10953_AI_Business_School_David_LePenske_FINAL_Custom_Custom

[AI Business School] [Define an AI strategy to create business value Transform business processes in healthcare with AI] [Why is there such a large opportunity for AI to transform the healthcare industry?] >>David: For all its illustrious history of important discoveries leading up to the capabilities of today, it's important to humbly recognize that the practice of medicine is still very much an art and a science. [David Le Penske | Insight Digital Innovation, Director, Healthcare & Life Sciences] There's more to learn than we've discovered, and patients don't all respond to treatments in the same way. Apart from identical siblings, there's no one on earth that's exactly like each of us. It's important for us to recognize, as well, that there are no two health systems in the U.S. that are exactly the same. From the 1,000 or more systems that comprise their infrastructure, to patient demographics and seasonal weather patterns, and socioeconomic and demographic information, there is also a corresponding art and a science to what is commonly referred to as big data. AI will have a very powerful role in not only helping us to understand more about our health and our providers, and how they're different, but it'll also help us readily determine the best healthcare journey for each one of us. [How do you set yourself up for success with AI?] There are a number of critical path success factors to consider. First, tight use case scope. Tight project scope in defining the clinical and business and technical success criteria up front is really paramount. We usually accomplish this through half-day envisioning sessions, similar to a Microsoft technology center meeting or briefing, where the business and clinical thought leaders are in the room and really define the success criteria for the project. Deeply understanding the end-user personas is the second key factor. Technology's increasing ability to produce more data for data's sake is really meaningless. Who is it going to benefit? What is the work flow? The art of big data is defining the end-user experience, and how those users will be able to capture and leverage that information for their jobs. Analyzing a wealth of information, and transforming that into meaningful, actionable, role-based views that patients and clinicians can both independently and collectively benefit from that improves the quality of care by delivering exactly what is needed, when it's needed is going to lower healthcare costs and improve patient outcomes. Third, minimum viable project velocity. I guarantee you that no healthcare provider is used to getting anything of tangible innovation value quickly and at a low cost. I refer daily to Azure as the greatest Lego set that's ever been invented. The modularity of the cloud, the tools, the capabilities to continuously improve. It's our job, collectively, to scope a successful starting point, or a minimum viable product, or platform, that we strive to deliver from an architectural white board to a first vertical slice of what could ultimately become a larger solution capability over time. We deliver the MVP, or the minimum viable product, or platform, in just six to eight weeks. Again, this minimum viable product takes a vertical slice of real data, transforms it from a source into the cloud, cleanses it. We apply analytics intelligence, and deliver a first modern, actionable, role-based end-user experience that the client can evaluate. Last, return on investment, or what I call, return on innovation investment. ROII is important because if you think about incremental investment, you're able to incrementally invest in smaller, very tightly scoped initial projects that drive innovation value at a much lower cost, and time to demonstrated value. This approach can help clients begin to see, touch, and feel innovation investment return in just six to eight weeks in a period of time. Demonstrating real innovation value, what I would refer to as micro-solving the real customer problems, with their systems, their data, fosters deeper collaboration and value. And incremental investment, and return at velocity also incrementally builds organizational confidence. Based upon success, additional incremental investment delivers corresponding value, and it's a reciprocal process. That's the value of true innovation. [Where can AI deliver the most value in healthcare?] There's never been a greater opportunity to meaningfully advance and transform every facet of health in the history of mankind than today. The last 20 years of refining global clinical data standards are now being leveraged by the most powerful data analytics and artificial intelligence capabilities ever. And it will have a profound transformational effect on the health and well-being of every single person on the planet at some point in their lives. Here are just a few examples of the magnitude of it. First, providing clinical decisions support. The world's population is aging rapidly, and the shortage of doctors and nurses continues to become more acute. The World Health Organization reports that 45% of member countries report to have less than 1 physician per 1,000 people. In the U.S., the number is 2.6 doctors per 1,000. As the population is rapidly growing older, we are typically consuming 80% of our healthcare needs in the last 20% of our lives. Artificial intelligence will help dramatically to augment this critical healthcare provider gap from early detection to diagnosis and prevention. Second, identifying future health risks at birth. Artificial intelligence is driving our capability to discover mutations in our DNA at birth. Every baby born in the United States, for example, is given a routine blood test to screen for dozens of potentially inherited medical conditions. Now, the U.S. Institutes of Health is exploring the use of DNA sequencing at birth to screen newborn babies for additional genetic abnormalities and disorders. Many of which, once identified, can be proactively treated to reduce or eliminate future health risks, which enable healthier lives at a reduced healthcare cost. Third, personal health assistants. We helped Becton Dickinson deliver Briight, a personal health assistant for diabetics. Briight is a free mobile application download on the Apple or Google Play Store. It allows patients to connect data from fitness, health management devices, and other applications, such as diet, nutrition, and fitness data. Briight has three user personas, which are really important. The patient, the caregiver, and the clinician, each with their own experience, offering different personalized experiences over time each day as part of the personal care team centered around each patient. Fourth, improving imaging diagnostics. Artificial intelligence has much sharper eyesight than humans do. Microsoft research has already published a case study on inner eye, where researchers are taking artificial intelligence to detect healthcare conditions, and potential risks from retinal scan images. Early detection of abnormalities in MRI and CT scans are precisely tracing margins for tumor removal. And those are just a few of the examples from an imaging perspective. And lastly, greater independence and living as we age. Artificial intelligence is going to provide more modular care that can add devices and sensors and relay information and provide reminders as our health state declines over time. Keeping us connected with our family, our caregivers, our providers, the health services we need, all at the right place and the right time. Artificial intelligence is going to help all of us live healthier and more independent lives, safely at home as we age. [How can artificial intelligence improve experiences for care providers and patients?] There are more and more studies today coming out on this. In a fairly recent New York Times article, researchers found that doctors spent nearly twice as much time doing administrative work as actually seeing patients. 49% of their time, and growing, is stuck in administration data entry, where just 27% of their time is actually treating patients. Not only are more doctors retiring, but I was just meeting with an Ivy League medical school recently, and they're seeing a decline in medical school admittance, and more dropouts as a result, because they want to become doctors and treat patients and save lives, not get stuck in data entry and antiquated clinical data systems with horrible tabular reviews. Leveraging cloud and machine learning platforms above and alongside aging heterogeneous health system infrastructure can compliment these legacy systems, and free up work flows.