Roadmap to the Effective Use of Continuous Glucose Monitoring in Primary Care.

Diabetes technology has undergone a remarkable evolution in the past decade, with dramatic improvements in accuracy and ease of use. Continuous glucose monitor (CGM) technology, in particular, has evolved, and coevolved with widely available consumer smartphone technology, to provide a unique opportunity to both improve management and decrease the burden of management for populations across nearly the entire spectrum of people living with diabetes. Capitalizing on that opportunity, however, will require both adoption of and adaptations to the use of CGM technology in the broader world of primary care. This article focuses on mechanisms to expand pathways to optimized glycemic management, thereby creating a robust roadway capable of improving care across broad populations managed in primary care settings. Recent expansions in access to devices combined with improved mechanisms for data access at the time of primary care visits and improved training and evolving systems of support within primary care, hold potential to improve glycemic management in diabetes across the health care spectrum.

Glycaemic profiles of diverse patients with type 2 diabetes using basal insulin: MOBILE study baseline data.

Basal insulin is often prescribed to patients with suboptimally controlled type 2 diabetes (T2D); however, its therapeutic efficacy is inadequate in many. During the MOBILE study's baseline phase, we evaluated 173 participants' continuous glucose monitoring (CGM) data (mean ± SD age 57 ± 9 years; 50% female; HbA1c 9.1% [range 7.1%-11.6%]; 40% using sulphonylureas; 19% using NPH; reported self-monitored blood glucose [SMBG] frequency median 1.0 checks/day) who were using basal, but not prandial insulin. Blinded CGM data were recorded for 10 days prior to randomization. The mean glucose value was 208 ± 47 mg/dL and it was lowest in the early morning. Mean time in the 70-180 mg/dL range was 9.6 ± 6.1 hours/day (40% ± 25%). Hyperglycaemia was extensive with medians of 14.7 (61%) and 5.0 (20.9%) hours/day with glucose greater than 180 and 250 mg/dL, respectively. Hypoglycaemia was infrequent (median [IQR] 0 [0, 4.3] minutes/day [0.0% {0.0%, 0.3%}] with glucose less than 70 mg/dL). Blinded CGM highlights the limitations of infrequent SMBG in basal insulin users with T2D and allows characterization of hyperglycaemia and hypoglycaemia in basal insulin users with suboptimal control. The MOBILE study randomized phase will define the benefits of using real-time CGM compared with SMBG in this population.

Expert Panel Recommendations for a Standardized Ambulatory Glucose Profile Report for Connected Insulin Pens.

Background: Connected insulin pens capture data on insulin dosing/timing and can integrate with continuous glucose monitoring (CGM) devices with essential insulin and glucose metrics combined into a single platform. Standardization of connected insulin pen reports is desirable to enhance clinical utility with a single report. Methods: An international expert panel was convened to develop a standardized connected insulin pen report incorporating insulin and glucose metrics into a single report containing clinically useful information. An extensive literature review and identification of examples of current connected insulin pen reports were performed serving as the basis for creation of a draft of a standardized connected insulin pen report. The expert panel participated in three virtual standardization meetings and online surveys. Results: The Ambulatory Glucose Profile (AGP) Report: Connected Insulin Pen brings all clinically relevant CGM-derived glucose and connected insulin pen metrics into a single simplified two-page report. The first page contains the time in ranges bar, summary of key insulin and glucose metrics, the AGP curve, and detailed basal (long-acting) insulin assessment. The second page contains the bolus (mealtime and correction) insulin assessment periods with information on meal timing, insulin-to-carbohydrate ratio, average bolus insulin dose, and number of days with bolus doses recorded. The report's second page contains daily glucose profiles with an overlay of the timing and amount of basal and bolus insulin administered. Conclusion: The AGP Report: Connected Insulin Pen is a standardized clinically useful report that should be considered by companies developing connected pen technology as part of their system reporting/output.

Biomarkers for the Diagnosis of Heart Failure in People with Diabetes: A Consensus Report from Diabetes Technology Society.

Diabetes Technology Society assembled a panel of clinician experts in diabetology, cardiology, clinical chemistry, nephrology, and primary care to review the current evidence on biomarker screening of people with diabetes (PWD) for heart failure (HF), who are, by definition, at risk for HF (Stage A HF). This consensus report reviews features of HF in PWD from the perspectives of 1) epidemiology, 2) classification of stages, 3) pathophysiology, 4) biomarkers for diagnosing, 5) biomarker assays, 6) diagnostic accuracy of biomarkers, 7) benefits of biomarker screening, 8) consensus recommendations for biomarker screening, 9) stratification of Stage B HF, 10) echocardiographic screening, 11) management of Stage A and Stage B HF, and 12) future directions. The Diabetes Technology Society panel recommends 1) biomarker screening with one of two circulating natriuretic peptides (B-type natriuretic peptide or N-terminal prohormone of B-type natriuretic peptide), 2) beginning screening five years following diagnosis of type 1 diabetes (T1D) and at the diagnosis of type 2 diabetes (T2D), 3) beginning routine screening no earlier than at age 30 years for T1D (irrespective of age of diagnosis) and at any age for T2D, 4) screening annually, and 5) testing any time of day. The panel also recommends that an abnormal biomarker test defines asymptomatic preclinical HF (Stage B HF). This diagnosis requires follow-up using transthoracic echocardiography for classification into one of four subcategories of Stage B HF, corresponding to risk of progression to symptomatic clinical HF (Stage C HF). These recommendations will allow identification and management of Stage A and Stage B HF in PWD to prevent progression to Stage C HF or advanced HF (Stage D HF).

Continuous glucose monitoring in primary care - are we there?

PURPOSE OF REVIEW: In this review, we examine the expanding role of continuous glucose monitoring in glycaemic management in primary care. RECENT FINDINGS: Improving technology and decreasing cost have increased the uptake of use of continuous glucose monitoring (CGM) for glycaemic management in primary care, wherein most diabetes is managed. Optimized use of this technology, however, will require a convergence of several factors. Availability of devices for people with diabetes, availability of data at the time of clinical interactions, and expertise in interpretation of CGM and ambulatory glucose profile (AGP) data, as well as optimization of therapies, will be required. Significant progress has been made in all three areas in recent years, yet creating systems of support for widespread use of CGM in primary care remains an area of active investigation. SUMMARY: There has been significant uptake in the use of CGM in the management of diabetes in primary care. Optimized use, however, requires both access to CGM data and the expertise to use the data. Although promising strategies have emerged, the task of generalizing these strategies to the broad population of primary care in America is ongoing. CGM technology holds significant potential for improving glycaemic management in primary care, yet important work remains to leverage the full potential of this promising technology.

How use of continuous glucose monitoring can address therapeutic inertia in primary care.

A significant proportion of individuals with diabetes have suboptimal glycemic management. Studies have shown that persistent hyperglycemia significantly increases the risks for both acute and long-term microvascular and macrovascular complications of diabetes. A key contributor to suboptimal glycemic management is therapeutic inertia in which clinicians delay intensifying therapy when patients are not meeting their glycemic goals. During the past five years, an increasing number of individuals with type 1 diabetes (T1D) and insulin-treated type 2 diabetes (T2D) have adopted the use of continuous glucose monitoring (CGM) for daily measurement of glucose levels. As demonstrated in numerous clinical trials and real-world observational studies, use of CGM improves glycated hemoglobin (HbA1c) and reduces the occurrence and severity of hypoglycemia. However, for primary care clinicians who are unfamiliar with using CGM, integrating this technology into clinical practice can be daunting. In this article, we discuss the benefits and rationale for using CGM compared with traditional blood glucose monitoring (BGM), review the evidence supporting the clinical value of CGM in patients with T1D and T2D, and describe how use of CGM in primary care can facilitate appropriate and more timely therapy adjustments.

Continuous Glucose Monitoring Integration for Remote Diabetes Management: Virtual Diabetes Care with Case Studies.

Use of telemedicine and remote monitoring technologies can significantly improve glycemic control in patients with type 1 diabetes and type 2 diabetes. Patients' ability to interact remotely with their health care providers via smartphones and other communication devices can increase their access to clinical care and online coaching and support programs. The establishment of metrics for clinical use of continuous glucose monitoring data and standardization of data reporting has enabled clinicians to maintain high-quality diabetes care through remote monitoring and telemedicine visits during the COVID-19 pandemic. This article discusses our experiences using remote monitoring and telemedicine visits during this time.

Effect of Professional CGM (pCGM) on Glucose Management in Type 2 Diabetes Patients in Primary Care.

BACKGROUND: Little data exists regarding the impact of continuous glucose monitoring (CGM) in the primary care management of type 2 diabetes (T2D). We initiated a quality improvement (QI) project in a large healthcare system to determine the effect of professional CGM (pCGM) on glucose management. We evaluated both an MD and RN/Certified Diabetes Care and Education Specialist (CDCES) Care Model. METHODS: Participants with T2D for >1 yr., A1C ≥7.0% to <11.0%, managed with any T2D regimen and willing to use pCGM were included. Baseline A1C was collected and participants wore a pCGM (Libre Pro) for up to 2 weeks, followed by a visit with an MD or RN/CDCES to review CGM data including Ambulatory Glucose Profile (AGP) Report. Shared-decision making was used to modify lifestyle and medications. Clinic follow-up in 3 to 6 months included an A1C and, in a subset, a repeat pCGM. RESULTS: Sixty-eight participants average age 61.6 years, average duration of T2D 15 years, mean A1C 8.8%, were identified. Pre to post pCGM lowered A1C from 8.8% ± 1.2% to 8.2% ± 1.3% (n=68, P=0.006). The time in range (TIR) and time in hyperglycemia improved along with more hypoglycemia in the subset of 37 participants who wore a second pCGM. Glycemic improvement was due to lifestyle counseling (68% of participants) and intensification of therapy (65% of participants), rather than addition of medications. CONCLUSIONS: Using pCGM in primary care, with an MD or RN/CDCES Care Model, is effective at lowering A1C, increasing TIR and reducing time in hyperglycemia without necessarily requiring additional medications.

Making sense of glucose metrics in diabetes: linkage between postprandial glucose (PPG), time in range (TIR) & hemoglobin A1c (A1C).

While A1C is the standard diagnostic test for evaluating long-term glucose management, additional glucose data, either from fingerstick blood glucose testing, or more recently, continuous glucose monitoring (CGM), is necessary for safe and effective management of diabetes, especially for individuals treated with insulin. CGM technology and retrospective pattern-based management using various CGM reports have the potential to improve glycemic management beyond what is possible with fingerstick blood glucose monitoring. CGM software can provide valuable retrospective data on Time-in-Ranges (above, below, within) metrics, the Ambulatory Glucose Profile (AGP), overlay reports, and daily views for persons with diabetes and their healthcare providers. This data can aid in glycemic pattern identification and evaluation of the impact of lifestyle factors on these patterns. Time-in-Ranges data provide an easy-to-define metric that can facilitate goal setting discussions between clinicians and persons with diabetes to improve glycemic management and can empower persons with diabetes in self-management between clinic consultation visits. Here we discuss multiple real-life scenarios from a primary care clinic for the application of CGM in persons with diabetes. Optimizing the use of the reports generated by CGM software, with attention to time in range, time below range, and postprandial glucose-induced time above range, can improve the safety and efficacy of ongoing glucose management.

Trial of a New Diabetes Education Model: Closing the Gap in Health Disparity for People with Diabetes.

BACKGROUND: Quality measures relating to diabetes care in America have not improved between 2005 and 2016, and have plateaued even in areas that outperform national statistics. New approaches to diabetes care and education are needed and are especially important in reaching populations with significant barriers to optimized care. METHODS: A pilot quality improvement study was created to optimize diabetes education in a clinic setting with a patient population with significant healthcare barriers. Certified Diabetes Care and Education Specialists (CDCES) were deployed in a team-based model with flexible scheduling and same-day education visits, outside of the traditional framework of diabetes education, specifically targeting practices with underperforming diabetes quality measures, in a clinic setting significantly impacted by social determinants of health. RESULTS: A team-based and flexible diabetes education model decreased hemoglobin A1C for individuals participating in the project (and having a second A1C measured) by an average of -2.3%, improved Minnesota Diabetes Quality Measures (D5) for clinicians participating in the project by 5.8%, optimized use of CDCES, and reduced a high visit fail rate for diabetes education. CONCLUSIONS: Diabetes education provided in a team-based and flexible model may better meet patient needs and improve diabetes care metrics, in settings with a patient population with significant barriers.

HbA1c: The Glucose Management Indicator, Time in Range, and Standardization of Continuous Glucose Monitoring Reports in Clinical Practice.

Continuous glucose monitoring (CGM) use is growing rapidly among people with diabetes and beginning to be standard of care for managing glucose levels in insulin therapy. With this increased use, there is a need to standardize CGM data. CGM standardization has been set forth by expert panels. The Glucose Management Indicator is a concept using the CGM-derived mean glucose to provide a value that can be understood similarly to hemoglobin A1c. The times an individual spends in various glucose ranges is emerging as an important set of metrics. Metrics derived from patient CGM data are changing the way diabetes is managed.

Utilizing the Ambulatory Glucose Profile to Standardize and Implement Continuous Glucose Monitoring in Clinical Practice.

Use of continuous glucose monitoring (CGM) is recognized as a valuable component of diabetes self-management and is increasingly considered a standard of care for individuals with diabetes who are treated with intensive insulin therapy. As the clinical use of CGM technology expands, consistent and standardized glycemic metrics and glucose profile visualization have become increasingly important. A common set of CGM metrics has been proposed by an international expert panel in 2017, including standard definitions of time in ranges, glucose variability, and adequacy of data collection. We describe the core CGM metrics, as well as the standardized glucose profile format consolidating 2 weeks of CGM measurements, referred to as the ambulatory glucose profile (AGP), which was also recommended by the CGM expert panel. We present an updated AGP report featuring the core CGM metrics and a visualization of glucose patterns that need clinical attention. New tools for use by clinicians and patients to interpret AGP data are reviewed. Strategies based on the authors' experience in implementing CGM technology across the clinical care spectrum are highlighted.