What does it mean to have a comprehensive vision when adopting novel technologies in your health facility? Onyeka Nchege, SVP and CIO of Novant Health, a four-state integrated network consisting of over 1,600 physicians throughout 15 medical centers and hundreds of outpatient facilities and physician clinics, weighed in during a recent conversation with Aidoc.
The conversation covered a wide variety of topics ranging from:
Below is the conversation* surrounding the impact of adopting healthcare AI with an enterprise-minded approach.
Aidoc: I’d like to understand what advanced your enterprise vision when it came to AI adoption. How as the CIO did you develop that amongst the leadership team and even the broader Novant team?
Nchege: At Novant, our approach when adopting technology is born with several goals in mind: patient care, patient engagement, quality and safety. One patient at a time. One community at a time. Everything we do is framed by that. How we created that was through the executive team, leadership team, management team and all 38,000 folks that exist within Novant health. We create forums that allow us as an organization to understand how to do things right from the start.
Aidoc: Let’s talk a bit on integration. The whole process can be very resource intensive and obviously there are concerns about data privacy that need to be addressed. Can you explain what is important for you to consider an implementation as successful? What are some things you like to see from providers and vendors that others in your position should consider?
Nchege: When it comes to integration, you’re right, “resource intensive” is the word that rules. I believe when implementing and integrating any technology, there are several things we’re looking at. A big one is ease. How easy is it to integrate this technology into the already existing footprint that we have? If it’s easy to integrate, it makes life better for us as an organization. So as I think about vendors who are creating solutions, it’s about creating them in such a way that I can take it, infuse it into my technology landscape, and be able to do so with minimal effort. I think we have to do it in a way that makes it easy for us to use.
When I download an app onto my phone, I don’t have to go through a whole lot of gyrations to start using it. It’s pretty intuitive, right? So the question for us is how do we get enterprise solutions at that same level where we can absorb them and start using them right away. A partner has to understand my technology ecosystem, meaning they need to spend some time understanding what that looks like and being part of the process.
Aidoc: Of course part of an enterprise-wide vision involves a facility-wide impact, meaning that multiple departments will see the benefits of a new technology being adopted into the hospital. On that note, can you explain the collaboration effort between different service lines and how to go about fostering that?
Nchege: I’ll give an example. Our institute leaders get together periodically to talk about what’s happening on the clinical front, and our technology teams are a part of these conversations. Even if we just sit in the back and listen, right, we get an opportunity to hear how the institutes are collaborating with one another and sharing ideas, and we start to hear “hey there are things we’re working on in this part of our organization, we’re wondering if this part can use or leverage that.” And we can make a connection for that. So I think it’s an opportunity to foster some of that collaboration and it happens organically within clinical spaces and is facilitated by organizations like a technology organization that gets to see everything happening in our enterprise and gets to be that conduit to bringing those conversations together.
Aidoc: I’m curious, from a healthcare leadership perspective, being the CIO, there are a lot of executives out there who feel that AI can make an impact or that it’s important for the future of healthcare, but some are slower to adopt. What would you say to someone who has skepticism? How did you or other colleagues overcome skepticism?
Nchege: When you’re talking about AI and the amount of patient data we have access to, I think there’s always a level of hesitancy you have when thinking “Hey, I’m going to hand off patient data to a chatbot..” I think there’s hesitancy that’s appropriate as you think about it, so when considering any new integration, you need to know the current situation: what are the pain points? Where is there room for improvement? Have conversations inside and outside your organization.
First identify those needs and then you have to talk to your peers. Find out what is working for them. Who are their trusted partners? What are they seeing from the implementation process? Whether AI or other new technology, you need to know its limits. What are the benefits? Then you have to test the technology. Testing will really help you evaluate if it should be operationalized or not and a good fit for your organization. Ultimately, the hesitancy is right because there is real access to data.
*This interview was edited for length and clarity.
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