Cloud has served as the cornerstone of digital transformation objectives; now, it's kind of old news, according to Bill Gillis, CIO at Beth Israel Deaconess Care Organization. At the recent CDM Media CIO Boston Summit, Gillis sat down with us to discuss his digital transformation objectives and current progress, both revolving around data and new technologies like AI and machine learning.
In this video interview, he explains how he's looking to AI and machine learning to help automate data processing and analysis and streamline business processes.
Editor's note: The following transcript has been edited for clarity and length.
How far along are you in your digital transformation journey?
Bill Gillis: I think that it's an ongoing journey. I don't know if the journey will ever end, particularly in healthcare. If I look back to when I started in health information technology 20 years ago versus where we are now, it's been a massive change in journey. And it sort of escalates as the years progress. We were involved in putting cloud technologies in our environment around 2006 or 2007 -- ahead of the game compared to most of the industry. But now, cloud is kind of old; it's the older thing. Now, it's about AI and blockchain and looking at how you can use those technologies to better improve your business. In healthcare, it's really around care management, cost containment and patient experience.
What digital transformation objectives or projects are on the docket?
Gillis: Right now, as an accountable care organization we're really deep in the analytics side of things. So, we gather a lot of data from disparate clinical systems and we have to aggregate that, validate it and normalize it. It's a pretty massive undertaking. So, we're really hopeful in looking toward AI and machine learning to help us streamline that process, because as the data grows and as we gather more data, the task of normalizing and validating it becomes more difficult. Our hopes are that the use of AI and machine learning can help streamline that process and allow our data scientists to work on the more challenging problems, as opposed to sort of the route manual processes we're doing today.
Check out another clip from our interview with Gillis that addresses his biggest digital transformation challenge: data.