70-100) indicted a high perceived usability. CGM percent wear ≥ 94%, time spent in hypoglycemia ≤ 54 mg/dl of <0.01%, and <70 mg/dl of 0.5% predicted successful site-occlusion scenario performance with 100% accuracy. BOLUS score ≥ 2, TDD ≥ 34, and technology brand predicted exercise scenario success with 100% accuracy. There were an insufficient number of failed hypoglycemia scenarios to assess predictors. CONCLUSION: A1Control shows potential to increase access and frequency of self-management and technology education. Additional study is needed to determine sustained engagement and benefit.

Expect the unexpected: Adolescent and pre-teens' experience of diabetes technology self-management.

OBJECTIVE: Only 17% of adolescents with type 1 diabetes (T1D) are currently meeting their glycemic targets despite advances in diabetes technologies. Self-management behaviors and challenges specific to use of diabetes technologies are insufficiently studied in adolescents. We aimed to describe the experience of diabetes technology self-management, including facilitators and barriers, among preteens/adolescents with low and high A1C. RESEARCH DESIGN AND METHODS: Youth (10-18 years of age) with T1D who use insulin pump therapy were recruited from the larger quantitative cohort of a mixed methods study for participation in semi-structured qualitative interviews. Maximum variability sampling was used to recruit youth with A1C <7.5% (n = 5) and A1C >9% (n = 5). Participants' personal insulin pump and continuous glucose monitoring data were downloaded and served as a visual reference. Interviews were analyzed using a qualitative descriptive approach. RESULTS: Participants were 50% female with a median age of 14.9 years and 80% used CGM. The sample was predominantly white (90.0%). Analysis produced four major themes, Bad Day, Expect the Unexpected, Nighttime Dependence, and Unpredictability, It's Really a Team and interconnecting subthemes. Youth characterized ''Bad Days'' as those requiring increased diabetes focus and self-management effort. The unpredictability (''Expect the Unexpected'') of glucose outcomes despite attention to self-management behaviors was considerable frustration. CONCLUSIONS: Diabetes devices such as insulin pumps are complex machines that rely heavily on individual proficiency, surveillance, and self-management behaviors to achieve clinical benefit. Our findings highlight the dynamic nature of self-management and the multitude of factors that feed youths' self-management behaviors.

Use of Continuous Glucose Monitor in Critically Ill COVID-19 Patients Requiring Insulin Infusion: An Observational Study.

CONTEXT: The coronavirus disease 2019 (COVID-19) pandemic has created a need for remote blood glucose (BG) monitoring in the intensive care unit (ICU). OBJECTIVE: To evaluate feasibility and patient safety of a hybrid monitoring strategy of point-of-care (POC) BG plus continuous glucose monitor (CGM) in the ICU. DESIGN: Retrospective analysis. SETTING: ICU of an academic medical center. PATIENTS: Patients with COVID-19 on IV insulin. INTERVENTION: After meeting initial validation criteria, CGM was used for IV insulin titration and POC BG was performed every 6 hours or as needed. MAIN OUTCOME MEASURES: Outcomes included frequency of POC BG, workflow, safety, and accuracy measures. RESULTS: The study included 19 patients, 18 with CGM data, mean age 58 years, 89% on mechanical ventilation, 37% on vasopressors, and 42% on dialysis. The median time to CGM validation was 137 minutes (interquartile range [IQR] 114-206). During IV insulin, the median number of POC values was 7 (IQR 6-16) on day 1, and declined slightly thereafter (71% reduction compared with standard of 24/day). The median number of CGM values used nonadjunctively to titrate IV insulin was 11.5 (IQR 0, 15) on day 1 and increased thereafter. Time in range 70 to 180 mg/dL was 64 ± 23% on day 1 and 72 ± 16% on days 2 through 7, whereas time <70 mg/dL was 1.5 ± 4.1% on day 1 and <1% on days 2 through 7. CONCLUSIONS: This study provides data to support that CGM using a hybrid protocol is feasible, accurate, safe, and has potential to reduce nursing and staff workload.

State of the science: A scoping review and gap analysis of adolescent insulin pump self-management.

PURPOSE: Adolescent diabetes outcomes remain poor despite increased use of diabetes technologies such as insulin pump therapy. Meaningful research examining adolescent insulin pump self-management has been done, however, a summary of these self-management findings has not been published. The aim of this literature review is to map, evaluate, and summarize existing adolescent insulin pump self-management research. METHOD: A scoping review of three databases was conducted to comprehensively report and synthesize relevant literature published before September 2019. RESULTS: Of the 1295 titles identified, 18 articles met the inclusion criteria and were included in this scoping review. Key insulin pump self-management behaviors were featured in the literature, most notably self-monitoring of blood glucose (SMBG) and bolus frequency. Several factors were found to influence pump self-management including psychological factors, parental support and self-management transition, insulin pump education and knowledge acquisition, and environmental factors. We uncovered five gaps in the literature including: an unclear delineation of adolescent age; limited minority representation; variability in the definitions and reporting of self-management behaviors; the role of data sharing and remote monitoring was not addressed; and there remains limited inquiry into diabetes burden and distress associated with insulin pump self-management. PRACTICE IMPLICATIONS: There exists a consensus that well-established behaviors, such as bolus and SMBG frequency, influence glycemic outcomes for adolescent insulin pump users, however, full insulin pump utilization and self-management is poorly understood. Diabetes clinicians should work to support adolescent insulin pump self-management practices by reinforcing bedrock behaviors while fostering supportive factors found to influence pump self-management.

From Consultant to Co-investigator: One Diabetes Research Team's Journey of Patient Engagement.

Patients with diabetes are experts in the lived experience of self-management, making patient engagement beyond the role of research "subject" imperative for the creation of health care solutions that meaningfully address the problems they identify. We discuss our research team's relationship with our university's College Diabetes Network (CDN), an advocacy and support group for emerging adults with diabetes. Our collaborative research relationship has spanned three years, and multiple research studies with members serving as co-designers, consultants, and co-investigators. We discuss the CDN's role in two particular studies in which CDN members made substantive contributions to study design, instrument adaptation, and interpretation of findings. Key CDN members played a larger role in research activities and facilitated sustained engagement with the larger university CDN chapter. Barriers encountered included navigating research regulatory requirements while engaging CDN members in research and facilitating sustained engagement as CDN membership changes.

Remote Continuous Glucose Monitoring With a Computerized Insulin Infusion Protocol for Critically Ill Patients in a COVID-19 Medical ICU: Proof of Concept.

OBJECTIVE: The use of remote real-time continuous glucose monitoring (CGM) in the hospital has rapidly emerged to preserve personal protective equipment and reduce potential exposures during coronavirus disease 2019 (COVID-19). RESEARCH DESIGN AND METHODS: We linked a hybrid CGM and point-of-care (POC) glucose testing protocol to a computerized decision support system for continuous insulin infusion and integrated a validation system for sensor glucose values into the electronic health record. We report our proof-of-concept experience in a COVID-19 intensive care unit. RESULTS: All nine patients required mechanical ventilation and corticosteroids. During the protocol, 75.7% of sensor values were within 20% of the reference POC glucose with an associated average reduction in POC of 63%. Mean time in range (70-180 mg/dL) was 71.4 ± 13.9%. Sensor accuracy was impacted by mechanical interferences in four patients. CONCLUSIONS: A hybrid protocol integrating real-time CGM and POC is helpful for managing critically ill patients with COVID-19 requiring insulin infusion.

Facilitators and Barriers to Nursing Implementation of Continuous Glucose Monitoring (CGM) in Critically Ill Patients With COVID-19.

OBJECTIVE: We describe our implementation of a continuous glucose monitoring (CGM) guideline to support intravenous insulin administration and reduce point of care (POC) glucose monitoring frequency in the coronavirus disease 2019 medical intensive care unit (MICU) and evaluate nurses' experience with implementation of CGM and hybrid POC + CGM protocol using the Promoting Action on Research in Health Services framework. METHODS: A multidisciplinary team created a guideline providing criteria for establishing initial sensor-meter agreement within each individual patient followed by hybrid use of CGM and POC. POC measures were obtained hourly during initial validation, then every 6 hours. We conducted a focus group among MICU nurses to evaluate initial implementation efforts with content areas focused on initial assessment of evidence, context, and facilitation to identify barriers and facilitators. The focus group was analyzed using a qualitative descriptive approach. RESULTS: The protocol was integrated through a rapid cycle review process and ultimately disseminated nationally. The Diabetes Consult Service performed device set-up and nurses received just-in-time training. The majority of barriers centered on contextual factors, including limitations of the physical environment, complex device set-up, hospital firewalls, need for training, and CGM documentation. Nurses' perceived device accuracy and utility were exceptionally high. Solutions were devised to maximize facilitation and sustainability for nurses while maintaining patient safety. CONCLUSION: Outpatient CGM systems can be implemented in the MICU using a hybrid protocol implementation science approach. These efforts hold tremendous potential to reduce healthcare worker exposure while maintaining glucose control during the COVID-19 pandemic.

Self-management among pre-teen and adolescent diabetes device users.

OBJECTIVE: Despite increased diabetes device use, few adolescents with type 1 diabetes (T1D) meet glycemic targets. We examine associations between utilization of insulin pumps and continuous glucose monitoring (CGM) and glycemic control. RESEARCH DESIGN AND METHODS: This prospective cohort study included 80 youths (10-18 years of age) with T1D. Multiple linear regression and linear mixed models (LMM) were used to estimate the effects of device self-management on HbA1c and daily time in range (70-180 mg/dL), respectively. RESULTS: Every blood glucose (BG) input/day was associated with a 0.2% decrease in HbA1c (95% CI: -0.297, -0.013), each bolus/day was associated with a 0.2% decrease (-0.327, -0.057), and use of CGM was associated with a 0.5% decrease (-1.00, -0.075). Among CGM users (n = 45) every 10% increase in CGM use was associated with a 0.3% decrease in HbA1c (-0.390, -0.180). In LMM accounting for within subject and between subject variability, there was a negative association between BG input/day frequency (coefficient = -1.880, [-2.640, -1.117]) and time in range. Residual random effects for CGM users were large showing time in range varied between youth with a SD of 15.0% (3 hours and 36 minutes) (SE 2.029, [11.484, 19.530]). Time in range varied significantly from day-to-day with SD of 18.6% (4 hours and 40 minutes) (SE0.455, [17.690, 19.473]). CONCLUSIONS: Device self-management behaviors among youth are significantly associated with both HbA1c and time in range. Our findings showing an association between reduced time in range and increased self-management behaviors is novel and deserves further investigation.

Evaluating Feasibility of Personal Diabetes Device Data Collection for Research.

BACKGROUND: Diabetes devices, like insulin pumps and continuous glucose monitors (CGMs), capture and store patient adherence and utilization data that can be retrieved or downloaded providing objective information on self-management behaviors; yet, diabetes device data remain underutilized in research. OBJECTIVE: The aim of the study was to examine the usability and feasibility of personal diabetes device data collected using a clinical download platform retooled for research purposes. METHODS: Investigators evaluated the feasibility of raw diabetes device data collection. One hundred eight preteens and adolescents with Type 1 diabetes and their parents provided consent/assent. RESULTS: Data were successfully collected from the diabetes devices (insulin pumps and CGM) of 97 youth using a clinical download software adapted for research, including data from all three commercially available CGM systems and insulin pumps brands, which contained all current and previous models of each insulin pump brand. The time required to download, mode of connection, and process varied significantly between brands. Despite the use of an agnostic download software, some outdated device brands and cloud-based CGM data were unsupported during data collection. Within the download software, dummy clinical accounts were created for each study participant, which were then linked back to a master study account for data retrieval. Raw device data were extracted into seven to eight Excel files per participant, which were then used to develop aggregate daily measures. DISCUSSION: Our analysis is the first of its kind to examine the feasibility of raw diabetes device data using a clinical download software. The investigators highlight issues encountered throughout the research process, along with mitigating strategies to inform future inquiry. CONCLUSION: This study demonstrates the feasibility of raw data collection, from a wide variety of insulin pump and CGM brands, through the retooling of a clinical download software. Data from these personal devices provide a unique opportunity to study self-management behavior and the glycemic response of individuals in their everyday environments.

REAL-WORLD IMPLICATIONS OF HYBRID CLOSE LOOP (HCL) INSULIN DELIVERY SYSTEM.

Objective: Clinical trial data demonstrates improved glycemic control with hybrid close loop (HCL) insulin delivery systems, yet limited real-world data exists. Data from the inaugural cohort of patients initiating a HCL system (Medtronic MiniMed™ 670G, Medtronic Canada, Brampton, ON) at a university medical center was used to examine real-world utilization and glycemic control following a standardized implementation process. Methods: Data from 34 adult patients with type 1 diabetes were obtained from pump downloads at 4 time points: (1) previous insulin pump, (2) HCL in manual-mode, (3) 2 weeks after HCL auto-mode transition, and (4) 6 to 12 weeks after initiation of HCL. In-person training by certified diabetes educators was performed across 3 sessions with phone and electronic messaging following auto-mode start. Results: Mean self-monitored blood glucose (SMBG) per day increased from 5.15 baseline to 6.49 at 6 to 12 weeks (P<.05) with 3.26 sensor calibrations per day. Time-in-auto-mode was 79.3% at 2 weeks and 72.3% at final follow-up, with 82% of patients spending >50% of time in auto-mode. There were 8.2 auto-mode exits over the final 14-day download. Time-in-target was 67.3% in manual-mode, 73.4% at 2 weeks (P = .09), and 71.7% by 6 to 12 weeks (P = .06). Hemoglobin A1c (HbA1c) decreased by 0.51% (P = .02), while total daily dose and % basal did not change. Patients with HbA1c <7.0% (53 mmol/mol) at baseline spent more time-in-target than those with HbA1c ≥7.0% (53 mmol/mol; 78.0% versus 67.5%) despite spending less time-in-auto-mode (66.5% versus 74.8%). Conclusion: These data illustrate real-world implementation of HCL technology using a structured education program within a major medical center. Overall benefit may vary based on baseline characteristics such as HbA1c. Abbreviations: CDE = certified diabetes educator; HbA1c = hemoglobin A1c; HCL = hybrid closed loop; SMBG = self-monitored blood glucose.

Insulin Pump Malfunction During Hospitalization: Two Case Reports.

BACKGROUND: Insulin pump malfunctions and failures continue to occur; however, more severe malfunctions such as the "runaway pump" phenomenon are rarely reported. This article describes two cases of pump malfunction in which pump users appear to have received an unsolicited bolus of insulin resulting in severe episodes of hypoglycemia during hospitalization. MATERIALS AND METHODS: Both cases of insulin pump malfunction occurred in the inpatient setting at a large academic medical center in the United States. An analysis of the corresponding insulin pump downloads was performed. The Food and Drug Administration's (FDA's) Manufacturer and User Facility Device Experience (MAUDE) database was searched for similar cases involving Medtronic (Northridge, CA) insulin pumps using the terms "pump," "infusion," "insulin AND malfunction AND Medtronic." RESULTS: The two cases described show remarkable similarities, each demonstrating a severe hypoglycemic event preceded by an infusion site change followed by an alarm. In both cases a rapid spraying of insulin was reported. The insulin pump downloads validated much of the patients' and medical staff's descriptions of events. The FDA's MAUDE database search revealed 425 cases meeting our search term criteria. All cases were reviewed. Seven cases were identified involving independent movement of the reservoir piston. CONCLUSIONS: The cases detailed are the first to describe an insulin pump malfunction of this nature in the hospital setting involving unsolicited insulin boluses leading to severe hypoglycemia. The cases are particularly compelling in that they were witnessed by medical personnel. Providers and patients should receive instruction education on the recognition and management of insulin pump malfunction.