Best of both worlds: ADA pairs its database to the computing power of IBM Watson Health
What do you get when you pair the world’s largest database on diabetes metrics with a big data super computer that will mine, analyze and optimize that data?
(To view the full Diabetes Report, click here.)
Well, we’re going to find out. This summer, the American Diabetes Association and its 66 years of diabetes intelligence partnered with IBM Watson Health around a long-term collaboration to bring together the cognitive computing power of Watson and the Association’s vast repository of clinical and research data.
“By combining the Association’s enormous body of valuable data with Watson’s cognitive computing capabilities, we will empower people living with diabetes, clinicians and researchers with better data and better insights, which ultimately can lead to better outcomes,” suggested ADA CEO Kevin Hagan.
“As the science of diabetes advances, big data presents a tremendous opportunity in diabetes care and prevention,” noted Kyu Rhee, chief health officer at IBM Watson Health. “But patients, caregivers and healthcare providers need access to cognitive tools that can help them translate that big data into action, and Watson can offer access to timely, personalized insights.”
“The American Diabetes Association is the ideal partner for IBM, [and] our collective goal is to provide the motivation, the tools and the insights to transform clinical care, self-management and accelerate scientific breakthroughs,” Rhee said.
The goal of the collaboration is to develop Watson-powered solutions that enable the diabetes community to optimize clinical, research and lifestyle decisions, and address important issues that influence health outcomes, such as social determinants of health.
For providers, the team plans to create a cognitive diabetes database to help inform treatment decisions and care management approaches. Healthcare providers could tap into personality insights through Watson to tailor their treatment approaches to the needs of an individual. Additionally, providers could identify and address potential risk factors for their patients by comparing an individual to population-level trends of patients with similar characteristics.
For patients and caregivers, cognitive tools for people living with diabetes or prediabetes could be developed to provide tailored information and insights, reflecting such individual factors as demographics, disease stage, treatment regimen and behaviors.