The health care market is constantly growing, so medical device companies and other tech companies are investing in new ways to help adults and children with diabetes. We’ve asked an expert in the endocrinology field, Rajiv B. Kumar, MD, to answer a few questions and provide his expert opinion on the latest technology developments in the health care and diabetes markets. Dr. Kumar is the Medical Director of Clinical Informatics at Stanford Children’s Health and Lucile Packard Children’s Hospital, and Clinical Assistant Professor of Pediatric Endocrinology & Diabetes at the Stanford School of Medicine.
What do you see as one of the greatest wearable technology innovations in the health care market?
Although I am biased by my specialty, I believe diabetes is leading all other diseases in the development of wearable technology. No other chronic disease requires this much data on a daily basis. People with diabetes stick their finger with a needle multiple times a day to get the glucose data they need to dose their insulin injections. With the latest advances in Continuous Glucose Monitoring (CGM) systems, one can now passively receive 288 data points daily. This enhances disease intervention and management simply by providing way more information than possible with traditional finger stick meters.
Also, the latest technology allows one to share glucose information with their health care providers. This is vital for providers to understand glucose level trends in the context of activity, food patterns and medication. Historically, there was limited communication of glucose information between visits because it was very labor intensive for the patient, as well as the physician, to share the data. Instead, providers would change treatment plans at visits and have to wait three months to assess the results.
In response we conducted a pilot with our electronic medical records (EMR) system to facilitate passive data sharing via Apple HealthKit. We can now easily assess glucose information between visits permitting more face-to-face time with our patients at visits to develop customized treatment plans. Following successful completion of this pilot in the summer, we have expanded within our practice and anticipate broad adoption by other health care systems.
How does this tie in with the concept of precision medicine?
The definition of precision medicine is using a person’s data to create a customized treatment plan. We typically don’t have home blood glucose trends to assess between visits and can’t look at all preceding data during in-person visits. Now, we can transmit all information directly into the patient’s medical record. While interpreting data is a lot of work; with CGM and background analytics we have a better picture of what’s going on between doctor visits. We can really assess for changes quickly instead of playing catch-up every three months. This is very important for our pediatric patients who are constantly growing and changing with resultant fluctuating insulin needs. Passive data and analytics allow for enhanced understanding of our patients facilitating more precise treatment plans.
You mentioned Big Data – besides the individual patient, what else can this data be used for?
The ability to assess home blood sugar trends in the EMR facilitates population health analytics. We’ll be able to assess for subgroups of patients across the country who have optimal blood glucose trends. We can evaluate the treatment practices for glycemic control in those groups including medication dosing styles, in addition to geographic variability and other variables, with resultant positive outcomes. Then we can adopt those best practices to help everyone on a wider scale.