Grand Rounds Recap: Is Continuous Glucose Monitoring Revolutionizing Diabetes Care?
Continuous glucose monitoring (CGM) has increased eight-fold in usage in the United States in the last decade, and it is estimated that 50% of patients with Type 1 diabetes use a CGM device. Although we see CGM increasingly in mainstream media and advertising, the American Family Physician reported that it is not ready for widespread adoption in Type 2 patients. Yet, many endocrinologists feel CGM is the greatest advancement in Type 1 diabetes since the discovery of insulin. Should more diabetes patients be utilizing this digital health tool?
In UCSF Department of Medicine Medical Grand Rounds, “Is Continuous Glucose Monitoring Revolutionizing Diabetes Care?” Aaron Neinstein, M.D., Associate Professor in the UCSF Health Division of Endocrinology, Vice President of Digital Health for UCSF Health, and Senior Director at the UCSF Center for Digital Health Innovation (CDHI) discusses how technology and data are transforming care, empowering patients and providing physicians with detailed data about their patients’ health.
In his presentation, Neinstein cited two cases where CGMs worn by his patients over a 14-day period allowed him – and his patients – to leverage the data and gain insight into their health.
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80-year-old Type 2 (insulin) patient: Data from CGM showed glucose levels dropped every night. This led to medication adjustments, which resulted in a decrease in hypoglycemia from 18 to 3%.
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70-year-old Type 2 (not on insulin) patient: CGM data showed the same patterned spike in glucose levels every morning. The patient was able to identify the foods causing the spike, which would not have been possible from fasting glucose levels and a fingerstick.
Key Highlights
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With digital health technological devices like CGM and access to their own health data, patients are empowered and in the driver’s seat of their care. By seeing their data, patients are learning, leading to more meaningful conversations with their care team.
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Studies show there are significant disparities in CGM use depending on geography, race and ethnicity, and education level.
Some reasons for disparity include: Physician bias contributes to disparity, as there is a misconception that only people who already have good diabetes control should get access to technology. Additionally, there are payor barriers requesting several documentation requirements.
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CGM has enabled closed loop insulin delivery in the last five years. An algorithm between the CGM and insulin pump allows the device to adjust the insulin pump’s delivery to keep the patient’s glucose within target range and prevent hypo- or hyperglycemic events. As the devices are not fully autonomous, we are not yet at the stage of the artificial pancreas.
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By leveraging technologies like CGM, endocrinology is one of top specialties using telehealth.*
With about 37.3 million Americans – 11.3% of the population – living with diabetes, and prevalence rising, transformation is needed in how patients manage their health.
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Instead of adopting a one-size fits all programs, we should create more personalized programs targeted at individuals’ risks.
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While studies have shown CGM is effective in driving behavior changes, there are still some questions that need to be answered, such as:
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Neinstein recommends physicians encourage CGM for patients with Type 1 and 2 diabetes on insulin as it has already revolutionized care for people on insulin therapy. Studies have shown CGM use in Type 1 diabetes leads to lower A1C and less hypoglycemia, and improves the quality of life.
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For people with Type 2 diabetes not on insulin or who are prediabetic, Neinstein recommends using CGM as a revolutionary biofeedback tool to enable self-learning and to treat it like a science experiment by trying different foods to see what the outcomes are.
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Digitizing CGM allows ecosystems to emerge, where digital clinics are leveraging CGM data to change the care model and to experiment.
According to Neinstein, CGM is a window into transformation in healthcare and that medical specialties should ponder how they could leverage their own continuous biometric device data. By capturing data, treatment plans could be more personalized based on individual needs and allow for tailored coaching and support for patients to better manage their health.