Publication

Article

Supplements and Featured Publications
Analyzing the Value of Continuous Glucose Monitoring in Diabetes Care and Overcoming Barriers Through Expanded Pharmacy Access
Volume 28
Issue 4

Continuous Glucose Monitoring Metrics: Interpretation and Integrations

To claim CE credit for this activity, please visit https://www.pharmacytimes.org/courses/analyzing-the-value-of-continuous-glucose-monitoring-in-diabetes-care-and-overcoming-barriers-through-expanded-pharmacy-access

Introduction to Continuous Glucose Monitoring

Clinicians who provide care for persons with diabetes are excited about continuous glucose monitoring (CGM). The technology with CGM is evolving and becoming more reliable and affordable; as it does, its use is increasing. Some experts expect that within a few years, all persons with diabetes will have access to this tool, not just those with the most serious disease. In other words, CGM is expected to become a ubiquitous standard of care.1 As medical engineers refine the abilities of CGM, they anticipate creating large databases that fold CGM data into several other data sources (eg, biomarkers from laboratory tests, clinical registries, electronic health records [EHRs], prescription registries). They also plan to have the patient’s medical devices for diabetes (blood glucose monitoring devices, insulin pumps and pens, and other variables collected by mobile apps) communicate to each other about diet, exercise, and medication. They call this the CGM digital ecosystem.1

The significant increase of devices used in healthcare presents challenges for healthcare providers (HCPs). While technology is essential to improving care, its proliferation can confuse and frustrate HCPs and patients who are candidates for the technology and consume valuable time as new devices come to market. Patients may find they have fragmented healthcare experiences.2 CGM and other technologies are changing rapidly; the velocity of the change may be so great that clinicians and insurers cannot or do not stay current, and cost and insurance issues remain significant barriers.3 Fortunately, leading professional organizations have taken steps to standardize the way technology is incorporated into care plans for persons with diabetes and how clinicians leverage technology-enabled solutions. This continuing education activity will address the integration and implementation of CGM into practice, including the interpretation of reports and data to optimize the care for persons with diabetes.

As noted previously in part 1, professional organizations endorse the use of CGM for adults with type 1 and type 2 diabetes (T1D/T2D), as CGM literature has demonstrated to significantly improve A1C levels and absenteeism and reduce the risk of treatment-emergent hypoglycemia, hospitalizations, and diabetes complications.4-10 CGM can also inform patients to adapt actions and behaviors and improve quality of life.9,11,12

Despite guideline recommendations and numerous studies reporting positive clinical and patient outcomes, implementation of CGM into practice has been slow. This has been attributed to clinician-specific barriers including difficulty identifying appropriate patents for CGM, complexity of data, time constraints, and workflow disruption.3,13 The Box14,15 lists common barriers associated with utilization of CGM in practice settings.14,15

The Identify, Configure, Collaborate Framework

First and foremost, for proper CGM implementation, it is imperative for HCPs to recommend and prescribe CGM and other diabetes technologies in the most appropriate way possible. The Identify, Configure, Collaborate (ICC) framework is a 3-step approach that assembles and communicates information in a manageable process to ensure this.13

ICC step 1 is to identify an individual patient’s needs and goals to determine the best technology at the right time.13 During assessment, the HCP needs to determine if the patient is ready to adopt new technology, is physically and cognitively prepared to work collaboratively, has knowledge or skill gaps, possesses appropriate healthcare literacy, and is able to make lifestyle choices.13 If the patient is unwilling to adopt new technology or unable to understand how to use it, CGM is not the best choice. Practices that see mostly older patients who have T2D may find that professional CGM rather than personal CGM may be most useful for them.14 Patients also need the financial means to obtain technology consistently.13

ICC step 2 is to configure that technology based on the patient’s preference and available support.13 HCPs need to look at the entire technology ecosystem (eg, medical devices, medical software, data platforms, and consumer applications for diabetes and related cardiometabolic conditions). Individual patients need device functions that align with their abilities, and they also need a support plan for the inevitable times when they have questions or problems. Some areas that need to be addressed proactively include setting up alarms or alerts, which can be bothersome for patients and create alarm fatigue, and determining the necessity of remote monitoring (ie, for children who were at school or adults who need close supervision). HCPs should consider starting patients who have low technology skills with customizable alarms.14 Experts indicate that once the CGM device is set up, HCPs should use the “show me” process to ensure that the patient can perform all necessary functions without assistance.13 They can add advanced functions as the clinician’s and the patient’s comfort grows.13

ICC step 3 is to collaborate with the patient and care team to individualize treatment and provide feedback.13 The collaborative process should engage the patient in ways that prompt behavioral changes and stimulate continuing progress toward the patient’s individual goals. It is also important to engage HCPs. The collaborative process can help HCPs identify and address their own clinical inertia, learn new interventions that can help patients move toward their goals, and teach them new ways of looking at old problems. Step 3 can also help address population health; by looking at trends across their entire patient population, they can see how the patient care they provide persons with diabetes trends over time and perhaps compare it with other providers’ care.13

Interpreting the Ambulatory Glucose Profile Report

The cornerstone of step 3 of the ICC is the Ambulatory Glucose Profile (AGP) report, a standardized report that uses a common language to describe key metrics developed by the International Consensus guidelines and the American Diabetes Association. 16-18 These standardized metrics (see Table 2 in part 1 of this supplement), depicted with numerical and graphic visualization such as charts and graphs of glucose data, help to address the barrier of complex data and increase the ability of HCPs to interpret data efficiently, independent of the CGM device used.16,17

The AGP (Figure 119) has a standardized format with 4 sections: (1) glucose statistics and targets; (2) time in range (TIR); (3) AGP; and (4) daily glucose profiles.20

Reviewing the Ambulatory Glucose Profile With Patients

Assisting patients with understanding the data obtained from their CGM device is a key opportunity for HCPs. Its full benefit is not fully realized unless patients can interpret and respond appropriately to their current glucose levels, glucose trends, and rate of change (the direction and velocity of change in glucose) in real time.21,22 Reviewing the AGP with patients is critical to engage patients in conversation about their diabetes management, including diet, physical activity, and medications.22Figure 222 summarizes an approach to interpreting the AGP with patients that employs the acronym DATAA.22

Download Data

In the clinic, downloading data can be a challenge for staff due to time constraints or a lack of technical skill.15,23 Each CGM system uses different software, and it is critical for practices that utilize this technology to have the appropriate software available. Once the data are downloaded, HCPs should start with a global overview and orient the person with diabetes to the AGP key metrics described in Table 2 of part 1 and engage them in discussion by inquiring about their successes with their self-management of diabetes.22

Assess Safety

Assessing safety is an important intervention, so HCPs should review the time below range (TBR), or hypoglycemia, in 3 ways: specific times the patient experienced hypoglycemia, percentage of time spent in hypoglycemia, and number of hypoglycemic events during the examined time frame. Asking the patient to describe potential causes and resolutions of these events is a priority during this step.22,23 A comparison of their TBR to the patient’s individual target goals and their glucose variability (GV) should also be analyzed (see Table 2 and Figure in part 1).20

Time in Range

After assessing safety, the HCP should review the percentage of time the person with diabetes was in their target range, or TIR, which is a visual representation of the percentage of time and actual time the patient was at their target (green), above their target (yellow), and below their target (red). As discussed in part 1, TIR is either 70 to 180 mg/dL for persons with T1D or T2D or 63 to 140 mg/dL for pregnant patients.20,22 The patients’ TIR goals will vary based on patient-specific factors (see Figure in part 1).20 At this step, the HCP should emphasize and affirm positive patterns where TIR is the greatest to identify periods of time where dietary changes and physical activity seem to contribute to good diabetes management. HCPs should stress duplicating actions that worked well whenever possible.22,23

Areas for Improvement

The last area of the AGP to review is the time above range, which denotes hyperglycemia. Similarly to the previous steps, the HCP can help patients look at the days of the week or times in the day when they tend to do better and encourage them to apply those actions during periods when they tend to be hyperglycemic. Stressing that some simple modifications in self-care behavior can improve the overall picture is critical.22,23

Action Plan

As in so many disease states, persons with diabetes need clear action plans to understand specifically what they should do and when to overcome inertia, which is the final step in this process. Action plans must be developed in collaboration with the patient or the patient’s caregiver, and they must clearly state whether the status quo is acceptable or adjustments to the patient’s self-management of their diabetes is required. Some authors suggest printing the AGP, marking it up, and giving a copy to the patient to take home.22,23

Example Clinician Interpretation of the Ambulatory Glucose Profile Report

In this example AGP (Figure 119), it can be seen that the patient’s TBR was very low 1% of the time and low 0%. The target goals for below less than 54 mg/dL are less than 1% (14 minutes). It would be important to have a conversation with the patient to try to identify what may have been the cause of this hypoglycemia. Did they skip a meal? Did they take too much of their insulin? Were they prepared to treat hypoglycemia, and did they manage it properly? This patient had no other indications of hypoglycemia in the 14-day period, but if they did, evaluating these targets and TBR are critical components of the interaction with the patient. HCPs should also be aware that false hypoglycemia can occur if there is pressure on the sensor during sleep.24 When evaluating the daily glucose profile, explained below, it can be determined that this occurred in the early morning hours on May 7 and appears to be an isolated incident, not recurring. It is likely false hypoglycemia if no cause is identified by the patient. Evaluation and management of TBR is an essential component of safety and it is vital to make sure patients are prepared to prevent hypoglycemia and manage it properly if it occurs.

This patient’s TIR (see Figure 119) was in target range 80% of the time and at a target goal of more than 70%. This is an area where success can be celebrated or, if not at target, where one can delve deeper into identification of where, why, and how to make an adjustment. When looking at the glucose statistics in Figure 119, one can identify that this patient did an excellent job with a GV of less than or equal to 36% at 20.1%. This demonstrates the magnitude of glucose excursions.

The AGP is the visual representation of blood glucose changes over time, and it identifies the ideal range using green lines.23 This simple and color-coded report allows clinicians to assess data and trends quickly and identify extreme GV swiftly.25 HCPs are able to visualize where excursions exist and potentially how to manage them. In Figure 119, the various percentiles are shown, with the median being at 50%. Over the 14 days, overlaid, it appears that the patient had the most variability at approximate mealtimes while still having a desirable GV.

One can further look at the daily glucose profile, a tool that depicts a midnight-to-midnight view of glucose trends with the blue line. Excursions above range are noted in yellow and below range in red for an easy interpretation of specific days or time of day when patients may have trouble with control (ie, on weekends or around holidays).25 Discussing daily trends often prompts patients to self-manage appropriately and start behavioral or dietary changes on their own. Patients can make better dietary adjustments and see how exercise affects their blood glucose.25

For example, Figure 119 demonstrates that on May 7 some hypoglycemia, marked in red, occurred in the early morning. HCPs can look further in the report, past the first AGP report page to the daily log, and drill down further, as shown below in Figure 3.19 It is there that one can identify that the 2 low readings occurred at approximately 2 am and 6 am, further supporting the suspicion of false hypoglycemia if no cause is identified. Additionally, you can see in yellow, days and times in the daily glucose profile, when a person is above 180 mg/dL. One thing to note is that with intermittently scanned CGM, patients need to scan at least every 8 hours for 24-hour data to appear. As shown in Figure 319, this patient scanned at 8 am and not again until about 6 pm, leading to a small gap in data shown on May 7 between 8 am and 10 am.

By evaluating the ranges, HCPs can help the patient identify the potential causes and solutions to manage time above range. Was it due to their food choices or lack of exercise? Was it due to missing or the wrong dose of oral medications or insulin? An important counseling point would be to have the patient type into their smartphone app notes to identify what is going on at the time of a reading below or above target. For example, in this patient (Figure 119) who has a blood glucose of 196 mg/dL at about 10:30 pm, it would be helpful for that person to write a note so that when the HCP is reviewing, they can identify the cause of the high reading. Did the patient just eat a high-carbohydrate meal or was there a medication issue? This documentation can help patients make informed choices and decisions with their foods and medication doses and help providers educate and provide strategies to improve glycemic outcomes.

Understanding how to interpret the AGP report and identify treatment approaches with medication or lifestyle adjustments is an important aspect of patient care. The AGP report is a powerful tool to improve patient outcomes.

Integration of CGM Data Within EHR Workflows

An integrated data network expands HCPs’ capacity to monitor patients’ health status comprehensively, allows for remote monitoring, and may permit them to consult without office visits or hospitalizations.24 Successful integration of CGM data (or an integrated data network) directly into the EHR is currently the exception rather than the rule.26 Thus, HCPs cannot see CGM data as they do clinical laboratory results, imaging reports, medication records, and other test results. While HCPs usually are not involved in the mechanics of marrying personal devices to large information technology systems, knowing why these systems do not communicate to each other magically can reduce frustration. Systems that successfully integrate such data usually need assistance from third-party integration engines or data aggregators.26 In many practices, once the data are downloaded as a PDF, this can be either uploaded into the EHR or it can be copied and pasted directly into an electronic chart note. The AGP and subsequent data that are available can also be printed if needed and can be sent to a patient electronically from a practice’s secure portal if so desired and if the technology of the EHR allows.

When CGM data are integrated into the main information system, reviewing data is easier. Absent that ability, clinical teams need to establish workflows that fit into standard practice.27 The clinical team needs to establish who will download data, what software is needed, and which departmental computers will house these data. Further consideration should include data storage in “cloud-based” platforms to allow data access from multiple workstations. This may require the health-system information technology personnel to create HIPAA-compliant work-arounds to overcome firewall barriers to allow access.27,28 HCPs will also need to discuss privacy concerns with patients, and discuss the expected duration of data collection, how the data will influence clinical decisions, and timing of data submission (especially if the patient must scan the device).28

EHR-integrated, patient-generated health data have some downfalls. It can be burdensome for clinicians, leading to burnout.29 HCPs may also be unfamiliar with various devices and uncertain about matching devices to each patient’s needs.14 Many HCPS experience “technostress,” stress caused by working with computers on a daily basis. Ensuring that all members of the team have clear roles can decrease technostress, as does availability of standard, easy-to-read reports and dashboards, such as the AGP. Education and training also reduce technostress.29

Time pressure can also lead to burnout.29 In this instance as well, standardized formats are helpful and timesaving. A review of all tasks associated with current and proposed technology can help systems identify demanding or poorly designed tasks and plan appropriate solutions. Using algorithms is also timesaving, especially if they incorporate alerts and filters that clinicians need and appreciate; clinicians appreciate seeing material in one screen without having to search or switch from screen to screen.29

Workflow-related issues can seem overwhelming, and systems need to visualize how work will be done. Assigning responsibilities to specific staff or departments, identifying the best frequency for reviewing data, clarifying how clinicians can contact patients (eg, secure message, phone call, telehealth platforms), and clarifying which patient-owned devices are best for specific patients can reduce workflow stress.29

The ICC framework and other experts identify 3 areas where healthcare systems can use data from CGM and related devices in the ecosystem as a performance and quality improvement initiative.13,29 Appropriate health-system employees need to:

  • Evaluate the possibility that the teams or patients are experiencing data overload, burnout, and disengagement.
  • Compare current and new technology to establish its value in clinical practice, in the system’s specific populations, and in the healthcare industry.
  • Consider technology and its uses, advantages, and disadvantages as they develop policy.
  • When addressing each of these areas, decisions need to be collaborative and include frontline clinicians and patients in the processes.

Conclusions

Diabetes technology continues to evolve and expand. Perhaps one day, CGM will be integrated with other remote monitoring devices in a wearable device that also monitors blood pressure, an electrocardiogram, or other values of importance to HCPs and patients. CGM inevitably will advance and be refined in the future for improved care and outcomes for persons with diabetes. Standardization and understanding of interpretation of reports will help minimize or avoid “technostress” that can occur in providers and patients alike. Determining how to implement and integrate these technologies into daily workflow is a critical aspect, as well as the education and utilization for patients. Although today, CGM is not accessible for all persons with diabetes, it likely will become standard of care as more proof of value and disease state management outcomes become available.

Author affiliations: Jennifer Goldman, PharmD, RPh, CDCES, BC-ADM, FCCP, is a Professor of Pharmacy Practice, School of Pharmacy, Massachusetts College of Pharmacy and Health Sciences, Boston, MA; Clinical Pharmacist, Well Life Medical, Peabody, MA.

Funding source: This activity is supported by an educational grant from Abbott Diabetes Care Inc.

Author disclosure: Dr Goldman has the following relevant financial relationships with commercial interests to disclose: Speakers Bureau: Novo Nordisk, Xeris, Amarin, Abbott Diabetes Care Inc, Lilly; Stock: Novo Nordisk, Lilly, Abbott Diabetes Care Inc

Authorship information: Analysis and interpretation of data; concept and design; critical revision of the manuscript for important intellectual content; drafting of the manuscript; supervision.

Address correspondence to: jennifer.goldman@mcphs.edu

Medical writing and editorial support provided by: Jeannette Y. Wick, MBA, RPh, FASB, FASCP

REFERENCES

  1. Vettoretti M, Cappon G, Acciaroli G, Facchinetti A, Sparacino G. Continuous glucose monitoring: current use in diabetes management and possible future applications. J Diabetes Sci Technol. 2018;12(5):1064-1071. doi: 10.1177/1932296818774078
  2. Rahimi B, Nadri, H, Afshar HL, Timpka T. A systematic review of the technology acceptance model in health informatics. Appl Clin Inform. 2018;9(3):604-634. doi: 10.1055/s-0038-1668091
  3. Lanning MS, Tanenbaum ML, Wong JJ, Hood KK. Barriers to continuous glucose monitoring in people with type 1 diabetes: clinician perspectives. Diabetes Spectr. 2020;33(4):324-330. doi: 10.2337/ds19-0039
  4. Haak T, Hanaire H, Ajjan R, Hermanns N, Riveline JP, Rayman G. Flash glucose-sensing technology as a replacement for blood glucose monitoring for the management of insulin-treated type 2 diabetes: a multicenter, open-label randomized controlled trial. Diabetes Ther. 2017;8(1):55-73. doi: 10.1007/s13300-016-0223-6
  5. Beck RW, Riddlesworth T, Ruedy K, et al; DIAMOND Study Group. Effect of continuous glucose monitoring on glycemic control in adults with type 1 diabetes using insulin injections: the DIAMOND randomized clinical trial. JAMA. 2017;317(4):371-378. doi: 10.1001/jama.2016.19975
  6. Beck RW, Riddlesworth TD, Ruedy K, et al; DIAMOND Study Group. Continuous glucose monitoring versus usual care in patients with type 2 diabetes receiving multiple daily insulin injections: a randomized trial. Ann Intern Med. 2017;167(6):365-374. doi: 10.7326/m16-2855
  7. Bergenstal RM, Tamborlane WV, Ahmann A, et al; STAR 3 Study Group. Sensor-augmented pump therapy for A1C reduction (STAR 3) study: results from the 6-month continuation phase. Diabetes Care. 2011;34(11):2403-2405. doi: 10.2337/dc11-1248
  8. Bolinder J, Antuna R, Geelhoed-Duijvestijn P, Kroger J, Weitgasser R. Novel glucose-sensing technology and hypoglycaemia in type 1 diabetes: a multicentre, non-masked, randomised controlled trial. Lancet. 2016;388(10057):2254-2263. doi: 10.1016/s0140-6736(16)31535-5
  9. Charleer S, De Block C, Van Huffel L, et al. Quality of life and glucose control after 1 year of nationwide reimbursement of intermittently scanned continuous glucose monitoring in adults living with type 1 diabetes (FUTURE): a prospective observational real-world cohort study. Diabetes Care. 2020;43(2):389-397. doi: 10.2337/dc19-1610
  10. Fokkert M, van Dijk P, Edens M, et al. Improved well-being and decreased disease burden after 1-year use of flash glucose monitoring (FLARE-NL4). BMJ Open Diabetes Res Care. 2019;7(1):e000809. doi: 10.1136/bmjdrc-2019-000809
  11. Gilbert TR, Noar A, Blalock O, Polonsky WH. Change in hemoglobin A1c and quality of life with real-time continuous glucose monitoring use by people with insulin-treated diabetes in the Landmark study. Diabetes Technol Ther. 2021;23(S1):S35-S39. doi: 10.1089/dia.2020.0666
  12. Polonsky WH, Hessler D, Ruedy KJ, Beck RW; DIAMOND Study Group. The impact of continuous glucose monitoring on markers of quality of life in adults with type 1 diabetes: further findings from the diamond randomized clinical trial. Diabetes Care. 2017;40(6):736-741. doi: 10.2337/dc17-0133
  13. Greenwood DA, Howell F, Scher L, et al. A framework for optimizing technology-enabled diabetes and cardiometabolic care and education: the role of the diabetes care and education specialist. Diabetes Educ. 2020;46(4):315-322. doi: 10.1177/0145721720935125
  14. Hirsch IB, Miller E. Integrating continuous glucose monitoring into clinical practices and patients’ lives. Diabetes Technol Ther. 2021;23(S3):S72-S80. doi: 10.1089/dia.2021.0233
  15. Rodbard D. Continuous glucose monitoring: a review of successes, challenges, and opportunities. Diabetes Technol Ther. 2016;18 Suppl 2(Suppl 2):S3-S13. doi: 10.1089/dia.2015.0417
  16. Bailey TS, Grunberger G, Bode BW, et al; American Association of Clinical Endocrinologists (AACE), American College of Endocrinology (ACE). American Association of Clinical Endocrinologists and American College of Endocrinology 2016 outpatient glucose monitoring consensus statement. Endoc Prac. 2016;22(2):231-261. doi: 10.4158/EP151124.CS
  17. Danne T, Nimri R, Battelino T, et al. International consensus on use of continuous glucose monitoring. Diabetes Care. 2017;40(12):1631-1640. doi: 10.2337/dc17-1600
  18. Draznin V, Aroda VR, Bakris G, et al; American Diabetes Association Professional Practice Committee. Glycemic targets: standards of medical care in diabetes-2022. Diabetes Care. 2022;45(Suppl 1):S83-S96. doi: 10.2337/dc22-S006
  19. Image provided by Jennifer Goldman, PharmD, RPh, CDCES, BC-ADM, FCCP
  20. 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 targets for. Diabetes Care. 2019;42(8):1593-1603. doi: 10.2337/dci19-0028
  21. Fitts E. 2019: a year of time in range. diaTribe Learn. Published May 18, 2020. Accessed May 25, 2022. https://diatribe.org/2019-year-time-range
  22. Isaacs D, Cox C, Schwab K, et al. Technology integration: the role of the diabetes care and education specialist in practice. Diabetes Educ. 2020;46(4):323-334. doi: 10.1177/0145721720935123
  23. Edelman SV, Cavaiola TS, Boeder S, Pettus J. Utilizing continuous glucose monitoring in primary care practice: what the numbers mean. Prim Care Diabetes. 2021;15(2):199-207. doi: 10.1016/j.pcd.2020.10.013
  24. Mensh BD, Wisniewski NA, Neil BM, Burnett DR. Susceptibility of interstitial continuous glucose monitor performance to sleeping position. J Diabetes Sci Technol. 2013;7(4):863-870. doi: 10.1177/193229681300700408
  25. Glucose management indicator (GMI). JEAB Center for Health Research. Accessed May 25, 2022. www.jaeb.org/gmi/
  26. Espinoza J, Xu NY, Nguyen KT, Klonoff DC. The need for data standards and implementation policies to integrate CGM data into the electronic health record. J Diabetes Sci Technol. 2021;19322968211058148. doi: 10.1177/19322968211058148
  27. Simonson GD, Bergenstal RM, Johnson ML, Davidson JL, Martens TW. Effect of professional CGM (pCGM) on glucose management in type 2 diabetes patients in primary care. J Diabetes Sci Technol. 2021;15(3):539-545. doi: 10.1177/1932296821998724
  28. Omoloja A, Vundavalli S. Patient generated health data: benefits and challenges. Curr Probl Pediatr Adolesc Health Care. 2021;51(11):101103. doi: 10.1016/j.cppeds.2021.101103
  29. Ye J. The impact of electronic health record-integrated patient-generated health data on clinician burnout. J Am Med Inform Assoc. 2021;28(5):1051-1056. doi: 10.1093/jamia/ocab017
AJMC Managed Markets Network Logo
CH LogoCenter for Biosimilars Logo