Craig Kwiatkowski, senior vice president and CIO at Cedars-Sinai, and his team have pushed the renowned health system into the realm of artificial intelligence.
Their crowning achievement is the AI-powered virtual primary care app Cedars-Sinai Connect. Launched in fall 2023, the app has increased primary care capacity by 11% – the equivalent of building three new clinics. It has helped more than 6,900 patients – from San Diego to Sacramento – access care through more than 9,200 virtual visits.
But that’s just one of AI’s achievements. Kwiatkowski, who holds a doctorate in pharmacy, is tech-savvy, looking for ways to improve outcomes, enhance patient and provider experiences, and reduce clinician burnout.
The following is the eighth interview in our series of leading voices in health IT discussing AI. In this part one, we chat with Kwiatkowski about his views on hot topics in the AI in overall healthcare. Tomorrow, in part two, we will discuss AI projects at Cedars-Sinai.
Ask. How do you decide whether to build or buy AI, and what are the biggest challenges in integrating AI technology into existing systems?
ONE. The build versus buy question depends on the situation, and we start by looking at each problem with fresh eyes, trying to understand the problem we’re trying to solve. And where possible, we want to find solutions within our existing systems and platforms.
So we’re an Oracle shop for our ERP and we’re an Epic shop for our EHR. If workflow is enabled in one of those platforms, we will typically work with that functionality where possible. And those and other major vendors are building a good roadmap of tools, and we want to lean on those where possible.
An example could be from Epic. We are starting to use in-cart message response technology, which others are also using, where drafts will be queued for the doctor to edit and send further.
Another feature we are starting to implement is the ability to summarize charts, which uses AI to organize all the information in the chart and start course notes or maybe even discharge notes . In those vendor solutions, what we’re trying to address is physician burnout and well-being.
If that problem isn’t solved well by one of those platforms or solutions, we’ll look for other vendors to support the solution and we’ll consider whether to build something ourselves that or not. There are obviously a lot of variables in that decision, and there’s probably too much to say here, but in terms of topic, the main variables will center on capacity and resource availability, feasibility and efficiency.
Sometimes we can bribe our acceleration. Ambient documentation solutions are a good example. We won’t try to build it ourselves. That would be too difficult, too time-consuming and too expensive. But sometimes we are willing to invest and build when we see a gap in the market or if it makes sense for us to do it ourselves.
DIY gives us more control and flexibility to create something that suits our specific needs. I think as much as we’d like to think and people in general in the health care field like to think that we’re getting to a point where health care is standardized and scalable, there’s still a lot of regulation. Native processes and workflows aren’t always worth buying, or you buy them and you still end up spending a lot of time on local configuration.
So there’s probably always going to be some kind of trade-off there.
The second part of your question is integration and workflow. I’ve alluded to that, but the more we can do to incorporate these tools into existing workflows, the better off we’ll be. Frankly, cutting them out of their workflow is not smart, certainly from the physician’s perspective. No separate logins, no parallel ports or dueling screens, no extra keystrokes, ideally fewer keystrokes.
And that is what will lead to success in integrating and adopting these solutions in the short and long term.
And sometimes these solutions, like it or not, just require asking redesign the workflow. There’s no way around it, in some cases. And so, in those cases, we need a good “why” story and all the necessary change management measures to support those who will be most affected on the front lines.
Q. How are patients and clinicians responding to these tools, and can more healthcare work be done to accelerate use or expand adoption?
ONE. We’ve been using AI for many years, primarily in the machine learning and rule-based forms, and we’ve had a lot of success incorporating those types of tools in our workflows and adoptions. effective in all types of use cases – predicting patient risk, deterioration, length of stay, patient flow.
But consider the newer one innovative AI tools, it’s still very early days. I think we’re taking a thoughtful approach, like most people around the country, in validating these tools to ensure they’re safe and effective. We are focused on organizing our approach around the FAVES principles: fair, appropriate, valid, effective and safe. And make sure we understand how these tools work and perform in the short and long term.
That being said, there are a lot of things we are still learning in the first rounds. And we’re testing whether these tools work or not. And a few examples I mentioned. Are the draft basket notes complete? Are there any keywords missing? Where can context be lost? Where can additional information be inserted that was not originally there? People who hallucinate are aware and want to take precautions.
We’re intentionally limiting adoption a bit, proceeding with caution to ensure we’re deploying the solution in a safe and responsible way, which is also really helpful from an adoption perspective .
As we build the trust of our early adopter community, they can become evangelists who help share the story of how these tools work, how they help, and where we There might be some chance. Having colleagues who can share that information is very helpful. We already know that word of mouth is an extremely powerful tool to speed up or slow down adoption.
But there’s certainly a lot of interest in these tools and excitement about their potential. Frankly, I don’t see a silver bullet to solve many of the challenges we face in the short term, but there’s incredible potential with these tools, these synthetic tools, in the middle. and long term. So it will be interesting to go through those.
To read part two of this interview, click here.
Editor’s note: This is the eighth in a series of articles featuring leading voices in health IT discussing the use of artificial intelligence in healthcare. To read the first article about Dr. John Halamka at the Mayo Clinic, click here. To read the second interview with Dr. Aalpen Patel at Geisinger, click here. To read the third part, with Meditech’s Helen Waters, click here. To read the fourth part, with Epic’s Sumit Rana, click here. To read part five, with Dr. Rebecca G. Mishuris of Mass General Brigham, click here. To read part six, with Dr. Melek Somai of Wisconsin’s Froedtert & Medical Network, click here. And to read part seven, with Dr. Brian Hasselfeld of Johns Hopkins Medicine, click here.
Follow Bill’s HIT news on LinkedIn: Bill Siwicki
Email him: [email protected]
Healthcare IT News is a publication of HIMSS Media.
