Stakeholder Insights on rtCGM in T2D Population Health Management

ABSTRACT

As a key driver of health care resource utilization, type 2 diabetes (T2D) has drawn the attention of payer and health system stakeholders. Health coaching and interdisciplinary programs are taking hold in the space of population health, with increasing integration of smartphone applications and other technologic advancements. However, until recently, few payers have leveraged the full breadth of diabetes technology available via continuous glucose monitoring (CGM). CGM has been shown to improve glycemic control, increase time in range, reduce hypoglycemic risk, and enhance patient engagement and self-management in type 1 diabetes (T1D) and T2D to varying degrees depending on the category of the system used. Intermittently scanned CGM (isCGM) systems measure glucose levels continuously but require scanning to view glucose values, whereas real-time CGM (rtCGM) systems measure and store glucose levels continuously and display glucose values without prompting. Although isCGM and rtCGM devices were initially prescribed predominantly for patients with T1D, the mounting body of literature has led to more widespread use in insulin-treated T2D and beyond. Based on grade A evidence supporting rtCGM use in T2D cited by the American Diabetes Association and published literature demonstrating the utility of rtCGM in population health, 4 payer and 5 health system experts convened virtually to share their insights on the integration of this technology in current programs. Presented here are a review of key evidence discussed by these stakeholders and findings from the meeting, with recommendations for the implementation of T2D population health programs incorporating rtCGM alongside other interventions.

The American Journal of Accountable Care. 2023;11(4):34-50. https://doi.org/10.37765/ajac.2023.89476

Diabetes affects more than 37 million Americans, with type 2 diabetes (T2D) accounting for approximately 90% to 95% of cases.¹ Although T2D most often develops in individuals 45 years and older, an increasing proportion of children, teenagers, and young adults are receiving T2D diagnoses,¹ representing a public health crisis at the population level. Beyond its adverse consequences in the lives of affected individuals, T2D is recognized by payer and health system stakeholders as being among the costliest chronic conditions.² To manage the clinical and economic burden of T2D more effectively, these stakeholders have increasingly turned to population health efforts. Management of diabetes often requires a complex patient self-management regimen involving the monitoring of symptoms and glucose levels, adherence to medication, and lifestyle modifications. The use of an interdisciplinary care team with numerous patient touchpoints and technological interventions to support patient care is well supported by evidence.^2-4

The current population health approach to T2D is rooted in the chronic care model proposed by Wagner et al in the 1990s, which centers on clinical information systems and decision support tools as a means of optimizing population-level disease care, patient self-management, and patient access to community resources.^2,5-7 Recent population-level findings have shown that effective outpatient interventions that improve T2D management and process outcomes have a multistakeholder aim across patients, providers, and the health care system.² Interventions shown to promote safe and effective glycemic control and use of evidence-based glucose management practices include provider reminder and clinical decision support systems, automated computer order entry, provider education, and organizational change.² Over the past decade, health coaching and interdisciplinary efforts involving primary care physicians, endocrinologists, dietitians, and certified diabetes educators have become the foundation of many population health programs.² Although digital health solutions are broadly available to support patients with their diabetes care, until recently there was limited evidence for the use of continuous glucose monitoring (CGM) in patients with T2D. CGM has been shown to improve glycemic control, increase time in range (TIR), reduce hypoglycemic risk, and enhance patient engagement and self-management in type 1 diabetes (T1D) and T2D to varying degrees depending on the category of the system used.⁸ Intermittently scanned CGM (isCGM) systems measure glucose levels continuously but require scanning to view glucose values, whereas real-time CGM (rtCGM) systems measure and store glucose levels continuously and display glucose values without prompting. Although isCGM and rtCGM devices were initially prescribed predominantly for patients with T1D, the mounting body of literature has led to more widespread use in insulin-treated T2D and beyond and has prompted the American Diabetes Association (ADA) to recommend the use of CGM from the outset of diabetes diagnosis, which has varying grades of supporting evidence (Table 1).⁸

Considering these evolving clinical practice guidelines and the emerging evidence supporting rtCGM use in T2D management—specifically the grade A evidence cited in the ADA Standards of Medical Care in Diabetes—leading payer and health system stakeholders convened virtually to share their insights on population health management and the role of diabetes technology in current and future programs. A total of 4 payer and 5 health system representatives were selected based on their interest in diabetes-related population health management and diabetes technology. During the 5-hour meeting, attendees reviewed consensus recommendations and current evidence supporting rtCGM integration in population health management, with moderated question-and-
answer sessions and discussion. Findings from this meeting and a review of key evidence discussed by these stakeholders are presented here, with recommendations and considerations for the implementation of T2D population health programs incorporating rtCGM alongside other interventions.

Identifying the Value of rtCGM in T2D Population Health Management From the Available Evidence

Literature supporting the application of CGM in T2D varies across available systems, as highlighted by differential grades of evidence assigned in the ADA Standards of Medical Care in Diabetes and other consensus recommendations. At present, a greater volume of more robust data supports the use of rtCGM specifically in T2D, but evidence indicates that isCGM offers value as well, particularly over usual care with blood glucose monitoring (BGM). For example, a meta-regression that included clinical trials and observational studies in T1D and T2D suggested that isCGM could reduce hemoglobin A_1c (HbA_1c) levels by 0.55%, with the magnitude of reduction being proportional to baseline HbA_1c.⁹

Underscoring the mounting body of evidence supporting rtCGM, results of 2 recent studies published in JAMA highlight the potential role of this intervention in population health programs to optimize the management of T2D. The findings from these studies—the MOBILE randomized controlled trial (RCT) (NCT03566693) and a Kaiser Permanente Northern California retrospective claims analysis—represent the highest standard of evidence from an RCT coupled with real-world claims evidence from usual-care settings.

An RCT: the MOBILE study. The MOBILE RCT followed 175 adults with basal insulin–treated T2D over 32 weeks at 15 primary care centers.¹⁰ The primary end point was a significant 1.1% HbA_1c reduction in the rtCGM group compared with the BGM group (1-3 fasting and postprandial fingerstick tests/day) without a significant increase in insulin doses or noninsulin medications.⁹ From a quality-focused perspective, 61.5% more participants in the rtCGM group than in the BGM group were able to achieve a Healthcare Effectiveness Data and Information Set (HEDIS) target HbA_1c of less than 8%. The number needed to treat (NNT) for HbA_1c of less than 8% was 4.2. rtCGM users also demonstrated improvements in terms of TIR (70-180 mg/dL; 3.6 more hours/day) and time spent in hyperglycemia (glucose > 250 mg/dL; 3.6 fewer hours/day) vs BGM users. Overall, the rtCGM group demonstrated greater glycemic improvement despite the administration of fewer medications (insulin and noninsulin medications) than those in the BGM group. With respect to social determinants of health, the clinical benefits of rtCGM were consistent across minority racial/ethnic groups, which comprised 53% of the study population. Collectively, the evidence from the MOBILE study was categorized as level A by the ADA and contributed to the association’s recommendation to use rtCGM in insulin-treated T2D in the 2022 iteration of the Standards of Medical Care in Diabetes.⁸

Real-world evidence: the Kaiser retrospective claims analysis. A real-world retrospective claims analysis conducted by Kaiser Permanente Northern California used a propensity score–matched cohort analysis to compare rtCGM with BGM (12 months pre–/post rtCGM initiation) among 30,407 members with insulin-treated T2D.¹¹ rtCGM resulted in a significant advantage over BGM, including a 0.56% reduction in HbA_1c. This HbA_1c difference favored rtCGM across all ages (33-79 years), baseline HbA_1c levels (7.1%-11.6%), education levels, and diabetes numeracy. In terms of resource utilization, rtCGM resulted in a significant reduction in hypoglycemia rate, a 51% rate reduction in emergency department (ED) visits and hospital admissions, a reduction in outpatient visits, and an increase in telephonic visits. These latter findings suggest increased patient engagement without increased in-person visits, representing potential cost savings. In addition, improvement in HEDIS-target HbA_1c was demonstrated for rtCGM across several measures, including a 12.5% increase in the amount of members with an HbA_1c level of less than 7%, a 17.7% increase in members with an HbA_1c level less than 8%, and a 10.8% decrease in members with an HbA_1c level greater than 9%. The NNT to achieve an HbA_1c of less than 8.0% was 6, with an NNT of 25 to avoid 1 hypoglycemic event (ED or hospital admission).¹¹

These recently published studies demonstrate that the benefit of rtCGM in patients with T2D is similar to published evidence for patients with T1D, with researchers and leading clinicians calling for increased access to rtCGM for insulin-treated patients with T2D and suggesting the value of expanded use and application in population health programs.^12,13

Evidence from rtCGM-based population health programs. Translating these findings into population health programs, rtCGM has also been deployed in virtual population health programs for T2D (Table 2^13-21). The Onduo virtual diabetes clinic (VDC) for T2D combines a mobile app, remote personalized lifestyle coaching, connected devices, and live video consultations with board-certified endocrinologists for medication management and prescription of rtCGM devices for intermittent use.^14-17 In terms of clinical outcomes, enrollment in the program resulted in a significant decrease in HbA_1c.¹⁷ VDC participation also resulted in significant increases in TIR percentage and significant decreases in weight, body mass index, systolic blood pressure, total cholesterol, low-density lipoprotein cholesterol, ratio of total cholesterol to high-density lipoprotein cholesterol, and triglycerides (P ranged from .04 to <.001).¹⁴

Patient adherence and satisfaction were measured via survey in the VDC app (n = 594 patients).¹⁸ In terms of patient experience, the mean rtCGM satisfaction score was 4.5 out of 5, and 94.7% of respondents were comfortable inserting the sensor with remote guidance from a health coach. In addition, respondents reported that rtCGM use improved understanding of the impact of eating (97.0%) and increased their diabetes knowledge (95.7%). Findings from the survey also pointed to a quality improvement component from the health care payer perspective, with the proportion achieving a HEDIS-target HbA_1c level of less than 8% increasing from 46.0% at baseline to 65.3% at follow-up in the insulin group and from 78.6% at baseline to 93.1% at follow-up in the noninsulin group.¹⁸

Similarly, UnitedHealth Group’s Level2 population health program for T2D features integrated tools including rtCGM, an activity tracker, app-based alerts, and one-on-one clinical coaching to help encourage healthier lifestyle decisions around food choices, exercise, and sleep patterns.¹⁹ A pilot study of 790 UnitedHealth Group members reported positive outcomes, with members having a baseline HbA_1c level greater than 8.0% demonstrating the largest reductions and achieving greater than 1% decreases in HbA_1c on average. Program sponsors further noted that some members were able to discontinue diabetes medications. Overall, the program eliminated the need for more than 450 prescriptions across the pilot population and achieved a mean member HbA_1c level less than 7.0% within 3 months of participation.^20,21

More recently, real-world data were analyzed from individuals with T2D who were not prescribed insulin and who were enrolled in a program that provided both an rtCGM system and an artificial intelligence–driven digital health coaching platform (Welldoc).²² Among the 75 participants in the program, the most favorable glucose improvements were found among those with a baseline mean blood glucose level greater than 180 mg/dL, and more dramatic reductions in blood glucose were observed with increasing use of rtCGM.²²

In terms of return on investment, rtCGM has demonstrated real-world cost savings in T2D in prospective and retrospective analyses due to improved glycemic outcomes and reduced resource utilization. In the Intermountain Healthcare/SelectHealth network, 99 members (n = 93 with T2D on various insulin treatment regimens) were randomly assigned for analysis, including 50 assigned to rtCGM and 49 assigned to BGM.²³ rtCGM users demonstrated significantly reduced HbA_1c levels (P = .001), total visits (P = .009), ED encounters (P = .018), and laboratory tests ordered (P = .001). Among SelectHealth non–Medicare Advantage members, savings amounted to $417 per member per month (PMPM) for rtCGM users compared with BGM users.²³

Similarly, a retrospective cohort analysis including 571 patients with T2D from the Optum Research Database who were treated with intensive insulin therapy and nonintensive therapies demonstrated a reduction of $424 PMPM in diabetes-related medical care costs after initiating rtCGM.²⁴ PMPM reductions were driven, in part, by reductions in diabetes-related inpatient medical costs, including inpatient hospital stays and hospital days.²⁴

Stakeholder Insights on rtCGM-Based T2D Population Health Programs

Payer and health system stakeholders noted the impact of these findings associated with rtCGM in population health, particularly those data pertaining to decreased resource utilization (ie, fewer ED visits/hospital admissions) and reduction in HbA_1c levels.

Measuring quality. Although many stakeholders stated they are interested in using TIR as a clinical measure, HbA_1c is entrenched in the health care system and remains the standard by which quality management is currently measured. Accordingly, payer and health system stakeholders noted that longer-term (6 months to 3 years) clinical outcomes and cost savings associated with improvements in TIR would be needed to make associated changes in policy and clinical practice. Previous findings from the IQVIA Core Diabetes Model—showing that improvements in TIR were estimated to reduce the risk of developing diabetes-related complications such as myocardial infarction, end-stage renal disease, severe vision loss, and amputation and resulted in an initial conservative estimated reduction of up to $9.7 billion in costs over a 10-year period—may help elucidate future analyses by population health stakeholders.²⁵ The stakeholders also noted that an algorithm to guide provider practice with specific clinical interventions would bolster the value of TIR as a measure. Preliminary guidance on goals for TIR in clinical practice has been published to this end, and National Committee for Quality Assurance leadership is investigating the use of glucose management indicator and TIR in quality measurement, indicating that the predominant data set may soon be evolving.^26,27 Furthermore, the provision of real-time data at the population health level is seen as an advantage and an opportunity to move away from HbA_1c average blood glucose metrics for quality measurement and provider contracting. Any changes in clinical measurements for quality and contracting agreements would require data integration into the payer, electronic health record (EHR), and health care systems. For the time being, ideal quality measures to highlight the performance of rtCGM-based programs are those that are included in most risk-sharing agreements (eg, HbA_1c-centered metrics, retinopathy, nephropathy, foot examinations). Population health stakeholders will continue to assign substantial value to interventions that can have a demonstrable effect on Star Ratings and HEDIS gaps in care. However, it was mentioned that improved performance on quality measures may not be readily attributable to rtCGM when there are often many other population health interventions in place for diabetes care. Alternatively, risk-sharing agreements could be structured to support broader use of rtCGM and evidence generation.

Driving patient engagement. Population health stakeholders seek further validation of rtCGM as a behavior-modifying intervention. Many asserted that notification of current HbA_1c or trends in blood glucose alone were not necessarily effective as stand-alone behavior-changing factors. However, this information offered in tandem with directive and specific coaching or advisement for patients is viewed as being highly valuable and effective as part of comprehensive care programs. Although reducing HbA_1c levels and health care resource utilization was noted as being important to payer and health system stakeholders, data demonstrating the effect of rtCGM on behavior modification must be more direct and robust, including metrics demonstrating that the rtCGM is being utilized to enable patient behavioral change with regard to diet, lifestyle, and treatment. Of note, since this meeting was convened, additional evidence has emerged supporting the value of rtCGM as a behavior-modifying intervention, including a meta-analysis specific to T2D.²⁸ Interestingly, significant improvements in outcomes were observed more often following shorter vs longer clinician intervention periods upon rtCGM initiation.²⁸ The ability to administer patient surveys within rtCGM-based program applications was highly valued by population health stakeholders to assess patient experience/satisfaction.

Incorporation of CGM into practice. Payers and population health stakeholders offered several considerations among their list of priorities when assessing the use of a new medical intervention, which included the following:

• Interoperability and ease of integration of rtCGM data (eg, open application programming interface) with existing disease management applications and/or EHR systems
• Compatibility with other connected technologies such as blood pressure monitors, fitness trackers, etc
• rtCGM training and support for the patient and care team from the manufacturer
• Analytics support to assess glucose data and return on investment from rtCGM due to decreased HbA_1c, increased TIR, and reduced health care resource utilization (eg, prescriptions, ED/hospital admissions)
• rtCGM flexibility to utilize in key identified populations, either continuously or intermittently over defined time periods as needed by program parameters
• Digital coaching that lessens or eliminates the need for additional human support
• Shared risk between the program vendor/manufacturer and health care system around which to build value-based agreements

Conclusions

Evidence-based recommendations and mounting literature support the opportunity to integrate rtCGM in current and future T2D population health programs as part of a multifaceted approach to chronic disease management. Given appropriate patient selection, outreach, and engagement, available models have yielded demonstrable results in terms of outcomes, resource utilization reduction, and member satisfaction.

Payers and health system stakeholders are acutely aware of the clinical and economic burden that T2D places on the health care system and have accordingly rolled out a multitude of population health programs to date. A growing body of evidence, expert recommendations from ADA and other professional organizations, and successful pilot programs have demonstrated the role of rtCGM in T2D programs moving forward. Stakeholders are interested in better clinical and quality measurement in diabetes, but longer-term data and system integration are recommended to adopt new clinical measures like TIR. Interoperability with currently available programs and integrability in the EHR are seen as part of the value proposition for emerging rtCGM-based solutions.

An analysis presented after this meeting convened showed rtCGM to be cost saving and cost-effective compared with isCGM in insulin-treated T2D over a lifetime projection from the US payer perspective,²⁹ which represents the kind of data called out as being necessary for implementing comprehensive population health programs. Further analyses of cost-effectiveness, preferably stratified by disease progression/severity (eg, treatment regimen, baseline HbA_1c, comorbidities), would likely assist health care decision makers in assessing and implementing rtCGM-centered programs. However, stakeholders are currently open to working on pilot programs or risk-sharing agreements based on shared accountability for outcomes and costs between the program sponsor/manufacturer and the entity (eg, payer/employer/health system) utilizing rtCGM in a population health program.

Considering that the growing body of evidence supporting the use of rtCGM is now extending beyond insulin-treated T2D, future assessments of the technology must be applied as data emerge. As such, further discussion is warranted to determine the appropriate application of CGM in more widespread diabetes management programs, including the potential use among individuals not treated with insulin therapy or among those with prediabetes and the use of more sophisticated metrics such as TIR and glucose management indicator.³⁰ In addition, payer and health system stakeholders must not lose sight of the potential challenges facing disadvantaged demographics, including cost, health literacy and numeracy, and technology literacy. Given the disproportionate burden of T2D among these individuals affected by social determinants of health, interventions to facilitate equitable access to CGM are imperative to effective population health management.¹³

Author Affiliations: Microsoft (DR), Redmond, WA; Orlando Health (BB), Orlando, FL; Trinity Health (VB), Novi, MI; Cooperative Benefits Group (JD), Sandy, UT; Impact Education, LLC (MP), Blue Bell, PA; Independent consultant (DW-P), Detroit Lakes, MN; Mount Sinai Health System (AR), New York, NY; Dexcom, Inc (RT), San Diego, CA.

Source of Funding: Funding for the population health advisory board meeting and the preparation of the subsequent manuscript was provided by Dexcom, Inc Medical Affairs.

Author Disclosures: All authors were paid for their participation in the advisory board meeting funded by the study sponsor, Dexcom, Inc Medical Affairs. Dr Thomas is also an employee of Dexcom, which manufactures continuous glucose monitoring systems.

Authorship Information: Concept and design (DR, JD, MP, DW-P, RT); acquisition of data (BB); analysis and interpretation of data (DR, VB, DW-P, AR); drafting of the manuscript (DR, BB, MP, DW-P, AR, RT); critical revision of the manuscript for important intellectual content (DR, BB, VB, JD, MP, AR); obtaining funding (RT); administrative, technical, or logistic support (JD); supply of content and information (VB); and supervision (VB).

Send Correspondence to: Michael Pangrace, BS, Impact Education, LLC, 589 Skippack Pike, Suite 200, Blue Bell, PA 19446. Email: mike.pangrace@impactedu.net.

REFERENCES

1. National Diabetes Statistics Report: Estimates of Diabetes and Its Burden in the United States. CDC; January 8, 2022. Accessed July 20, 2022.https://web.archive.org/web/20220719115559/https://www.cdc.gov/diabetes/data/statistics-report/index.html

2. Schmittdiel JA, Gopalan A, Lin MW, Banerjee S, Chau CV, Adams AS. Population health management for diabetes: health care system-level approaches for improving quality and addressing disparities. Curr Diab Rep. 2017;17(5):31. doi:10.1007/s11892-017-0858-3

3. Gonder-Frederick LA, Cox DJ, Ritterband LM. Diabetes and behavioral medicine: the second decade. J Consult Clin Psychol. 2002;70(3):611-625. doi:10.1037/0022-006x.70.3.611

4. American Diabetes Association Professional Practice Committee. 16. diabetes care in the hospital: Standards of Medical Care in Diabetes—2022. Diabetes Care. 2022;45(suppl 1):S244-S253. doi:10.2337/dc22-S016

5. Wagner EH. Chronic disease management: what will it take to improve care for chronic illness? Eff Clin Pract. 1998;1(1):2-4.

6. Schmittdiel JA, Nichols GA, Dyer W, Steiner JF, Karter AJ, Raebel MA. Health care system–level factors associated with performance on Medicare STAR adherence metrics in a large, integrated delivery system. Med Care. 2015;53(4):332-337. doi:10.1097/MLR.0000000000000328

7. Comprehensive diabetes care (CDC). National Committee for Quality Assurance. Accessed July 20, 2022. https://www.ncqa.org/hedis/measures/comprehensive-diabetes-care/

8. American Diabetes Association Professional Practice Committee. 7. diabetes technology: Standards of Medical Care in Diabetes—2022. Diabetes Care. 2022;45(suppl 1):S97-S112. doi:10.2337/dc22-S007

9. Evans M, Welsh Z, Ells S, Seibold A. The impact of flash glucose monitoring on glycaemic control as measured by HbA1c: a meta-analysis of clinical trials and real-world observational studies. Diabetes Ther. 2020;11(1):83-95. doi:10.1007/s13300-019-00720-0

10. Martens T, Beck RW, Bailey R, et al; MOBILE Study Group. Effect of continuous glucose monitoring on glycemic control in patients with type 2 diabetes treated with basal insulin: a randomized clinical trial. JAMA. 2021;325(22):2262-2272. doi:10.1001/jama.2021.7444

11. Karter AJ, Parker MM, Moffet HH, Gilliam LK, Dlott R. Association of real-time continuous glucose monitoring with glycemic control and acute metabolic events among patients with insulin-treated diabetes. JAMA. 2021;325(22):2273-2284. doi:10.1001/jama.2021.6530

12. Schaffer R. Real-time CGM lowers HbA1c, reduces ED visits in insulin-treated diabetes. Healio. June 8, 2021. Accessed July 20, 2022. https://www.healio.com/news/endocrinology/20210607/realtime-cgm-lowers-hba1c-reduces-ed-visits-in-insulintreated-diabetes

13. Peek ME, Thomas CC. Broadening access to continuous glucose monitoring for patients with type 2 diabetes. JAMA. 2021;325(22):2255-2257. doi:10.1001/jama.2021.6208

14. Majithia AR, Kusiak CM, Armento Lee A, et al. Glycemic outcomes in adults with type 2 diabetes participating in a continuous glucose monitor-driven virtual diabetes clinic: prospective trial. J Med Internet Res. 2020;22(8):e21778. doi:10.2196/21778

15. Dixon RF, Zisser H, Layne JE, et al. A virtual type 2 diabetes clinic using continuous glucose monitoring and endocrinology visits. J Diabetes Sci Technol. 2020;14(5):908-911. doi:10.1177/1932296819888662

16. Polonsky WH, Layne JE, Parkin CG, et al. Impact of participation in a virtual diabetes clinic on diabetes-related distress in individuals with type 2 diabetes. Clin Diabetes. 2020;38(4):357-362. doi:10.2337/cd19-0105

17. Layne JE, Zisser H, Bergenstal RM, et al. 70-OR: change in A1C with and without intermittent use of CGM in adults with type 2 diabetes participating in the Onduo Virtual Diabetes Clinic. Diabetes. 2020;69(suppl 1):70-OR. doi:10.2337/db20-70-OR

18. Bergenstal RM, Layne JE, Zisser H, et al. Remote application of use of real-time continuous glucose monitoring by adults with type 2 diabetes in a virtual diabetes clinic. Diabetes Technol Ther. 2021;23(2):128-132. doi:10.1089/dia.2020.0396

19. Innovative new Level2 digital health therapy resulted in better health for people with type 2 diabetes. News release. UnitedHealth Group. July 13, 2020. Accessed July 20, 2022. https://bit.ly/46wyBej

20. Gururaj A, Cai A, Close K. UnitedHealth Group launches Level2 type 2 diabetes remission program following successful pilot. Close Concerns Knowledgebase. July 15, 2020. Accessed July 20, 2022. https://www.closeconcerns.com/knowledgebase/r/93a0536e

21. Type2 improved. Level2. Accessed July 20, 2022. https://mylevel2.com/

22. Kumbara A, Iyer A, Leone K, Shomali M. Evaluating the impact of a combined real-time CGM/digital health solution on glucose control for people with type 2 diabetes. Poster presented at: 15th International Conference on Advanced Technologies & Treatments for Diabetes; April 27-30, 2022; Barcelona, Spain. Accessed July 20, 2022. https://www.welldoc.com/wp-content/uploads/2022/04/ATTD-2022-updated-V2.pdf

23. Isaacson B, Kaufusi S, Sorensen J, et al. Demonstrating the clinical impact of continuous glucose monitoring within an integrated healthcare delivery system. J Diabetes Sci Technol. 2022;16(2):383-389. doi:10.1177/1932296820955228

24. Norman GJ, Paudel ML, Bancroft T, Lynch PM. 66-LB: real-time continuous glucose monitor (RTCGM) use associated with decreased diabetes medical costs for patients with type 2 diabetes (T2D). Diabetes. 2021;70(suppl 1):66-LB. doi:10.2337/db21-66-LB

25. McEwan P, Foos V, Palmer JL, Lamotte M, Lloyd A, Grant D. Validation of the IMS CORE Diabetes Model. Value Health. 2014;17(6):714-724. doi:10.1016/j.jval.2014.07.007

26. Battelino T, Danne T, Bergenstal RM, et al. Clinical targets for continuous glucose monitoring data interpretation: recommendations from the international consensus on time in range. Diabetes Care. 2019;42(8):1593-1603. doi:10.2337/dci19-0028

27. Rethinking diabetes care in the digital age. National Committee for Quality Assurance. February 14, 2022. Accessed July 20, 2022. https://www.ncqa.org/white-papers/rethinking-diabetes-care-in-the-digital-age

28. Engler S, Fields S, Leach W, Van Loon M. Real-time continuous glucose monitoring as a behavioral intervention tool for T2D: a systematic review. J Technol Behav Sci. 2022;7:252-263. doi:10.1007/s41347-022-00247-5

29. Alshannaq H, Norman GJ, Lynch PM. 141-LB: cost-
effectiveness of real-time continuous glucose monitoring (rt-CGM) vs. intermittent-scanning continuous glucose monitoring (is-CGM) from a U.S. payer perspective in patients with type 2 diabetes on multiple daily injections of insulin (PwT2D on MDI). Diabetes. 2023;72(suppl 1):141-LB. doi:10.2337/db23-141-LB

30. Barua S, Sabharwal A, Glantz N, et al. The northeast glucose drift: stratification of post-breakfast dysglycemia among predominantly Hispanic/Latino adults at-risk or with type 2 diabetes. EClinicalMedicine. 2021;43:101241. doi:10.1016/j.eclinm.2021.101241