How to Improve Blood Sugar Control Using New Tech Data

Health tech devices (e.g., continuous glucose monitoring systems [CGMs], insulin pumps) are increasingly popular among people with type 1 diabetes (T1D). They provide many benefits in terms of diabetes management, including reduced burden, improved quality of life, less time spent in hypoglycemia and improved blood sugar levels over time (HbA1c).  

While these technologies could potentially help to adjust treatment with more precision, the loads of downloadable data stored into devices can turn out to be intimidating for users. 

However, the ability for users to remotely upload data and share it with their healthcare teams before appointments is a timesaver, as it helps professionals to analyze the information and adjust treatment between appointments, as needed.

But how does this really work? Is this information easy to download and analyze? Are more resources needed? 

One study was recently conducted to answer these questions by collecting data among a group of 138 adult patients of an Australian hospital. 

No easy feat!

The study found that while approximately 80% of participants did upload their data to platforms such as Clarity (Dexcom), Glooko (Omnipod, Tandem) and Carelink (Medtronic), less than 31% looked at or analyzed their data before their appointments with their healthcare teams. What was the most common reason that participants gave for not analyzing their data? Because they cannot make sense of it. 

However, more participants who used both an insulin pump and a CGM reported that they analyzed their data (51%) than participants who either had only a CGM (31%) or only a pump (20%). This could be explained by the fact that analyzing CGM data without pump data, and vice versa, is more complex than analyzing both sets of data together. 

Resources for improved HbA1c levels and simplified analysis

Despite the complexity of the uploaded data, a vast majority of participants (approximately 89%) said they were very interested in reviewing and better understanding their data.

The study also showed that participants who did analyze their data had lower HbA1c levels, mirroring the results obtained in other studies that looked at algorithms developed to help people with T1D analyze their data and make their own treatment decisions.

This means that healthcare teams should make more resources available to T1D patients who wish to better understand and use their data.

You will find our tool to help analyze CGM data on the Support training platform

This tool will guide you through the process step by step based on three questions: “Did you have any hypoglycemic episodes?”, “Are there trends?” and “Does my blood sugar vary significantly?”. 

View the tool


  • Kong, Yee Wen et al. “Upload and Review of Insulin Pump and Glucose Sensor Data by Adults with Type 1 Diabetes: A Clinic Audit.” Diabetes technology & therapeutics, 10.1089/dia.2021.0558. 15 Feb. 2022, doi:10.1089/dia.2021.0558
  • Jenkins AJ, Krishnamurthy B, Best JD, et al. Evaluation of an Algorithm to Guide Patients With Type 1 Diabetes Treated With Continuous Subcutaneous Insulin Infusion on How to Respond to Real-Time Continuous Glucose Levels. Diabetes Care. 2010;33(6):1242. doi:10.2337/dc09-1481
  • Breton MD, Patek SD, Lv D, et al. Continuous Glucose Monitoring and Insulin Informed Advisory System with Automated Titration and Dosing of Insulin Reduces Glucose Variability in Type 1 Diabetes Mellitus. Diabetes technology & therapeutics. 2018;20(8):531-540. doi:10.1089/dia.2018.0079

Upcoming Event