Using AI to analyze unstructured data

The Mayo Clinic’s IT department is at the forefront of making AI more accessible for the organization’s clinical healthcare processes and decisions as well as the business overall.

“We have a strong belief that in the next decade there is going to be a lot of medical cures from leveraging data and so we think of two ingredients that are essential to this innovation,” said Dr. Vishwanath Anantraman, Chief Technology Officer at the Mayo Clinic.

The first ingredient to the Mayo Clinic’s innovative approach to data accessibility is to scale the data in a way that makes it accessible to as many people as possible. Of course, it also needs to remain secure as well. This is known as “under the glass” because of its high degree of privacy.

The second ingredient, and perhaps more important, is to structure the data so that it is more usable to those who actually need it. Currently, 80% of the data collected in healthcare is unstructured, according to Anantraman, and, therefore, not easily usable for clinical or business decisions.

Anantraman also believes that IT leaders need to find a way to democratize AI. In other words, lower the barrier for understanding the data without highly specialized training in statistics or computer science. Anantraman credits working with big names such as Google and Microsoft to help bring AI to the people who need it. Ultimately, the goal is for doctors or nurses who only have a few minutes between patients to have access to critical information to help them solve clinical problems.

Thus far, the healthcare industry has not capitalized on embedding data into the day-to-day clinical workflow, but Anantraman sees embedding as the next step in the evolution.

Collecting data is not new to the healthcare industry. When it first began about a decade ago, machine learning and EMRs were highly disparate. Ten years later, systems can collect mass amounts of data from multiple sources and store it in the cloud, making the process less expensive to maintain. But the final step will be a shift in thinking for healthcare IT. Data should be accessible with minimal training, and without needing a business analyst or a PhD.

“With the speed at which we can do AI today, it is going to really drive a lot of interesting outcomes in the future,” Anantraman said.

Anantraman’s team at the Mayo Clinic is also focused on ensuring diversity in the collection and analysis of data. In order to do this, he recommends partnering with other hospitals and systems that can build upon existing platforms. For example, the Mayo Clinic platform, which launched about a year-and-a-half-ago, offers third party entities access to using and building upon its data collection processes.

The Mayo Clinic’s strategy leading up to 2030 is to “cure, connect, and transform healthcare” by finding new cures using data and AI via the power of its digital platform.

“We look at the consumer and producer and Mayo being mediator between them to create a multiplicative effect on transforming healthcare,” he added.

Anantraman will be presenting “Designing a Data-Forward Digital Enterprise,” at the ViVE event on Tues., March 8.

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• Maximizing the ROI of investments in healthcare digital transformation tools
• In a COVID-19 world, digital transformation of the workforce goes beyond clinical tools
• Embedding DEI initiatives into healthcare talent recruitment
• Building virtual care infrastructure begins with removal of perceived barriers
• Sutter Health staying agile to improve patient experience with digital automation

Jacqueline Renfrow is a journalist with more than 20 years of experience reporting on and writing about the intersection of healthcare, education, and retail with technology. Living just outside of Washington, DC, she enjoys exploring all that the nation’s capital has to offer with her husband and three children in tow.