From Consumer Electronics Show (CES) 2018 Digital Health Stage, Anand Iyer, Ph.D., MBA, well known digital health guru delivered a keynote presentation focused on how artificial intelligence (AI) and machine learning are increasingly infusing digital health tools with the power of, if not more than, prescribed medications.
He began by floating the idea of using software within a digital therapeutic like a drug—a healthcare tool that would be prescribed, available in a digital formulary and have demonstrated health and economic outcomes.
Through his presentation he weaves in the use case of diabetes. He describes how digital therapeutics, like WellDoc’s BlueStar, that he has been integrally involved in innovating, have the capacity to play a significant role assisting in the care and control of people with type 2 diabetes. Iyer notes that diabetes is at pandemic levels globally.
Using diabetes treatment as his case example, he discusses how we, especially now, have plenty of meters, monitors and a plethora of new medications in our treatment armamentarium. But, even with the power of this bevy of tools, we aren’t improving diabetes care or lowering A1c levels sufficiently – including individually or collectively.
He poses this question: Are we trying to solve the wrong problem? He asserts that for all chronic diseases, we’re not getting the right data, to the right people at the right place and at the right time.
Iyer goes on to show how WellDoc’s BlueStar is designed to solve this essential problem with three key elements in its platform that works in conjunction and simultaneously with one another.
- Personalized coaching: Provided at the point of care, specific to the person based on personal parameters and inputs. This capacity to personalize enables contextualized learning based off of real time data.
- Smart Visit Report: This patient generated report provided by the patient to their provider offers key information about where the patient was, where they are and what’s changed from the last contact. This report assists providers to optimize treatment through clinical decision support and regularly updated evidence-based recommends guide decisions.
- Population management portal: Allows from small provider practices to large healthcare systems to manage a population of people with diabetes.
Due to built-in AI and machine learning BlueStar is able to provide the user with three critical elements of chronic disease management – motivation, confirmation and affirmation.
Iyer next details the five Vs in utilizing data to develop and optimize digital health therapeutics:
He then discusses the I-D-E-A model and how the data one gathers from AI and machine learning has the potential to become the value proposition in digital health.
- I – Inform
- D – Discover
- E – Extrapolate
- A – Adapt
Iyer defines machine learning as an adjunct, a multiplier to people and providers trying to manage chronic conditions that are data-centric, like diabetes. He notes machine intelligence and the power of computing can help everyone involved in healthcare to use technology to reach higher and further – beyond our current capabilities. And using this power, as WellDoc recently demonstrated with Truven Analytics we can convert AI into economic return.
Iyer concludes this keynote stating that data science and the power of machine intelligence is only one of the necessary ingredients to move the needle in the management of chronic diseases. The other critical ingredient for success is the engaged patient. Digital therapeutics have demonstrated increased engagement of patients in their care.
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