The Role of Advanced Technologies in Improving Diabetes Outcomes

ABSTRACT

Objectives: To discuss the current state of diabetes care in America, the value and utility of innovative diabetes technologies, barriers to access to quality diabetes care and technologies, and how a value-based model of diabetes care can improve outcomes and reduce costs.

Study Design: Narrative review of the current state of diabetes care in America and use of diabetes technologies such as continuous glucose monitoring (CGM) and automated insulin delivery (AID) systems.

Methods: An internet search of relevant studies and government reports was conducted.

Results: Numerous studies have shown that use of CGM and AID improves glycemia, diabetes-related events, and health care resource utilization and lowers overall health care costs. Despite these demonstrated benefits, the majority of individuals with diabetes are not achieving their glycemic goals. Although many of these individuals have limited access to these technologies due to restrictive coverage eligibility criteria, significant disparities exist in technology use within racial/ethnic minority populations and communities of lower socioeconomic status. Transitioning to a value-based approach to diabetes care supports the Quintuple Aim framework.

Conclusions: Shifting our current health care delivery paradigm from the traditional volume-based, fee-for-service model to a value-based model that takes a proactive approach could improve patient outcomes and overall quality of life while helping to reduce the long-term costs of diabetes care.

Am J Manag Care. 2025;31(4):e102-e112. https://doi.org/10.37765/ajmc.2025.89725

Takeaway Points

Diabetes is a significant health crisis in the US that is driving adverse clinical outcomes and associated costs.

• The majority of the estimated 38.4 million Americans living with diabetes have suboptimal glycemic control.
• Despite the demonstrated advantages of continuous glucose monitoring (CGM) and automated insulin delivery (AID) systems, millions of people with diabetes have little or no access to these technologies.
• Increasing access to CGM, AID, and other technologies within a value-based model of diabetes care could improve patient outcomes and overall quality of life while helping to reduce the long-term costs of diabetes care.

The fundamentals of diabetes care have evolved dramatically over the past 20 years. Just as the discovery of insulin in 1921 changed the course of diabetes outcomes for millions of patients globally, the introduction of continuous glucose monitoring (CGM) technologies has revolutionized the way individuals manage diabetes.

This technology enhances what pharmaceutical companies strive to achieve with their prescription medications. Multiple studies have shown that CGM users in various diabetes populations see at least a reduction of 0.5% in hemoglobin A_1c (HbA_1c) levels.^1-4 A reduction of 0.5% is considered to be not only clinically significant⁵ but also comparable to the HbA_1c efficacy end point used in most diabetes medication studies. Thus, use of CGM can be considered a therapy.⁶

Numerous randomized clinical trials and prospective/retrospective studies have demonstrated that daily use of CGM in individuals treated with intensive and nonintensive insulin therapy regimens significantly improves overall glycemic status^7-22 and reduces diabetes-related events, hospitalization rates, and associated costs.^13,23-26 Moreover, CGM use has been shown to significantly improve patients’ understanding of the disease and increase their engagement in daily self-management, particularly in patients treated with nonintensive insulin regimens and noninsulin medications.^27-30

CGM data are also critical for clinicians to provide optimal management of dysregulated glucose levels. The constant flow of data provided by CGM allows a practitioner to see the impact of different therapies, titrate them appropriately, and counsel the patient about how to respond to patterns or glucose events that would be invisible to a patient who sporadically uses a finger stick test to ascertain their glucose level. This means that patient care is more personalized, is customized more rapidly, and more accurately responds to what is happening with the patient, thus improving outcomes and quality of life. The strong endorsement of CGM use found in the Standards of Care in Diabetes of the American Diabetes Association and the clinical guidelines of the American Association of Clinical Endocrinology is a reflection of how valuable these data are to practitioners seeking to provide the best care to their patients.^31,32

Advances in CGM technology and insulin dosing algorithms have led to the development of automated insulin delivery (AID) systems. These systems utilize sophisticated controller algorithms that continuously adjust insulin infusion in response to CGM glucose sensor levels and allow the pump to respond to other factors such as carbohydrate intake and physical activity.³³ Studies with various AID systems have demonstrated significant improvements in glycemic outcomes in individuals with both type 1 diabetes (T1D) and type 2 diabetes (T2D) across all age groups, regardless of diabetes duration, prior insulin delivery method, or baseline HbA_1c level.^34-41 Recent studies have also shown that use of these technologies improves patient satisfaction, quality of life, and other psychosocial measures.^42-46 Study findings also suggest the significant cost-effectiveness of these systems.^47-51

Despite the advantages of CGM, AID, and other innovative diabetes devices (eg, smart insulin pens, bolus calculators) over traditional approaches to therapy, millions of people who could greatly benefit from these technologies have not yet had the opportunity to do so. Fortunately, during the past 5 years, CMS and the more forward-thinking commercial insurers have altered their coverage policies based on new and rapidly emerging clinical data demonstrating efficacy and safety of these innovative self-management tools. Manufacturers have also continually improved their devices, with new generations being introduced on a continual basis. These more capable devices have made the case for their use even more compelling.

Unfortunately, for many individuals with diabetes, access to these technologies continues to be denied, particularly among racial/ethnic minority groups and individuals with low socioeconomic status (SES) who are disproportionately affected by diabetes and its complications.^52,53 For example, Medicaid coverage for CGM varies substantially from state to state,⁵⁴ and the process of ordering or jumping through the hoops of third-party suppliers hampers the expansion of the use of this tool. Limited access to these technologies further exacerbates the rising and unsustainable cost of diabetes in America.

In this article, we review the underlying barriers to access and discuss how a shift in our current health care delivery paradigm from the traditional volume-based, fee-for-service model to a value-based model that takes a proactive approach could improve patient outcomes and overall quality of life while helping to reduce the long-term costs of diabetes care.

Scope of the Problem

Growing diabetes prevalence among young people. An estimated 38.4 million Americans are living with diabetes.⁵⁵ Although the majority of these individuals have T2D,⁵⁶ which occurs mainly in middle-aged and older adults, the number of individuals younger than 20 years with diabetes is expected to increase rapidly over the next decades. The expected upward trend could lead to as many as 220,000 young people having T2D in 2060—an increase of almost 700%.⁵⁷

Despite the availability of newer classes of medications, in addition to the innovative technologies previously discussed, the majority of individuals with diabetes are not achieving their glycemic goals.⁵⁸ Numerous studies have demonstrated that chronic hyperglycemia leads to a constellation of microvascular and macrovascular complications, including coronary artery disease, peripheral artery disease, cerebrovascular disease, diabetic kidney disease, neuropathy, and retinopathy.⁵⁹ In older patients, these complications often take several years to develop. However, a recent study found that individuals who develop T2D as children or adolescents are at increased risk for developing complications of diabetes when they are in their 20s and have a higher probability of developing multiple complications within 15 years of their diagnosis.⁶⁰ Study findings have begun to emerge showing that access to the advanced diabetes technology that would make this paradigm shift in self- and provider-directed care possible has not occurred as broadly as it could.^61-65

Racial/ethnic and socioeconomic disparities. One must also consider the current status of glycemic management in racial/ethnic minority and lower-SES populations, which often demonstrate poor glycemic control and, as a result, are disproportionately affected by T2D and its associated complications.⁶⁶ The highest percentage of adults with diagnosed diabetes in the US is among American Indian/Alaska Native individuals (14.7%), followed by Hispanic (12.5%), Black (11.7%), and Asian (9.2%) individuals compared with White individuals (7.5%).⁶⁷ Hispanic and Black adults also experience a higher burden of worse glycemic outcomes and diabetes-related complications, including higher rates of retinopathy, albuminuria, end-stage renal disease, and lower-extremity amputations compared with White adults.^68,69

However, the higher prevalence of diabetes complications within racial/ethnic minority populations is also closely intertwined with SES, which in turn impacts access to medical specialists and many essential health care services.^70-74 Although poverty rates for racial/ethnic minority groups have dropped sharply since 1990, they remain significantly higher for Native American (23.0%), Black (19.5%), and Hispanic (17.0%) individuals compared with White individuals (8.2%), according to data from the 2020 census.⁷⁵

The impact of race/ethnicity and SES on diabetes outcomes is most notable among women with gestational diabetes (GD). Women with a history of GD have an 8- to 10-fold higher risk of developing T2D and a 2-fold higher risk of developing cardiovascular disease compared with women without prior GD.⁷⁶ The complications of GD are also disproportionally higher across racial/ethnic minority groups, particularly within the Medicaid population.⁷⁷ A recent March of Dimes PeriStats report found that approximately 42% of all births in the US were covered by Medicaid in 2020.⁷⁸ Although most women do not experience GD, the incidence of cesarean deliveries was 35.7% higher among those with GD vs those without (42.0% vs 30.9%, respectively).⁷⁸ The report also showed that the overall incidence of admissions to a neonatal intensive care unit (NICU) among newborns of Medicaid beneficiaries with GD was 38.8% higher than among newborns of beneficiaries without GD (14.0% vs 10.1%, respectively).⁷⁸ Additionally, the percentage of women requiring cesarean delivery was notably higher among Black women (45.5%) compared with White (41.3%) and Hispanic (40.6%) women.⁷⁹ Disparities were also observed in the proportion of Black women whose newborns required NICU care compared with White and Hispanic women (17.5% vs 13.1% and 12.8%, respectively).⁷⁹

Disparities in use of diabetes technologies. Numerous studies have shown disparities in the use of diabetes technologies such as CGM and insulin pumps within disadvantaged populations. Findings from recent studies demonstrate a significant underutilization of these technologies among Black and Hispanic patients with diabetes compared with White patients (Table 1^61-65). These studies clearly demonstrate a notable racial/ethnic gap in the use of diabetes technologies.

Clearly, SES plays a role in contributing to these disparities. For example, a number of early studies have shown that individuals with low SES have more limited access to medical specialists and a variety of health care services.^71-74 Thus, in lower-SES communities, the lack of diabetes specialists with confidence and experience in using diabetes technologies likely contributes to these disparities. But one cannot ignore the influence of implicit bias, which can impact clinicians’ willingness to prescribe these technologies. Clinicians’ perceptions of patients’ intelligence and likelihood of adherence to prescribed therapy are often associated with the patient’s race or ethnicity.⁸⁰ Moreover, health care providers are more likely to adopt a more directive, less participatory approach with patients with less education,⁸¹ which can diminish patients’ trust in their clinicians and negatively impact their adherence to treatment and willingness to return for follow-up visits.⁸²

Although the studies listed in Table 1 summarize disparities in access to diabetes technology, the larger and far more important story is that in all populations across the board, people with diabetes are not being provided these technologies. This means that the best tools for helping manage a devastating and extraordinarily expensive condition are not making it into their hands due to coverage eligibility obstacles⁸³ and underutilization of these tools in primary care.⁸⁴ Although this is slowly changing as the number of CGM and pump users grows,^61,85,86 there is significant room for increasing the use of these technologies across our entire population.

Diabetes Technologies Improve Outcomes

A growing body of randomized trials and real-world evidence suggests that use of diabetes technologies such as CGM and AID can actuate more effective diabetes management^{7-22,39-41,87,88} and improve outcomes^{13,23-26,89-91} (Table 2 [part A, part B, and part C]^{3,17-19,22,39-41,51,89-97}).

Improved Outcomes Reduce Long-Term Costs

Recent studies have demonstrated a strong relationship between the use of CGM and lower rates of diabetes-related health care resource utilization (HCRU) and lower costs.^13,26,77 Norman et al reported cost reductions ranging from –$424 (95% CI, –$816 to –$31; P = .035) per patient per month in a large claims database analysis after initiation of CGM.¹³ In a large cohort of Medicaid beneficiaries treated with intensive insulin regimens, Frank et al reported a $19.4 million decrease in overall costs over the first year of CGM use and continued cost reductions of more than $25.3 million in years 2 and 3.²⁶ More recently, Levy et al reported that the projected savings associated with use of CGM in reducing cesarean deliveries and NICU admissions among Medicaid beneficiaries with GD have also been reported.⁷⁷ As demonstrated by Murphy et al, routine use of CGM by pregnant women with T1D would result in substantial cost savings, mainly through reductions in NICU admissions and shorter duration of NICU care.⁹⁸

Although an increasing number of studies demonstrate that the reductions in HCRU associated with CGM use result in significant cost savings, it is not possible to calculate a definitive or universal dollar amount given the highly variable costs across payer groups and populations due to differences in coverage policies, reimbursements, and cost-sharing programs, particularly among state Medicaid programs.^99,100 Therefore, we recommend that both commercial and government payers take into consideration the demonstrated reductions in all-cause hospitalizations and diabetes-related event rates associated with CGM use and apply their specific multipliers (eg, average cost of 1.0% HbA_1c reduction over 10 years) and HCRU rates in order to determine the potential savings to be gained by expanding CGM coverage among their health plan members and beneficiaries.

Diabetes Technologies Support Value-Based Diabetes Care

The goal of value-based diabetes care (VBDC) is to achieve the best possible health outcomes—physical and psychological—at the lowest cost over the lifetime of each patient. Unlike traditional fee-for-service models, VBDC clinician and hospital reimbursements are based on patient outcomes rather than the volume of patients seen or procedures performed. The underlying rationale for adopting VBDC is simple: Improving patient outcomes will reduce the short- and long-term costs of diabetes care,²⁴ which will have a significant positive impact for all stakeholders, including patients, clinicians, government and commercial insurers, and employers.

The need for a paradigm shift away from our current fee-for-service, chronic care model of diabetes care has never been more critical given the increasing prevalence of diabetes and the poor glycemic status of most patients. In a recent study that assessed glycemic control in individuals with T1D and T2D who are treated with intensive insulin (prandial) or nonintensive insulin (basal only) therapy, Hankosky et al reported that only 26.2% of patients with T1D and intensively treated T2D achieved the goal of an HbA_1c level less than 7.0%; less than 12.3% of patients with T2D treated with nonintensive insulin therapy met this goal.⁵⁸ With the expanding population of patients with poorly controlled diabetes, there has been a significant rise in diabetes complications and cost of treatment. Recent data show that the total cost of diabetes-related health care has risen 21% over 5 years, from $327 billion in 2017 to more than $412 billion in 2022.¹⁰¹ This comprises $306.6 billion in direct costs and an additional $106.3 billion associated with the indirect burden of diabetes, which includes the costs incurred by absenteeism, presenteeism, reduced workforce participation, and early mortality. Clearly, significant changes are needed in the way diabetes care is delivered. Our current approach is untenable.

VBDC Supports the Quintuple Aim for Health Care Improvement

Importantly, VBDC closely aligns with the Quintuple Aim, which builds upon the Triple Aim, a model of health care delivery based on improved patient experience (including better outcomes) and lowered cost of care as the essential components of improving the quality of care. A fourth component that addresses clinician satisfaction was added to create the Quadruple Aim model (Figure^102-105).¹⁰²

The focus on patient experience includes improving access to quality, reliable, person-centered care.¹⁰³ Improving outcomes requires utilizing treatments and interventions that are most appropriate for each patient based on evidence-based protocols and best practices, resulting in lower per capita costs, or at least reductions in the rate of increase in those costs. The fourth component, clinician satisfaction, focuses on the need to address the detrimental impacts of clinician burnout and inefficiencies that are created by increasing patient loads and onerous administrative tasks¹⁰⁴ and correlate with lower patient satisfaction, poor clinical outcomes, and higher costs.¹⁰⁶

The Quintuple Aim takes this approach one step further by incorporating health equity as a key component of health care transformation.¹⁰⁵ This component focuses on improving overall population health by developing a greater understanding of the differences in health and health outcomes based on race/ethnicity, SES, geography (eg, regional differences, urban vs rural), and other social determinants of health and then implementing strategies to overcome the barriers created by these determinants through changes in government policies at the national, state, and local levels and initiatives supported by the private sector.

Digital technologies can and will play a major role in implementing the Quintuple Aim components. Advanced analytics and use of artificial intelligence (AI) offer the capability to assess and quantify the clinical efficacy and financial costs of current and future health interventions, leading to more informed decision-making (clinical and policy), improved outcomes, and lower costs. Moreover, these technologies will enable us to identify and track gaps in health equity within various populations and geographic areas, facilitating more targeted solutions.

On the patient level, technologies such as CGM, AID devices, and use of telehealth not only improve patient outcomes^7-26,34-41 but also lessen the burden of diabetes management, resulting in greater patient satisfiaction^19,96 and improved quality of life.^90,107 At the same time, the improved efficacy can positively affect clinician satisfaction. Friedberg et al found that clinicians who perceived themselves as providing high-quality care reported better professional satisfaction and that obstacles to providing high-quality care were major sources of professional dissatisfaction.¹⁰⁸ In addition, the investigators reported that the functionality of electronic health records (EHRs) also impacts clinician satisfaction, which highlights the need for more efficient, convenient uploading of health data (eg, CGM reports) into EHR systems to improve patient care and reduce administrative burden. To this end, the Diabetes Technology Society recently initiated the Integration of Continuous Glucose Monitoring Data into the Electronic Health Record, or iCoDE, Project to facilitate automated uploading and integration of CGM data into the EHR.¹⁰⁹ Over the next few years, it is probable that AI applications will make significant changes to the functionality of EHRs. This would impact both the integration and interpretation of data, which will ultimately result in higher-value personalized care. Currently, this capability forms the basis for recent developments in closed-loop insulin delivery systems. This clearly suggests that future development of EHRs will take advantage of this capability. In this regard, data-driven, evidence-based personalized medicine is foundational to the VBDC system.

Discussion

Increasing diabetes prevalence, the burdens of daily self-management (particularly as therapies become more complex), and the rising costs associated with managing poorly controlled diabetes pose challenges to all stakeholders. To achieve optimal glycemic outcomes and thus reduce the development of expensive and debilitating complications, patients must be vigilant in monitoring the disease and making appropriate therapeutic decisions. Clinicians—who are overburdened with large patient loads, onerous documentation requirements, and burdensome administrative tasks—often lack the time, expertise, and human resources to meet the individual needs of each patient and teach them to utilize tools that can help them better manage the diabetes and improve the quality of their lives. Moreover, health care systems often lack the infrastructure, processes, and accurate, easily accessible data that would allow them to make more informed decisions about the most efficacious and cost-effective strategies for delivering patient care. Payers are increasingly challenged to balance treatment efficacy, cost, and patient satisfaction when determining coverage policies, and policy makers are tasked with establishing quality standards that correlate with the delivery of quality care and optimal outcomes. In this regard, the current paradigm of providing care is not achieving these goals.

Although utilizing a fee-for-service model may be effective for managing injuries and acute illnesses, it is not well suited for the management of chronic conditions, particularly those, such as diabetes, that are reliant on the active participation of the patient to achieve optimal outcomes. Yet many payers, both government and commercial, continue to struggle with the cost of providing innovative diabetes technologies that have been shown to improve this end. Rather than focusing on reducing the immediate costs of treating the complications of poorly controlled diabetes, we should instead focus on investing in the tools that prevent these complications.

The phrase “penny-wise and pound-foolish” comes to mind. For example, although hospital inpatient days, hospital outpatient visits, emergency department visits, and ambulance services represent almost half ($191.3 billion) of the total cost of diabetes, the technologies that have been proven effective in improving glycemic control,^{7-22,39-41,87} reducing hospitalizations and emergency department visits,^13,23-26,89 and lowering health care costs^{13,26,77,110,111} represent less than 1% ($4.2 billion) of the total cost of diabetes in the US.¹⁰¹ Although there is a clear and urgent need to reduce costs in order to sustain the viability (solvency) of all health care systems, US and international, focusing on the price of these technologies—the traditional “low-hanging fruit”—as the means for lowering health care cost ignores the reality of diabetes. With few exceptions, diabetes is a lifelong disease. Saving a few dollars in the short term while increasing the risk for developing severe and expensive complications in the future makes no sense, financially or ethically.

By design, the VBDC approach generates and processes accurate health data and facilitates standardized measurement of health outcomes and costs through each patient’s lifetime, which enables clinicians and health care systems to continually monitor the effectiveness of treatment in each patient and adjust therapy as needed. Moreover, the continuous flow of patient outcomes data would facilitate better-informed decision-making among all stakeholders. CGM is a tool that facilitates this timely flow of data, to both patients and providers, and it allows payers to support individualized care rather than paying for volume of care. Patients who use CGM have immediate access to information about their health status, being able to see, in real time, how specific foods or activities impact their glucose level. This immediate feedback on behavior not only encourages higher levels of engagement and treatment adherence but also provides the patient (and provider) with the information that is indispensable for making the hour-by-hour modifications in behavioral choices needed to effectively manage diabetes. VBDC also creates opportunities to develop more collaborative, trusting clinician-patient relationships and shared decision-making based on accurate, real-time data. This could help alleviate implicit bias by breaking down social barriers and increasing clinician-patient trust. It would also expand utilization of diabetes technologies among all patients regardless of race, gender, and SES. Moreover, it would help clinicians improve the quality of care they provide through learning from the data. Health care systems would benefit from the ability to generate and standardize evidence-based best practices that would eliminate costly trial-and-error decision-making when determining treatment strategies that are most appropriate for their patient populations. It also would help identify and prioritize communities where clinicians with expertise in diabetes management are needed.

Access to accurate, comprehensive outcomes data would enable payers to assess the true value of medications and technologies relevant to their long-term impact on reducing complications and enhancing patient satisfaction among their plan beneficiaries. These data would not only assist decision makers in determining coverage policies but could also be used to elevate their Star Ratings and National Committee for Quality Assurance Health Plan Ratings, which would be beneficial for expanding their member base. Similarly, the ability to collect outcomes data will enable policy makers to make more informed decisions about quality measures, health care reform, and allocation of health care resources. From a clinical perspective, access to these data would facilitate more informed decision-making regarding the most effective intervention based on each patient’s individual needs and preferences. Moreover, these data would be extremely useful in keeping education programs and materials current.

Although transitioning to VBDC may seem a daunting task, we do not have to reinvent the wheel. The ongoing development of innovative diabetes and general health technologies has created a diabetes ecosystem that encompasses a diverse offering of digital tools and capabilities, including connected medical devices (eg, CGM, insulin pumps, AID systems), decision support software, remote coaching programs, social networking, and rapidly advancing data analytics. With the advent of increasingly sophisticated AI software and machine learning capabilities, we already have the tools in place to begin the transition. Further development is needed to implement individualized management in real time with and without health care provider input. Directing resources to allow ongoing algorithmic-derived input into diabetes management may achieve the outcomes that have thus far been elusive.

The diabetes epidemic will only worsen in the years ahead if we continue to use outmoded treatment methods that have been based on acute care strategies. VBDC provides a pathway for reducing health care costs while improving the lives of individuals with diabetes.

Author Affiliations: School of Public Health, University of Arizona (DGM), Tucson, AZ; CGParkin Communications, Inc (CGP), Henderson, NV; Division of Endocrinology, Metabolism and Molecular Medicine, Feinberg School of Medicine, Northwestern University (GA), Chicago IL; University of Washington School of Medicine (IBH), Seattle, WA; Division of Endocrinology, Metabolism and Lipid Research, School of Medicine, Washington University in St Louis (JM), St Louis, MO; University of Miami Miller School of Medicine, University of Miami Health System, Jackson Memorial Hospital (RJG), Miami, FL; Lennar Foundation Medical Center (RJG), Coral Gables, FL; Division of Endocrinology, Diabetes, and Bone & Mineral Disorders, Henry Ford Health (DFK), Detroit, MI; Division of Endocrinology, Diabetes, and Metabolism, Icahn School of Medicine at Mount Sinai (CJL), New York, NY; International Diabetes Center, HealthPartners Institute (ALC), Minneapolis, MN; Division of Endocrinology, Metabolism, and Lipids, Emory University School of Medicine (GEU), Atlanta, GA; Diabetes and Endocrinology, Grady Memorial Hospital (GEU), Atlanta, GA.

Source of Funding: None.

Author Disclosures: Dr Marrero has received honoraria for participating in a focus group at the American Diabetes Association Scientific Sessions meeting about diabetes education. Mr Parkin has received consulting fees from Abbott Diabetes Care, CeQur, Dexcom, Embecta Corp, HAGAR, Insulet Corporation, LifeScan, Mannkind Corporation, Roche Diabetes Care, Provention Bio, and Tandem Diabetes Care. Dr Aleppo has received grants from Fractyl Health, Insulet, MannKind, Tandem Diabetes Care, and Welldoc and lecture fees from Dexcom and Insulet. Dr Hirsch has participated in paid advisory boards for Abbott, Embecta, Roche, and Vertex Pharmaceuticals and received grants from Dexcom, Mannkind, and Tandem Diabetes Care. Dr McGill has participated in paid advisory boards for Bayer, Eli Lilly and Company, Mannkind, and Novo Nordisk and received grants from Novo Nordisk. Dr Galindo has received consulting or advisory fees from Abbott, AstraZeneca, Bayer, Dexcom, Eli Lilly and Company, Medtronic, and Novo Nordisk and received grants from Boehringer Ingelheim, Dexcom, Eli Lilly and Company, and Novo Nordisk. Ms Kruger has received consulting or advisory fees and honoraria from Abby Health, Arcor, Ascensia Diabetes Care, CeQur, Dexcom, Eli Lilly and Company, Embecta, Insulet, MannKind, Medtronic, Novo Nordisk, Proteomics International Laboratories, and Structure; received grants from Abbott, Insulet, and Tandem Diabetes Care; and received lecture fees from Abbott, Dexcom, Eli Lilly and Company, Insulet, and Novo Nordisk. Dr Levy has participated in paid advisory boards for Dexcom and Tandem Diabetes Care and received research support paid to her institution from Dexcom, Mannkind, Novo Nordisk, and Tandem Diabetes Care. Dr Carlson has received consulting or advisory fees from Insulet and research support from Abbott, Dexcom, Insulet, Medtronic, and Tandem Diabetes Care; all payments go directly to his employer, and none are paid to Dr Carlson directly. Dr Umpierrez has participated in paid advisory boards for Dexcom and GlyCare and received grant support to Emory University from Abbott, Bayer, and Dexcom.

Authorship Information: Concept and design (DGM, CGP, GA, IBH, JM, RJG, DFK, CJL, ALC, GEU); acquisition of data (JM); analysis and interpretation of data (DGM, CGP, GA, IBH, JM, RJG, DFK, CJL, ALC, GEU); drafting of the manuscript (DGM, CGP, IBH); and critical revision of the manuscript for important intellectual content (CGP, GA, JM, RJG, DFK, CJL, ALC, GEU).

Address Correspondence to: Christopher G. Parkin, MS, CGParkin Communications, Inc, 2675 Windmill Pkwy, Ste 2721, Henderson, NV 89074. Email: chris@cgparkin.org.

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