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The below article provides an overview of the May 2019 New England Journal of Medicine “Big Data and the Intelligence Community – Lessons for Healthcare.” The full article can be accessed by subscribers through the New England Journal of Medicine website.
In an article for the New England Journal of Medicine, Dr. Kevin Vigilante, Booz Allen’s chief medical officer, Steve Escaravage, senior Booz Allen data scientist, and Mike McConnell, former Director of National Intelligence, describe what the intelligence community can teach the healthcare industry about big data and artificial intelligence (AI).
Over the last two decades, and especially following the September 11, 2001, attack, intelligence agencies have realized an urgent need to break down intelligence silos and rapidly integrate and analyze massive amounts of widely disparate data. The healthcare industry faces similar challenges in the massive volume, variety, and velocity of its data requirements. The authors discuss some of the strategies that could be used to help promote more data sharing between and within government agencies focused on healthcare. By following the data management best practices established by the intelligence community, these agencies will deepen data science capabilities and create a more open environment for using data management tools to ultimately drive better outcomes.
“Healthcare is lagging behind other industries in its approaches to data science, in part because it is relatively new to big data. By learning from the intelligence community, the health industry can accelerate progress and capitalize on existing innovations.”
Using tools and technologies such as data lakes, automation, algorithms, open-source software, and others, the healthcare industry can get more from the way it handles, protects, and analyzes data. AI capabilities, which are driving another wave of innovation in the intelligence community, can do the same for the healthcare industry. New breakthroughs in machine intelligence, natural language processing, deep learning, and computer vision can make this vision a reality – especially for federal agencies with massive amounts of health-related data such as the National Institutes of Health, the Veterans Administration, the Food and Drug Administration, the Center for Medicare and Medicaid Services, and the Centers for Disease Control and Prevention.
Better integrating and analyzing data within and across these agencies will bring significant benefits, and the acceleration of AI and deep learning capabilities in the last 5 years makes this possibility even more achievable. The healthcare industry will be well served by learning from those clandestine agencies that, like them, strive to keep Americans safe.
Artificial intelligence is being used to substitute for human intelligence in a growing number of tasks. Ceding them to machines will change our jobs, economy, relationships, and understanding of ourselves. Read More
Vast amounts of data are becoming available for precision medicine, giving us the potential to make quantum leaps in our understanding of disease and how to treat it. But so far, we’ve had only a limited ability to use all this big data—much of it is scattered in countless isolated databases that have been difficult to bring together to get the big picture. Read More