Continuous glucose monitoring and the transformation of diabetes care

Nathaniel Heintzman, 12 Jul 2017

The revolution in health care wearables is coming to diabetes management. Accurate, continuous blood sugar data from cutting-edge glucose sensing technology, will substantially improve the quality of life of diabetes patients – and provide data for the better understanding and more efficient management of the disease.

The burden of diabetes: Personal and societal

Diabetes is a serious chronic disease in which the body cannot produce or use the hormone insulin effectively, causing an accumulation of glucose (sugar) in the blood. Diabetes is a critical and increasing worldwide public health problem. Approximately 422 million adults globally were living with diabetes in 2014, nearly double the prevalence of diabetes in 1980[1]. If this trend continues, by 2025 the number of adults with diabetes will surpass 700 million[2].

In addition to serious effects on personal health and quality of life, diabetes has a severe impact on global economic development. Worldwide direct spending to treat diabetes and prevent complications was estimated to range from USD 673 billion to USD 1,197 billion in 2015[3], with the United States alone spending USD 320 billion.

In normal human physiology, blood glucose levels are tightly regulated by naturally produced hormones including insulin. About 95% of people with diabetes have type 2 diabetes (in which sufficient insulin cannot be produced, and the body cannot efficiently use the insulin it does produce). Many millions of others are living with type 1 diabetes (in which insulin cannot be produced at all) or gestational diabetes (elevated maternal blood glucose during pregnancy). Many people with diabetes (and everyone with type 1 diabetes) must take insulin, and there are several different classes of non-insulin medications used to control blood glucose levels. Diabetes is unique among chronic medical conditions in that almost all day-to-day management decisions are made by the patients (or their caregivers) themselves, and not under direct supervision of healthcare providers.

Measuring blood glucose

All people with diabetes, especially those who take insulin, must monitor their blood glucose levels frequently. Uncontrolled blood glucose can cause short- and long-term health complications including dizziness, fatigue, nerve damage, organ failure, and even death. Living with diabetes requires constant decision-making about medications, exercise, and nutrition, as blood glucose levels are affected by these factors and many others including stress, sleep, and illness. Making matters more complicated, each individual’s glucose dynamics can behave quite differently, while standard diabetes management and care guidelines are often quite general. Thus, patients and their caregivers must make dozens of decisions each day regarding their diabetes management. Each of these decisions requires knowledge of the individual’s past and current blood glucose levels and a guess at how their blood glucose is likely to behave in the near future.

For decades, people with diabetes have had to prick their fingers with a needle to test their glucose levels with a drop of blood (the “finger-stick” or “finger-prick” test)[4]. The discomfort and inconvenience of finger-stick tests leads many patients to test only when they absolutely must. This results in very little glucose data being typically available to the people with diabetes making real-time therapy decisions, or to their caregivers and clinicians responsible for advising them on their treatment regimens.

The revolution of continuous glucose data

Today, however, glucose levels can be constantly measured and reported by a medical device technology known as a continuous glucose monitor, or CGM[5].

CGM systems include a body-worn electrochemical sensor attached to a transmitter, and a nearby device for receiving, analysing, and displaying the data (either a dedicated receiver or a compatible smartphone/watch). By providing real-time data throughout the day and night, these CGM systems represent a tremendous advance in diabetes care and allow people with diabetes to avoid dangerous high and low glucose concentrations and maintain lower average glucose values as measured by hemoglobin A1C (a standard laboratory measurement of long-term blood glucose levels). For people with type 1 diabetes, the benefits of CGM are immediate and sustained[6], and apparent whether insulin delivery is via an insulin pump device[7] or via multiple daily injections[8,9]. Because of these glycemic benefits, CGM has the potential to reduce the risk of acute and chronic complications (and their associated costs), thereby improving patients’ quality and expectancy of life (while reducing financial burden)[10].

Since the first CGM entered the market almost 20 years ago, measurement accuracy has more than doubled, device size and costs have been reduced, and patient and caregiver satisfaction with CGM therapy has increased. Consequently, the popularity of CGM is on the rise in the diabetes community. The global market for CGM sensors was USD 466 million in 2015, and is projected to reach USD 3,450 million in 2022, representing a 33.7% compound annual growth rate[11].

Reimbursement coverage for CGM technology is also expanding, both geographically and demographically.

In addition to providing glucose levels without a painful finger-stick, CGM shows the direction and rate of change in glucose levels, which is valuable information for making decisions about diabetes therapy. The system can be programmed to alert users when glucose levels are too high or too low, and the data can be shared in real time with remote healthcare providers or caregivers, offering additional safety for patients and peace of mind for their care teams.

Benefits of real-time measurements

This continuous stream of real-time glucose data can also be employed in a closed-loop system with an insulin pump to drive the automated delivery of insulin (the “artificial pancreas”), an endeavour being pursued by many companies and researchers around the world. Further, the frequency of glucose measurements (288 data points each day) facilitates more data-driven conversations between patients and their caregivers when they review CGM data during clinical visits. Cloud-based software allows care teams to view, interpret, and act on their patients’ data even between clinical encounters. The abundance of glucose data from CGM enables frequent and personalised fine-tuning of diabetes treatment regimens to an extent not possible with previous glucose measurement devices.

Indeed, CGM data can empower all stakeholders in the diabetes care continuum to improve patient outcomes and reduce costs. With CGM:

  • Patients and their loved ones can navigate daily self-management decisions with feedback loops for personal understanding of glucose response.
  • Clinicians can identify patients who need more attention and develop individualised precision treatment plans.
  • Those paying healthcare costs can deeply comprehend the efficacy of treatments to target care more efficiently and cost-effectively.
  • Health systems, private and public, can gain population-level insights on which approaches have driven positive impacts for different kinds of patients, and why.
  • Not surprisingly, then, many stakeholders in the diabetes community are eager to expand their access to and understanding of CGM data.
Big data and diabetes

Recognising the importance of collaborating broadly to solve diabetes with data, the market-leading CGM company (Dexcom Inc; San Diego, USA) has committed to moving beyond the status quo of siloed medical data by making CGM data available as ubiquitously as possible, while maintaining the security and privacy of personal health information. This approach is grounded in the development of a data platform that leverages best-in-class big data technologies such as Hadoop, Cassandra, Sqoop, Kafka, and Spark. These tools are well established for their scalability, speed, fault tolerance, and redundancy. They meet core platform requirements for security, privacy, integration, and adaptability, within a computing environment where regulatory and quality compliance are paramount.

Upon this platform rests a robust API (application programme interface) services layer. A cloud API facilitates industry-standard secure data-sharing and enables third parties to build their own software applications that add value and utility to CGM data in diverse ways. Interested parties will be able to freely access documentation and explore the capabilities of the API at Dexcom’s developer portal (https://developer.dexcom.com/). Notably, this API-based model of data accessibility respects personal privacy and ownership of data, as only individual patients can authorise third parties and their software applications to access their personal CGM data, subject to any other applicable regulations and policies.

This unique combination of CGM connectivity with a cloud API is ushering in a new era of integration, insight, and innovation around CGM data. The entry of CGM to the Internet of Things (IoT) enables novel, high-impact analytics on CGM data in the context of manifold types of data that are relevant to the management, care, and economics of diabetes. For example:

  • Analysing integrated CGM and cost data could determine the impact of glucose control on cost of care.
  • Integrating CGM data into electronic health record systems could facilitate the development of clinical decision support systems and aid in evaluating treatment and intervention efficacy.
  • Adding risk data could help to identify high-risk patients who need further support with their chronic disease management.
  • Combining CGM data with geolocation, exercise, diet, and other patient-generated data in apps could improve self-management and daily quality of life with diabetes.

All of these use cases, and more, are enabled by secure, privacy-preserving mechanisms for CGM data access, like the aforementioned API.

While most current users of CGM are people with type 1 diabetes, CGM use by people with type 2 diabetes is on the horizon. For example, Dexcom and Verily (Mountainview, USA; the life sciences division of Google’s parent company, Alphabet) are collaborating on next-generation CGM devices that maintain state-of-the-art accuracy and prolong wear time while substantially reducing device size and cost. These significant performance and cost improvements will further reduce the barriers to access to this increasingly prevalent and valuable technology.

As more research emerges to support the benefit of CGM therapy for all people with diabetes, and as insurers expand coverage of CGM to additional demographic markets, it is only a matter of time until continuous glucose data are recognised by all stakeholders as the key vital sign for the shared management of diabetes – and a key vital sign that should be opened to the ecosystem of diabetes innovation.

References

1. World Health Organization. Global Report on Diabetes. Isbn 978, 88 (2016).

2. Zhou, B. et al. Worldwide trends in diabetes since 1980: A pooled analysis of 751 population-based studies with 4.4 million participants. Lancet 387, 1513–1530 (2016).

3. International Diabetes Federation. IDF Diabetes Atlas. IDF Diabetes Atlas, 7th edition (2015). doi:10.1289/image.ehp.v119.i03

4. Clarke, S. F. & Foster, J. R. A history of blood glucose meters and their role in self-monitoring of diabetes mellitus. Br. J. Biomed. Sci. 69, 83–93 (2012).

5. Haviland, N., Walsh, J., Roberts, R. & Bailey, T. S. Update on Clinical Utility of Continuous Glucose Monitoring in Type 1 Diabetes. Curr. Diab. Rep. 16, 1–7 (2016).

6. The Juvevile Diabetes Research Foundation Continuous Glucose Monitoring Study Group. Sustained Benefit of Continuous Glucose Monitoring on A1C, Glucose Profiles, and Hypoglycemia in Adults With Type 1 Diabetes. Diabetes Care 32, 2047–2049 (2009).

7. Bergenstal, R. M. et al. Effectiveness of Sensor-Augmented Insulin-Pump Therapy in Type 1 Diabetes. N. Engl. J. Med. 363, 311–320 (2010).

8. Beck, R. W. et al. Effect of Continuous Glucose Monitoring on Glycemic Control in Adults With Type 1 Diabetes Using Insulin Injections. J. Am. Med. Assoc. 317, 371 (2017).

9. Lind, M. et al. Continuous Glucose Monitoring vs Conventional Therapy for Glycemic Control in Adults With Type 1 Diabetes Treated With Multiple Daily Insulin Injections. J. Am. Med. Assoc. 317, 379 (2017).

10. Toschi, E. & Wolpert, H. Utility of Continuous Glucose Monitoring in Type 1 and Type 2 Diabetes. Endocrinol. Metab. Clin. North Am. 45, 895–904 (2016).

11. Occams Business Research and Consulting Pvt Ltd. Global Continuous Glucose Monitoring System Insights, Opportunity, Analysis , Market Shares and Forecast 2016 – 2022. (2016).

Author

Nathaniel Heintzman

Director of Data Partnerships, Dexcom

Nathaniel Heintzman is Director of Data Partnerships at Dexcom Inc, where he leads efforts to support and expand the diabetes innovation ecosystem. Prior to joining Dexcom in early 2014, he directed the Diabetes Informatics + Analytics Lab (DIAL) at the University of California, San Diego (UCSD), where he served as faculty in the School of Medicine’s Division of Biomedical Informatics. Nathaniel Heintzman also has a long history of diabetes advocacy, including his founding role in Insulindependence and volunteering for other diabetes advocacy organizations.

Nathaniel Heintzman received his PhD in Biomedical Science from UCSD and his BA in Biochemistry and Molecular Genetics at Gustavus Adolphus College (St Peter, Minn), and his graduate and postdoctoral research in genomics and bioinformatics was published in Nature. Helives in San Diego, California and enjoys spending his spare time surfing, playing bass and keyboard in his rock cover band, and gardening.

Nathaniel Heintzman was a speaker at the "Health monitoring: Making sense of sensors" conference at the Swiss Re Institute's Centre for Global Dialogue.

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