Health Care Disparities in Use of Continuous Glucose Monitoring

Abstract

Numerous studies have demonstrated that use of continuous glucose monitoring (CGM) improves glycemic control and reduces diabetes-related hospitalizations and emergency room service utilization in individuals with diabetes who are treated with intensive insulin regimens. Recent studies have revealed disparities in use of CGM within racially and ethnically diverse and lower socioeconomic populations, leading to underutilization of CGM in these populations. This article reviews the scope and impact of these disparities on utilization of CGM and explores the factors that may be contributing to this issue.

Introduction

Large randomized controlled trials and prospective studies have demonstrated that use of continuous glucose monitoring (CGM) improves glycemic control and reduces diabetes-related hospitalizations and emergency room service in individuals with diabetes who are treated with intensive insulin regimens.^1
–3 Recent evidence is emerging that shows similar benefits in individuals with type 2 diabetes (T2D) who are treated with less-insulin or noninsulin therapies.^4

–8

However, recent studies are now revealing disparities in the use of CGM within racially and ethnically diverse and lower socioeconomic populations who have been historically marginalized (National Minority Quality Forum [NMQF], unpublished data).^9
–11 In this article, we review the scope and impact of these disparities on use of CGM and explore the factors that may be contributing to this issue.

Diabetes Prevalence within Historically Marginalized Populations

General population

Racially and ethnically diverse populations have higher rates of diabetes prevalence and related complications compared with White diabetes populations.^{12

–19} The estimated percentage of adults with diagnosed diabetes in the United States in 2018 was highest among American Indians/Alaska Natives (14.7%), Hispanic Americans (12.5%), Black Americans (11.7%), and Asian Americans (9.2%) compared with Whites (7.5%).¹³ (Note that CDC references to populations, including Black, Asian, and White Americans, assume population is non-Hispanic; the “non-Hispanic” will be assumed for the rest of this piece where CDC references are used.)

Medicare population

Within the Medicare population, data from the Centers for Medicare & Medicaid Services (2012) showed that percentages of Black (30.0%) and Hispanic (26.7%) beneficiaries were notably higher than White (18.0%) beneficiaries.¹² Although Black beneficiaries were found to be as likely as White beneficiaries to perform daily self-management activities, they were less likely to report having adequate knowledge/skills to self-manage their diabetes, which raises health literacy questions and potential bias (economic, racial, etc.). Approximately 65% of Black and Hispanic beneficiaries compared with 79% of White beneficiaries knew that Medicare helps pay for diabetes testing supplies and self-management education. Awareness of educational benefits that come with Medicare coverage will presumably improve patient engagement related to patient education and its impact.²⁰

Medicaid/Children Health Insurance Program population

Disparities among racially and ethnically diverse populations and those with low socioeconomic status within the Medicaid/Children Health Insurance Program (CHIP) population are also concerning. Data from a 2019 report from the Kaiser Family Foundation showed that the percentages of Black, Hispanic, and American Indian/Alaska Native beneficiaries on Medicaid/CHIP were twice as high as White beneficiaries (32.9%, 30.0%, and 34.4% vs. 15.2%, respectively).²¹ Within the 29 states that publish Medicaid beneficiary health status, 38.8% of beneficiaries reported average HbA1c levels >9.0%.²² Presumably, of these 29 states, there would be an opportunity to increase educational outreach, suggest peer group support, and other approaches that could address systematically higher rates of suboptimal diabetes management.

Analysis of large databases reinforces that disparities persist: in a recent retrospective, observational, large database (Optum Humedica EHR) that included 31,430 adults with type 1 diabetes (T1D), it was shown that individuals with HbA1c ≥9.0% had a 2-fold risk of severe hypoglycemia and a 12-fold greater incidence of diabetic ketoacidosis (DKA) than those with HbA1c <7.0%.²³ Moreover, a significantly higher percentage of participants covered by private insurance had HbA1c levels <7.0% compared with those covered by Medicaid (20% vs. 12%, respectively). While both percentages are troubling, the fact that fewer people on Medicaid were at the recommended HbA1c level emphasizes the meaningful impact that low income has on diabetes outcomes.

Use of CGM

Pediatric/adolescent/young adult T1D populations

Although CGM in pediatric/adolescents with T1D has increased between 2011 and 2018, from 6% to 38% based on those studied in the T1D Exchange,²⁴ this technology remains largely underused in Black, Hispanic, Asian, and Native American pediatric/adolescent and young adult populations with T1D.^9,10,25 In a retrospective chart review, Lai et al. compared CGM initiation rates and continued use among 1509 pediatric/adolescent T1D patients (18.5% Black, 8.3% Hispanic, 73.2% White.)⁹ Investigators reported that only 30.5% of Black and 32.5% of Hispanic patients initiated CGM, compared with 54.3% of White patients. At 12 months, only 65.8% of Black patients were using CGM, beyond 1 year compared with 85.3% of White and 84.8% of Hispanic patients. Of note, the patients in the Lai et al. study were all eligible for CGM through universal Medicaid coverage for children in Pennsylvania. Real-world data have shown that ongoing discussion and translation related to time in range (TIR) and personalization of alarms and other features, such as sharing, will contribute to better outcomes.

Results from a cross-sectional, multicenter analysis that investigated racial/ethnic disparities within a cohort of 300 young T1D adults (33% White, 32% Black, 34% Hispanic) demonstrated that both socioeconomic status and racial/ethnic characteristics were positive or negative predictors of CGM use.¹⁰ In addition to significantly worse socioeconomic indicators (e.g., lower household income, higher neighborhood poverty), significantly fewer Black (28%) and Hispanic (37%) patients had ever used a CGM device compared with White patients (71%). In this analysis, Black patients also had significantly higher HbA1c levels than White patients: 10.7% ± 2.4% versus 8.5% ± 1.8%. We do note large confidence intervals related to study size, and we encourage more subgroup based on socioeconomic status and racial/ethnic background to further understand relative contributions of these factors.

In a recent retrospective cohort study, Addala et al. assessed the impact of CGM persistence in 264 pediatric/adolescent patients with T1D from a diverse population (49% Hispanic, 6% Black, and 45% White participants).²⁵ Among patients who used CGM, 61% were consistent in their use, defined as using the device 70% of the time or more. Among those who experienced interruptions in CGM, 65% of the interruptions were cost related. In patients with public insurance, improvements in HbA1c were associated with persistent CGM use, whereas those who experienced interruptions in CGM use showed increases in HbA1c levels.

Adult T1D and T2D populations

Disparities among older adults with T1D have also been observed in a retrospective review of 227 T1D adults (25% Black, 15% Hispanic, 43% White, 2% Asian, 15% Other) by Wirunsawanya.¹¹ Among the 68 (30%) patients who used CGM, differences in the proportions of CGM users were notable: 47% White, 22% Hispanic, and 14% Black. Notably, patients covered by government health insurance had lower odds of using technology (odds ratio, 0.43) compared with patients with private health insurance.

Recent CMS data have also shown that a disproportionately low percentage of eligible Black and Hispanic beneficiaries are using CGM (National Minority Quality Forum [NMQF], unpublished data). Among the Medicare beneficiaries who acquired a CGM device between July and December 2020 (n = 3022), investigators observed a significantly lower proportion of CGM use by Black and Hispanic beneficiaries (0.5% and 2.9%) compared with White (91.0%) and other (5.6%) beneficiaries.

Disparities in socioeconomic status and time in glucose target range were reported by Tan et al.²⁶ in their analysis of the General Practice Optimizing Structured MOnitoring To Improve Clinical outcomes (GPOSMOTIC) randomized controlled trial.²⁷ Recall and understanding of HbA1c can pose a challenge for people with low levels of health literacy and education. Time in range offers a clear and complete picture of daily glycemic control by including the percentage of time glucose levels are within a target range as well as capturing time spent above and below target range. In a cohort of 300 adults with T2D who used professional CGM over a 12-month period, higher socioeconomic status was associated with 15% higher time in glucose range and reductions in HbA1c compared with patients with lower economic status. Increased patient engagement and improved health outcomes are possible when using a glucose metric that may be easier to understand by patients, such as time in range. Authors did not measure the impact of race on time in range of HbA1c.

Potential Causes of Disparities

Low socioeconomic status

As discussed, the prevalence of diabetes is significantly higher within racial and ethnic populations. Numerous studies have also shown worse diabetes outcomes within these populations compared with White Americans.^{10,18,28–3329–34} Although biological and genetic differences between racial/ethnic groups may account for a portion of these disparities,³⁴ a significant underlying factor appears to be lower socioeconomic status. Other factors may include access to appropriate medicine and technology, healthy food, stigma, access to health care providers, access to peer support, and additional social determinants of health (SDoH) not mentioned.

Both high diabetes prevalence and poor clinical outcomes are strongly associated with lower socioeconomic status.^{23,29,32,35

–38} Within the Medicare population, there is a notable correlation between diabetes prevalence¹² and beneficiaries' family incomes. Recent data from the Kaiser Family Foundation show that ∼50% of Black and Hispanic beneficiaries have family incomes below 200% of the poverty threshold (Fig. 1).³⁹

FIG. 1.

Association between diabetes prevalence and below poverty threshold within Medicare population.

Access to quality health care

While low socioeconomic status can impact health in a number of ways, including unhealthy behaviors (e.g., smoking, poor nutrition, excessive alcohol consumption, sedentary lifestyle), mental health, and unsafe environment,^40
–42 it is also directly related to poorer quality of health care^{35

–38,43
–45} and limited access to health care providers.

Quality of health care

An early study by Pihoker et al. found that younger T1D patients who are covered by Medicaid are more likely to be treated with less-intensive insulin therapy and receive fewer changes to their current insulin regimens than those with private insurance, with a notable disparity between White and Black and Hispanic patients.⁴⁶ Among T1D children/adolescents covered by public health plans, those with lower socioeconomic status have been shown to have higher HbA1c values, greater incidence of DKA, and diminished quality of life.^35

–38 Previous studies have also found that individuals in lower income racially and ethnically diverse populations receive lower quality of health care, including preventive health services, compared with those who are White.^43
–45

Availability of health care providers

Early studies have shown that low socioeconomic status limits access to a variety of medical services.^47

–50 In a cross-sectional study of ∼50,000 older adults, investigators reported that cost was cited as a major reason for not obtaining needed care.⁵⁰

However, one of the additional largest barriers to health care delivery, beyond economic access, is the lack of adequate numbers of health care providers within low-income communities. As reported by Nguyen et al., individuals residing in low-income urban and rural areas are more likely to have fewer primary care physicians in their communities (0.5% and 7.4%, respectively) than those living in higher-income areas.^51,52 In an earlier analysis of the 2012 National Provider Identifier Registry, Lu et al. reported substantial variations in access to an endocrinologist within a reasonable driving distance and predicted a shortage of endocrinologists by 2020.⁵³ More recently, the Association of American Medical Colleges predicted a national shortfall of 21,000–55,000 physicians by 2032.⁵⁴

Restrictive coverage eligibility criteria

A significant obstacle to CGM use, regardless of socioeconomic status, is the lengthy list of requirements some patients must meet to obtain insurance coverage for CGM. A recent commentary by Galindo et al. presented a comprehensive critique of current CGM eligibility criteria required by CMS and many private insurers.⁵⁵ Most of these requirements (e.g., documented blood glucose monitoring [BGM] ≥4 times daily) were found to be unnecessary and unsubstantiated in the literature; lifting of this requirement in 2021 and communication around this change will help, as will changes to policies allowing PCPs to prescribe CGM. For Medicaid beneficiaries, who can only qualify for CGM only if they are under the care of a board-certified endocrinologist, the requirement is unrealistic. In Georgia, where there are an estimated 75,000 individuals with T1D,^56
–58 as well as over 300,000 individuals with T2D taking insulin, a significant majority of otherwise eligible beneficiaries cannot receive coverage for CGM due to limited or lack of access to a board-certified endocrinologist. According to the Georgia Medicaid requirements for CGM, patients must be under the care of a board-certified endocrinologist who is enrolled in the Medicaid program.⁵⁹ Unfortunately, only 93 board-certified endocrinologists are enrolled in Georgia Medicaid,⁶⁰ most of whom practice in the northwestern portion of the state. This creates significant access issues for patients living in the southern Georgia, where diabetes prevalence is highest.⁵⁷ Importantly, 15 states do even provide coverage for CGM.⁶¹

Excessive documentation requirements for demonstrating medical necessity

Obtaining approval for CGM coverage requires the prescribing health care provider to submit extensive data to support their claim for medical necessity. Although most endocrinology practices are equipped to provide this documentation, many primary care physicians are unwilling or lack the staffing to meet these requirements. Because most patients with lower socioeconomic status are not treated by an endocrinologist, they are at a further disadvantage for obtaining CGM.

Implicit bias among health care providers

Racial and ethnic stereotypes may impact health care providers' attitudes and behaviors when providing care, resulting in different treatment that vary in certain populations. Although implicit bias is difficult to quantify, a recent meta-analysis reported evidence of implicit biases among physicians and nurses in the majority of studies assessed.⁶²

An earlier systematic review by Hall et al. reported similar findings, and the levels of implicit bias among health care providers against people of color were similar across all patient groups.⁶³ However, it was unclear how implicit bias impacted treatment decisions or clinical outcomes. Although some studies showed no significant relationships between implicit bias and outcomes, there is growing recognition of and concern about implicit bias in and around health care provider and patient interactions. It was also found that Black patients perceived poorer treatment related to patient-centeredness and communications with their health care provider.⁶³

Another study found that health care providers are more likely to adopt a more directive, less participatory approach with less-educated patients, who are then less likely to have their expectations met.⁶⁴ Because patients' perceptions of poor-quality communication can negatively impact their adherence to treatment and return for follow-up visits, health care disparities may be further exacerbated.⁶⁵

Addressing bias

People with diabetes should be offered technology without regard to their racial/ethnic or socioeconomic status. There is great opportunity to increase focus on the impact of SDoH in the short and long term, particularly given recent writing and recommendations on SDoH by ADA in a prominent scientific review.⁶⁶ In a randomized, controlled trial of older adults with T1D, CGM was shown to improve glycemic outcomes.⁶⁷ CGM use in this population also demonstrated high treatment satisfaction.⁶⁸ Assumptions are also made regarding people with language barriers, lower health literacy levels, and of certain ethnic or cultural backgrounds. While it is necessary to individualize care, it is critical to be aware of bias when helping a person identify the optimal technology and related treatments. Spending more time in visits can allow for care to be customized for the unique individual. Because time is limited, other members of the care team should be utilized to provide initial education and ongoing support, including diabetes care and education specialists, nurse practitioners, pharmacists, physician assistants, dietitians, social workers, as well as community health workers. As a provider, knowing experts in diabetes technology and referring patients there for further support, education, and care can improve outcomes.⁶⁹

Expanding CGM support and access

The CGM device type and settings should be configured to a person's unique needs. For example, customizing alarms or integrating with connected mobile apps or devices versus aiming for more simplicity based on the person's preferences. Individualizing care and ensuring ongoing follow-up can help with device persistence. Increasing the frequency of visits and support can also reduce risk of discontinuation of the device. Connecting people with diabetes with experienced health care professionals to learn more about the benefits of technology is useful, as is extending knowledge and empowerment from peer support groups.⁷⁰ Thankfully, the recent change to Medicare removing the four times daily fingerstick requirement reduces one of the major barriers for people with diabetes to obtain CGM.⁷¹ To speed the number of people benefiting from more optimized care, health care providers can proactively review their patient panels to see which patients now likely qualify for CGM. As with previous policy changes, other third-party payers will be expected to follow in broadening coverage criteria.

Summary

Racial/ethnic and socioeconomic disparities have been reported across all facets of health care quality and outcomes. In diabetes, these disparities have been associated with higher levels of morbidity and mortality.^12,14,34,72 Although numerous studies have shown significant advantages of CGM use over traditional BGM in improving glycemic control^73

–78 and reducing diabetes-related hospitalizations and emergency room service utilization,^1
–3 this technology is underutilized in historically marginalized pediatric and adult populations.^{9
–11,25,26}

A number of potential factors are driving these disparities, including access to quality care, physician shortages, restrictive insurance eligibility criteria, and implicit bias among health care professionals. Potential solutions to address these barriers include advocacy efforts to expand CGM coverage, expansion of the care team by utilizing community health workers and telehealth services, and individualization of care with coordinated follow-up after device initiation.

Footnotes

Acknowledgments

The authors wish to thank Christopher G. Parkin, MS, CGParkin Communications, Inc., for editorial support and acknowledge the commitment of the Time in Range Coalition to advance the access and use of time in range to improve diabetes care.

Author Disclosure Statement

D.I. has received speaker honoraria from Dexcom, Insulet, Medtronic, Abbott Diabetes Care and Novo Nordisk, and she serves as an advisor to the Time in Range Coalition. N.J.B. has received speaker honoraria from Abbott Diabetes Care, and she serves as an advisor to the Time in Range Coalition. N.J.B., K.L.C., A.C., and U.B. work at Close Concerns, an organization that has received subscription funding from multiple organizations in the field, including Abbott Diabetes Care, Dexcom, Medtronic, and Senseonics, and multiple related organizations.

Funding Information

Funding for the development of this article was provided by Abbott Diabetes Care.

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