How the Chief AI Officer at Children’s National is approaching clinical and administrative automation
Editor’s note: This is part two of a two-part interview. To read part one, click here.
Children’s National Hospital, in Washington, DC, is making strong use of artificial intelligence technologies in both clinical and administrative environments across the enterprise. While many hospitals and healthcare systems across the country have begun exploring piecemeal AI projects and limited use cases, Children’s National is somewhat ahead of the curve.
One of the reasons it has been able to go further and faster is because it has one person overseeing everything related to its artificial intelligence and machine learning technologies: Alda Mizaku, Chief Data and Artificial Intelligence Officer of Children’s National .
Yesterday, in part one of this two-part conversation with Mizaku, she shared how AI chiefs need a deep understanding of the technologies and clinical operations and need strong leadership qualities and effective communication skills so they can talk to a diverse group of stakeholders.
Today she gives a tour of the Children’s National Hospital’s use of artificial intelligence, delves deeper into an AI project she’s particularly proud of and its results, and educates other IT executives looking to become Chief AI Officer some tips for the trip.
Q. Please talk at a high level about where and how Children’s National Hospital is using artificial intelligence today.
A. We use artificial intelligence in a number of areas. From a broad level it is about decision support, looking at patients and creating efficiency, both in a clinical environment and in an office environment. We’ve also had quite a bit of success with predictive analytics.
By using AI, the organization’s goal is to increase our ability to make faster decisions when we talk about patients and diagnoses. We look at treatment plans and the steps that are part of those treatment processes to ensure that they are personalized and that we have an effective way to track and document the notes that are generated as part of those office visits and hospital visits.
We also look to optimize resource allocation and ultimately improve both patient outcomes and operational workflows. Most of our work in artificial intelligence currently focuses on that area.
Q. This time I hope to be a little more specific that you can describe and discuss a particular AI project that you are proud of and that is working well for the organization. What are some results you see? How did you supervise this project?
A. Something that I’m incredibly proud of and something that we’ve put into practice quite recently is in partnership with Microsoft, where we’ve engaged our engineering team and also worked with Microsoft technical experts.
The intention was to create and facilitate a rapid prototyping session. We wanted to build four rapid prototypes in less than two days. We hear the concept of ‘fail-fast’, so we wanted to work with the leading experts in this field to understand some of the ideas we were interested in and how successful we could be in building some of those prototypes to see if it would be effective in our daily work.
We had over ten departments that came and participated as part of that process, really creating team science. We had a great partnership with Microsoft. It was a successful initiative. We ended up building four prototypes in just two days.
One generally focused on being able to search documents such as policies and procedures and has changed the way people interact with data and information stored in policies and procedures. Instead of having to look at a document, you can ask the AI the question and get an answer back without having to do much searching. We were able to build a prototype around that.
We then focused on an area of the clinical space where we focused on notes generated during a hospital stay, and we created summaries of those notes with a different character in mind. A note that could go to the patient’s parents, a series of notes written in the patient’s language, it’s something they could understand.
Another that can go to the primary care physician, another that can go to our revenue cycle department so they can understand some of the billing aspects of what’s been delivered in healthcare. We’ve also done something we call Next Best Action, which is focused on looking at all the appointments that could follow the interaction and engagement we had with the patient, and merging them into a common list that can then be followed up .
If the doctor makes a recommendation to go to a specialist or come back to that office or perform a certain test, all that is collected by AI, making it very easy to find all the information recommended to the patient . We also looked at some very specific ways changing some of the alertness and alertness fatigue that was happening in healthcare and testing a system in that area to see what was possible.
Many opportunities and many ideas have emerged from that collaboration.
Q. What are three or four tips you would give to other IT managers looking to become Chief AI Officer for a hospital or healthcare system?
A. I have three or four that I can share. The first is understanding the clinical landscape and ensuring one has a deep understanding of the clinical workflows and the challenges in those workflows. That can be done in collaboration with someone in the organization, but that knowledge only helps to identify where AI can provide real value.
Another is about promoting collaboration. We talked about that yesterday too, so we’ve been building really strong relationships with clinical operations IT teams. This collaboration leads to a successful AI implementation.
Another is finding a way to stay current. AI technology is developing so quickly, so it can be challenging to keep up with all the latest developments and all the regulations and all the new things that we encounter every day. Finding a way to stay connected to new initiatives, new opportunities, some of the cutting edge technology and some of the compliance rules that are coming out.
Finally, it’s just an emphasis on responsible use and ethics. Just to prioritize the time it takes to really think about the deployment of AI and take the responsible use considerations and ensure patient data, privacy and security, so that they are always at the forefront, so that we can innovate and great technology, but do it safely and responsibly.
To watch a video of this interview that contains BONUS CONTENT not featured in this story, click here.
Editor’s note: This is the third in our series, Chief AI Officers in Healthcare. To read the first: an interview with Dennis Chornenky at UC Davis Health, click here. To read the second, with Dr. Karandep Singh of UC San Diego Health, click here.
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