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The Mayo Clinic Platform is chasing the perennial technology promise: of boosting innovation from a wide range of sources by reducing the burdens deof development, testing, integration, and administrative management. Jeff Wu, Vice President of Technology describes their platform as allowing ârapid iteration at early stages with non-production dataâ to âbuild trust over time.â They include a âdistributed data networkâ that collects data âfrom participants across the globe.â
One of the challenges Wu identifies with AI is the fragmentation of data concerning patients. Data tends to be collected when they have an incident that requires medical intervention, or come into the clinic for occasional visits. But technology is allowing us to collect data in between those times. âWeâre learning more and more about the types of data we need to collect.â But storing the data in a useful manner, and âputting the results in the hands of the physicianâ are the next challenge.
While clinical or pharmacological breakthroughs are the most exciting goals, Wu says that realistically, the most effective and âgreatest valueâ applications for AI currently are automating clerical and administrative tasks: âthe really boring things.â
The current model for deploying new technologies in health care isnât working, according to Wu, because each vendor requires contracts, integration, and change management. He contrasts the situation with an app store, where you download with a click.
The Mayo Clinic Platform hopes to alleviate the burdens for health care. An algorithm should run automatically when needed, without the physician having to think about it. In such a system, a start-up could address things that are bothersome for a medical discipline, but not big enough for Epic or the larger clinical institution to address. Wu says this these edge issues are where the biggest inefficiencies are.
When evaluating vendors, the Mayo Clinic judges three criteria. First is ROI: Is the solution worth pursuing? Seconds comes the technology: Does it fit with their systems in a manner they can trust? The third criterion, clinical or administrative, is the hardest. They have to determine whether a solution developed in another setting will be generalizable and work for them.
Watch the video for more perspectives on AI in healthcare and the Mayo Clinic Platforms approach.
Learn more about Mayo Clinic Platform: https://www.mayoclinicplatform.org/
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