According to the International Diabetes Federation , in 2021, 53.7 million adults in the age group of (20-79) years had diabetes. Around 1.2 million children and adolescents (0-19) years have type 1 diabetes.
Diabetes is a chronic condition that can lead to serious health problems like vision loss, heart disease, and kidney disease. Hence, diabetic patients require constant self-management to regulate their condition daily. It is inevitable to use technology such as digital apps and Data Analytics to improve health management and care facilities.
Several technology giants have developed different software platforms to facilitate the healthcare industry’s needs. AI and analytic tools are crucial in making diabetes management a reality!
The patient suffering from a chronic diabetic condition needs to check blood sugar level frequency. With smart glucometers, patients can save every reading to their smartphones. These glucose readings can also be shared with the physician for the patient’s medical history study. With the help of data analytics, it is now easy to understand the body sugar level patterns and instantly understand body health statistics.
Smart glucometers are in sync with cloud-connected Apps that constantly monitor patient readings. The patients are then connected with diabetes experts, who guide them in better health choices and precautions.
IBM Watson Health and Medtronic had built and launched the ‘IQCast’ feature within Medtronic’s Sugar that helped predict blood sugar events. The diabetes assistant app allows patients to interact with continuous glucose monitors.
Machine learning and pattern-recognition algorithms-powered solutions analyze insulin data, blood glucose levels, food logs, and hypoglycemia episodes to give personalized reports to patients. These insights reveal important health trends that forecast the patient’s glucose levels and help control them.
AI and machine learning systems have the capability to analyze multiple signals received through body sensors. This technology assesses diabetic patients with a low, medium, or high risk of experiencing hypoglycemic events within the next 1-4 hours. The degree of predictive accuracy increases as a hypoglycemic event becomes more imminent.
These Data analytics technologies not only predict events but also analyze the patterns and suggest to patients some proactive steps that help prevent them. Adjusting the content of meals, the timings of the consumption of meals, and adjusting the insulin dose helps to achieve this goal.
The glycemic index is a commonly used parameter where a value is assigned to food items based on how much these items can contribute to a patient’s blood glucose level and how fast. This index can be quickly calculated by digitally mentoring devices that significantly help patients with type 1 diabetes (T1D).
The technology performs continuous glucose monitoring (CGM) function and keeps a close tab on insulin pumps through hybrid closed-loop (HCL) systems. This system can deliver automated basal insulin through an algorithm and real-time CGM sensor to align with the body’s glucose levels.
Based on Grand View Research, in 2021, the market for global diabetes devices was valued at USD 26.7 billion and is expected to expand with a growth rate (CAGR) of 8.2% from 2022 to 2030. The increased need for digital technologies in diabetic care indicates a new era of diabetes care facilities for patients.
AI and Data Analytics have bought several useful medical devices in the market that offer life-changing benefits to patients and health systems. The improved quality of life of people with diabetes signifies that technology must continue modernizing for better patient access and utility.
Healthcare providers and technology giants must collaborate to generate further optimized and valuable healthcare systems.
Are you looking for better and enhanced analytics solutions?