According to a Centers for Disease Control and Prevention (CDC) report issued last year, 100 million Americans today are either living with diabetes or prediabetes. Additionally, researchers have found that as many as one-third of those who are living with prediabetes (a condition that, if untreated, will ultimately result in the development of Type 2 diabetes) are unaware they have the condition. Even more concerning is the fact that 25 percent of U.S. citizens with diabetes do not realize they have the disease. Altogether, diagnosed cases of diabetes cost the U.S. approximately $327 billion every year. More importantly, the disease can drastically lower both the quality and length of life of those people who have it.
With new cases of the disease appearing every year and the price of healthcare showing no signs of abating, the U.S. government is taking steps toward reducing the incidence of diabetes with the launch of programs such as the National Diabetes Prevention Program. Likewise, nonprofits such as the American Diabetes Association, the American Medical Association and the Ad Council joined forces to develop and release helpful public service announcements to enhance awareness of the illness and to help people determine how likely they are to develop diabetes based on their family history and lifestyle.
While these actions are important, one valuable tool not to be underestimated in the fight to diagnose, treat and prevent diabetes is the Convergence in Healthcare movement. While not yet a mainstream idea, this integrative approach to medical research has already led to the development of a number of new technologies and concepts that could help change the future of diabetes.
Smartphone apps for better diabetes management
The efficacy of the Convergence in Healthcare movement can already be seen in the confluence of Big Data and biomedicine. It’s through the convergence of areas such as Big Data, device and diagnostics, modeling and biotech that companies such as Welldoc are able to design groundbreaking smartphone applications — think BlueStar — for people with diabetes.
BlueStar is a SOC 2 certified, FDA Cleared Class II medical device for people with Type 2 diabetes used via a smartphone app. BlueStar learns about a patient’s condition as the app is used. It also tracks patient data, acts as a coach to help users make better lifestyle and dietary choices to maintain more control over the condition and offers relevant in-app education for diabetes patients from qualified medical professionals. Additionally, the data collected by BlueStar can be easily shared with a patient’s physician so the time a doctor spends with a patient can be more useful and informative.
Smart devices for easier day-to-day living
Another way Convergence in Healthcare could change the lives of diabetes patients in terms of daily disease management stems from the intersection of smart devices and drug therapy. Via wearables or implantable sensors, forward-thinking research scientists are experimenting with technologies to would allow diabetes patients to more easily monitor and maintain their blood sugar levels.
One of the most exciting developments in this area is the idea of injectable “smart” insulin. This long-lasting form of insulin could theoretically enter the body via injection or pill to act independently of human control, regulating blood sugar based on the body’s needs in real time. Though recent articles suggest human testing of smart insulin (also known as glucose responsive insulin, or GRI) is still several years away, this form of drug therapy could ultimately reduce incidences of both hypoglycemia and hyperglycemia in diabetes patients. Additionally, it would eliminate the need for multiple insulin injections over the course of a day and could reduce the need for patients to count carbohydrates to maintain normal blood glucose levels.
Big Data analytics tools to enhance diabetes research
Besides leading to advances that give patients an increased ability to manage their diabetes on a day-today basis, Convergence in Healthcare could also help medical researchers gain a greater understanding of the disease, which could ultimately help improve treatment and possibly prevent it from developing in the first place. Unfortunately, diabetes is a complex illness that does not have one single, identifiable cause. Instead, diabetes develops as a result of a number of different factors and conditions in each patient that work together to create dangerous blood sugar levels. To understand the illness in any meaningful way would require the collection and synthetization of vast amounts of both active and passive data from a large group of people living with diabetes to identify trends and commonalities between dissimilar groups of people.
Through the convergence of life science, Big Data and information technology, this information could be easily collected through implantable sensors that monitor a wide variety of factors, both internal and environmental. Deep-learning algorithms could be applied to the data to discover new insights leading to health breakthroughs in diabetes as well as other chronic diseases such as heart disease or cancer. Big Data could also help scientists better understand the genetics of people who do not develop the disease in order to design therapies that could act as protection against the development of Type 2 diabetes.