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Editor’s Note: This is part two of our two-part interview with Dr. Melek Somai. To read part one, click here.
Froedtert & Medical College of Wisconsin Health Network is an academic health system based in eastern Wisconsin. It embarked on a journey to foster disruptive innovations by establishing Inception Health as an independent vehicle to drive innovation and digital transformation, focusing on digital health technology.
Dr. Melek Somai is vice president and chief technology and product officer at Inception Health and Froedtert & Medical College of Wisconsin Health Network, and assistant professor of medicine at the Medical College of Wisconsin.
Yesterday, he discussed artificial intelligence across healthcare overall, focusing especially on generative AI (the kind found in the popular ChatGPT). Today, he talks about the AI work being done at Inception Health and Froedtert & Medical College of Wisconsin Health Network.
Q. Inception Health and Froedtert are implementing AI to streamline certain processes, such as scheduling, to enable patients to identify their best options based on their individual preferences, with an easy AI interface, removing the complexity of the traditional decision tree. Please describe how this system works and the outcomes you expect.
A. We see AI as having three phases. I’m simplifying here. There is this phase of small improvements. What I mean by this is, while we hold a lot of hope that the value of generative AI to transform industries is high, the path is not going to be linear. It’s going to require more capabilities, more resiliency, and, more important, more preparedness from health systems to be able to provide demonstrable and verifiable value for AI.
And that last mile is not going to be an easy mile, it’s going to be one of the hardest. So, in the meantime, we see AI can have some immediate benefits that we can safely implement. Today, AI has some great potential in a few areas.
You mentioned navigating our health system and helping patients with scheduling. We know that navigating a health system today is not easy. And as we continue to improve the experience of patients navigating our health systems, AI, and specifically the combination of large language models with API integrations, can help us provide a more intuitive and personalized interface for patients.
This has less to do with providing the information; it’s more of an interface for patients to interact with our services that we already have. AI implementation at that layer can help patients with patient check-ins for their upcoming appointments; for instance, helping them with identifying the best option for rescheduling an appointment, taking into consideration their preferences, or actually figuring out and summarizing from the huge value of data.
We have to provide a summary, for instance, about specific questions for the patient; about, for instance, the lab results or their preventive care visit when it’s due. So, at this level, I want to be clear here – AI does not contribute to the care of the patient, but is instead used as more of an intuitive user interface to our back-end services that we already have.
This type of innovation has the ability to streamline certain processes and help the patient better navigate the health system. However, AI at this level is not transformative, and honestly, we could consider these use cases as not compatible with the cost of building these AI models in the first place. However, integrating AI at this level can help with creating use cases and building some more capabilities as we evolve in a safe manner.
As we look at this from Inception, for instance, we are making sure that building these models is across using really appropriate frameworks that ensure governance, data safety and data security. And again, those models are built in a way to help navigate, so more of an interface layer. As I mentioned, another level of integration, and this is probably the level, what I call level two, that is helping scale healthcare recommendations. This is still experimental today.
Q. Inception Health is reviewing AI systems that provide personalized preventive care recommendations, integrating patient medical records, the US Preventive Services Task force guidelines and rules-based recommendations. What do you want to do with AI here, and what do you hope the outcomes will be?
A. This is another level that I mentioned about integrating AI and how it can help and scale healthcare recommendations. This is still experimental, but it’s placing AI much closer to the realm of clinical care practice.
This is the area where implementing an AI governance framework, most likely nationally, is going to be critical. At this level, you can think of AI as a copilot to a patient, helping them understand their options and their care recommendations. This work entails a few aspects.
The work we currently do includes making progress in terms of retrieval, augmented generation, integration, embeddings and prompt engineering to help us build personalized and customizable copilots for our patients. There are a few fundamental points that we are currently taking as an example to how we are building these kinds of experimental copilots.
One of the key elements here is that the patient data is stateless at this stage. What I mean by this is that the data is not used by the model to train itself and is never stored. It is transient and is provided to answer the question in real time. This model means that AI does not have any capability to learn from the data or even be aware that the data even exists.
This type of integration today ensures security, privacy and transparency. And this is a common approach that probably we will see for the foreseeable future, being used to develop more robust AI frameworks and infrastructure the same way we do it.
I’m really glad we have the recent executive order (from President Biden) on the safe, secure and trustworthy development and use of AI, which is a great example of such commitment. But there is certainly one of many steps that the private sector health systems need to develop over the course of the next few months and decades to ensure that we use this in a safe, secure and trustworthy development.
And this capability is going to be important to our patients. If you think about having the ability to summarize data from best recommendations, able to recommend but also guide the patient through that experience, that it still, with oversight and guidance from the clinician, is going to help streamline that relationship and improve the capability of our health systems.
Q. Inception Health is developing a digital first healthcare model where AI is central to scaling services and improving convenience. You are shifting the model of care where AI helps with the first mile of care delivery. Please elaborate on this model and why you think this is the approach to go with regarding AI.
A. This is what I call level three, the next level where AI is helping us reshape. This is for me personally one of the most exciting areas that my team at Inception Health and at Froedtert is really looking into. Not only having an impact on generative AI in the near term, but in the mid to the long term, having the ability to redesign the healthcare model to leverage generative AI and technology as a platform, rather than just a back-office solution.
The approach we are taking today is to think creatively and more fundamentally about the value of AI and generative AI technology in shaping the care experience. And the way we have taken this as a team is we built a user research group and developed a product mindset of thinking about where can a generative AI technology help us reshape the model we deliver.
So, one of our active scopes at Inception Health is leveraging our insights in healthcare technology with our capabilities as a healthcare delivery system to think differently and ask, What if?
What if we can deliver an experience that is not based around a patient visit to the provider office? Take the example of the COVID era, where we have seen a massive uptake of telemedicine. One of the reasons the telemedicine uptake has declined after COVID is we did not fundamentally change the workflow and the experience of the patient nor the provider.
So, changing the medium is not enough. And what we are working on is what we can bring with the power of AI to reimagine the healthcare delivery experience altogether. And one of the approaches we are thinking about is what if we deliver a digital first experience where AI is not only a copilot, but also the driver to help patients communicate more clearly and actually more conveniently with their healthcare provider and the health system?
This is an area that really is exciting because it’s going to help us bring value that is not going to be an additive value to the current healthcare system but is going to be a catalyst for value. Some of the values around decreasing cost of care, improving the convenience of our health systems, and improving the experience for our patients are going to be impacted greatly by this approach.
This is an area that is really important where I think we are leading this wave. We are collaborating with industry leaders in this space, and this is going to be probably one of the most fundamental approaches that we’re going to learn a lot about: How we can deliver those experiences to our patients.
This is an area where, I believe, technology combines with clinical care to solve the problem. This is going to be critical for us to be successful over the next decades in delivering on the promise of technology and generative AI in healthcare.
To watch a video of this interview that contains bonus content not in this story, click here.
Editor’s Note: This is the sixth in a series of features on top voices in health IT discussing the use of artificial intelligence in healthcare. To read the first feature, on 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, with Helen Waters of Meditech, click here. To read the fourth, with Sumit Rana of Epic, click here. And to read the fifth, with Dr. Rebecca G. Mishuris of Mass General Brigham, click here.
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