Health IT leaders are accountable for identifying and implementing technology to support the health system’s mission and teams. They are also strategic leaders tasked with looking ahead and problem-solving alongside their C-suite colleagues.
Becker’s asked several IT leaders what they’re doing to set their systems up for success in the future during conversations for the “Becker’s Healthcare Podcast.” Here are their responses.
Yasir Tarabichi, MD, Chief Health AI Officer at MetroHealth and CMIO of Ovatient (Cleveland): We are making sure we have a solid AI governance strategy and plan, and the right people with a diverse set of experiences at the table. We are also upskilling our clinicians on what new technologies can and can’t do, and empowering them to speak up when the technology isn’t working the way it’s supposed to be working.
We will continue down that road, and we’re being really careful about the life cycle of all these solutions. We are ready from a financial responsibility perspective and even from just an overall governance perspective to say a tool or solution isn’t working and we need to decommission it. There’s a natural assumption that more technology is always good, so we have to keep balancing that out.
We’re also focused on making sure we are getting what we pay for and that we’re not making anything harder than it has to be from the AI perspective. From the virtual care perspective, we’re just keeping our heads down and trying to build a solid solution and product that really scales well. The most important thing I’ve learned in that space is that you can build the most exquisite piece of technology and platform that is seamlessly integrated into other EHRs or solutions, but what’s driving our energy and positive results is the people we’ve hired. We’ve continued to make sure that people understand our culture and that they’re a good culture fit. We’ve gotten a lot of positive responses from patients about the stellar care they’ve received with our services.
Omar Kulkarni, Vice President and Chief Transformation and Innovation Officer at Children’s Hospital Los Angeles: We’ve established a really great process around technology evaluation. It’s not just looking at vendors and solutions out there, but what we do is understand the current process, determine whether that process is a place we feel is ready for innovation, and if it is, what the core problem is we’re trying to solve. Then we work with stakeholders to figure out what within those problems are the most important problems and which are the ones that will result in a return on investment.
Then we go find innovative technologies that solve those problems and build a robust toolkit pathway around identifying innovation solutions. There are so many amazing solutions out there that it can be really easy to be distracted by the next great thing you get pitched. Having the discipline around looking at the process, looking at readiness, looking at problems and prioritizing it is really what we think about the ultimate goal, which is picking a handful of projects we think are going to deliver maximum value across our organization with the maximum amount of adoption.
We’ve been able to put that process out there, and that process is really going to help us in the future to continue to make disciplined decisions as it relates to innovation.
Sarah Pletcher, MD, Chief Digital Health Officer at Houston Methodist: We are making really pioneering investments and implementing them. We’re also really trying to remember to look a bit further ahead. With all the challenges everyone’s facing, you do have to strike this balance between keeping your eye on the current operational design performance and also looking ahead to get in front of where things are going. It’s thinking about how we’re struggling to cover certain shifts and we have to push our current team to cover them; you’ve got to cover the shifts today. But that is also an opportunity for us to look ahead and say how can we redesign this to have a more sustainable workforce for this particular thing?
The key is leaning into the bets we already made, focusing on keeping current operations high performance, and looking at all of our challenge points as opportunities to try to think further ahead about what transformation opportunities we have to centralize, automate, be more precise, think differently about how we deliver supply and demand, break free of the of the tyranny of integers. We have to staff in ratios, we have to staff in 120 hour shifts, we can only staff per unit, etc., and recognize that with these modern tools, we can deliver services very differently.
It’s trying to keep your eye on the now, but also looking ahead.
Deepti Pandita, MD. Vice President and CMIO of UCI Health (Orange County, Calif.): We have two big projects. One is bringing everyone on a single EHR platform, which we are working fast and furious towards to have a big bang go-live in December. The second is getting a handle on all of our AI suite of offerings and then working with our EHR vendor to make sure we are highlighting, leading and implementing all of those solutions. At the same time, we are standing up AI governance frameworks that assign clear accountability, ethical standards, compliance and trust in those systems. There are two parallel things going on there.
AI implementation is not just about the model. It’s not like reaching out to the vendor and getting an AI model. It still at the heart of it goes back to the key principles of informatics, which is people, process and policy, and technology. The systems that will invest in clinician buy-in, robust AI governance with multiple stakeholder presence, workflow integration, they are the ones who are going to see success in deployment of AI and expect gains rather than systems that are just implementing AI because it’s available.
Cheng-Kai Kao, MD. CMIO of UChicago Medicine: We talk a lot about the use of AI growing and there are more companies, and more use cases here and there coming up as we speak. Some say that people with AI may replace people who don’t know how to use AI. Maybe in the future there will be even more AI and automation in the work.
What we want to do is make sure we evaluate the AI literacy in our institution. We want to train people to know how to make the best use of AI. AI is not perfect. Training them to understand what the posting counts, what’s the limitation, what does it mean by AI hallucinations.
In the meantime, we want them to leverage AI as their most inexperienced intern. Someone on your team, almost like your digital worker, but who is inexperienced, who is new to the team. How do you train the AI to actually work with you to get things done more efficiently? That will be the goal we hope to convey to our colleagues.
I’m working on building up a generative AI platform that will be HIPAA compliant and secure for internal use, meaning our staff and healthcare providers will be able to upload certain information about patients and be able to use it to do things, like draft messages that we are about to send out in different formats and languages, in different types of literacy levels, which allows them to help improve some of the patient communications.
