Business Intelligence Is Easier to Implement Than AI, Says Highlands Oncology Group’s Jeff Hunnicutt

In this interview from the Association of Community Cancer Centers’ 49th Annual Meeting and Cancer Center Business Summit, Jeff Hunnicutt, CEO of Highlands Oncology Group, discusses the difference between business intelligence (BI) and artificial intelligence (AI), including process implementation and data compilation.

Transcript

Can you discuss what BI-enabled technology is and how it is used?

BI technology is business intelligence. Essentially, it's advanced internal analytics inside of your practice. Many applications that we deal with on a daily basis, we'll have kind of canned reports that will sit inside. They are useful inside of that application, but frequently, you want to be able to answer more difficult and advanced questions that involve multiple data sources. Business intelligence allows you to grab those data elements from different data sources, bring them into 1 platform, and then throw a visualization tool on top of that so that you can answer more complex questions and really be more efficient running your practice.

How does BI data analytics differ from AI, and what are the potential implications for oncology?

Compilation of data for business intelligence is a much easier endeavor than, say, [AI]. Now, AI is kind of an umbrella term where you have a lot of different technologies that sit underneath that, but the more advanced components of AI—things like deep learning—those take months, if not years, to even compile the amount of data and then have the engine ingest it and figure out what to do with it.

BI, you're gonna have an upfront lift of, say, interfacing technologies to get them into a central repository. But after that, it's really just running the reports and doing your analysis. I'd say it's significantly easier to get BI off the ground than a more complex AI model.