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Connecting Data to Contextualize the Complex Diabetes Journey

Diabetes is a complex disease that affects over 37 million Americans, or 11% of the population, and increases the likelihood of other comorbid conditions, such as heart and kidney disease.1 The prevalence of this life-changing illness has steadily increased over the years from a median of 6.3% of the population in 2004.2 With this, there is ongoing research to develop treatments for diabetes and related conditions. However, as a largely self-monitored and controlled disease, there are vast amounts of data about the diabetes patient journey that can better help clinical researchers but normally is not readily available.

In honor of National Diabetes Awareness Month, we recently hosted a webinar with HealthVerity data partner Glooko, who offers a personalized remote patient monitoring platform for people with diabetes, that explored how the HealthVerity IPGE platform, an integrated technology and real-world data infrastructure based on the foundational elements of Identity, Privacy, Governance and Exchange, can reveal a more complete diabetes patient story. If you missed the webinar, here’s what it covered:

Collecting Data to Improve Care and Clinical Research

Glooko’s remote diabetes patient monitoring uses a single platform to sync with over 200 glucose meters, insulin pumps and pens, continuous glucose monitors (CGMs), and fitness devices, tracking over 100 billion health data points from more than 1 million patients, creating one of the largest diabetes databases. This wealth of data not only helps patients and their healthcare providers (HCPs) better monitor and control their condition, it generates insights that, with additional contextualization, can accelerate clinical research.

A Wealth of Diabetes Data

With a glucometer, glucose levels are recorded whenever a patient administers a finger stick, typically a few times a day. While this is valuable data, it’s only telling part of the story. CGMs track glucose levels continuously throughout the day without the patient having to do any self testing, providing longitudinal glycemic data for a fuller story. This allows patients, caregivers and HCPs to see the amount of time the patient is spending within appropriate ranges, if they’re experiencing nighttime hyperglycemia or if they’re spending too much time in the hyperglycemic range. It records this data, allowing care providers to see the average time the patient was within a healthy range over the course of years to better understand how the condition is being controlled, beyond A1C alone. With access to this continuous and longitudinal data, clinical researchers can better see the impact of interventions and improvements or setbacks over time.

In addition to tracking glucometer and CGM data, Glooko tracks insulin intake, both one-time bolus injections and basal units provided over the course of the day from an insulin pump. Carbohydrate intake is also captured by the insulin pump and through the Glooko mobile app that offers a comprehensive database of food items, both packaged items and prepared meals, for more detailed data. Additionally, Glooko captures data on activity levels, medications, weight and blood pressure.

All of this data in isolation is useful, but once overlayed shows a more complete story, which can be tracked over time to show health improvements, such as weight loss or lowered blood pressure.

Accessing This Valuable Data and More

The HealthVerity IPGE platform allows the vast Glooko data to be licensed along with other sources, such as medical and pharmacy claims, electronic medical records (EMRs), and lab results from the nation’s largest healthcare and consumer data ecosystem in a normalized, HIPAA-compliant and research-ready format for a variety of use cases:

Use Case 1: Device Advances and Improvements
Closed loop or automated insulin systems were a major advance for controlling type 1 diabetes. Using the data from CGMs and pharmacy data for insulin and GLP-1 receptor agonists, researchers can apply predictive analytics and machine learning algorithms to improve model performance.

Use Case 2: Health Economics and Outcomes Research
With the rise of value-based care, new medical therapies and interventions need to demonstrate cost effectiveness to gain reimbursement and coverage support from payers. Using CGM, medical and pharmacy claims, and hospital chargemaster data, you can demonstrate the link between improved health outcomes, such as time within an acceptable glycemic range, and lower healthcare utilization, including reduced hospitalizations, fewer comorbidities and complications, and improved medication history.

Use Case 3: Clinical Trial Site Selection and Patient Recruitment
CGM data and other data from the HealthVerity Marketplace can help speed up clinical trial site selection and patient recruitment by identifying patients matching trial inclusion and exclusion criteria and the physicians treating them. As an example, if you’re looking for patients experiencing nighttime hyperglycemia, CGM data would reveal this outcome. Understanding the target patient population prior to trial initiation can also help with designing strong secondary endpoints and sub-cohort analysis to reduce trial length and costs.

There are at least 42 factors affecting blood glucose, making solving problems in diabetes and other comorbid conditions complex. By converging data from Glooko and the ever-expanding HealthVerity data ecosystem, you can accelerate clinical research and develop advances in diabetes treatment for the millions of people affected by this disease.

Click here to schedule a demo to see how you can access this valuable diabetes data.


1 Centers for Disease Control and Prevention (CDC). National Diabetes Statistics Report.

2 CDC. Prevalence of Diagnosed Diabetes.

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