How COVID-19 is Impacting the State of AI in Hospitals


During this panel, industry experts (showed above) discussed the impact of COVID-19 on AI on Hospitals. We’ve included a short transcription of the panel, beginning at 4:18 of the webinar.

Watch the full webinar here.

Christopher Hutchins, Northwell Health System: From an observational standpoint, COVID appears to be a catalyst for accelerating technology and analytics adoption. Is that your experience to date and how do you see AI adoption being impacted? Let’s start with you, Tawnya.

Tawnya Infantino, CommonSpirit Health: Absolutely, COVID-19 has been a catalyst. We were already working in this space prior, but what it really did was show us just how disparate our datasets were. As we came together as an organization, we had centralized data that was partial at best and then we also had a very decentralized model in the rest of our data. You can only solve problems when you have good data. 

A great example is: if we wanted to do any modeling and prediction in terms of an insurge of diagnoses based on symptoms that we’re seeing, you kind of need to know that the end diagnosis was COVID, right? So if you’re not using the right ICD-10 codes, if you’re not using all of the right markers and indicators, it’s really hard to model accurately. So what it has done for us is really shown us the areas that we need to focus on so that we can do good predictive modeling in the future and identify the right triggers for the appropriate place to make a big impact. 

With that focusing very heavily on that digital health platform and how we bring that data and we’ve had data scientists on staff for a while and we are seeing a surge of different consulting partners for speed to market, but we’re really looking at making this a core component of our organization.

Christopher Hutchins, Northwell Health System: Michelle, do you want to weigh in on that?

Michelle Stansbury, Houston Methodist: Sure. I definitely agree with Tawnya that data is key and that’s how it has been with our organization. We’ve had an enterprise data warehouse for several years with some data scientists. We’ve started down the path of working with AWS and really bringing in the machine power that we needed in order to analyze this data better. 

But I will tell you, during COVID we actually saw some of our innovation initiatives that we had started really take off. One was within our virtual ICU and the platform that we were using as we started off and I’ll talk a little bit more about it later in one of the other questions, but clearly it was a true success for us and really better over to predict deterioration of these patients from a virtual perspective. 

Having this remote monitoring that we put into place with a vendor that we were working with. As Tanya would say, it’s going to be key for any organization to really get a handle on their data and their data scientists because what is now happening with COVID is everyone is clamoring for the information and what we can learn about what happened during this pandemic and I will tell you, our researchers and our research institutes are just hungry to be able to get a hold of all of the data that’s being generated right now because of these patients we’re taking care of it. 

Tawnya Infantino, CommonSpirit Health: Michelle, are you finding that people are more ready to provide data and to open up data, whereas they weren’t before?

Michelle Stansbury, Houston Methodist: Yes.

Tawnya Infantino, CommonSpirit Health: Yeah. We’re seeing the same thing. 

Michelle Stansbury, Houston Methodist: I will tell you especially in the lab area, that was something that was very closed. I mean, we would share it just with ourselves. But now, lab data is very specific on what you absolutely need to be able to determine a lot of different predictions. And so yes, we’re now opening up that system a lot more to be able to share that data within other platforms that then allows data scientists to be able to use it and better facilitate the understanding of what we’re trying to understand.

Everyone’s trying to understand this patient population better and what happened and how can we better predict it so that we don’t have big masses of patients that flood us all all at once. So yes, I agree with Tawnya, it’s more that everyone understands now the importance and why we need it. Who would have known that we would ever go through a pandemic, right? But now that we have, how can we ever prevent it from happening again? 

And COVID is not going away. Not anytime soon. So the better that we can learn from this information, the better we’ll be able to predict the future and not have this surge of patients that we’ve had now. 

Christopher Hutchins, Northwell Health System: Sri, could address a couple different aspects, too, we’re hearing a lot about the criticality of having your data prepared and ready. Could you talk a little about the readiness aspect and how this is impacting the things as you see them? I’m sure you’re interacting with a lot of different organizations.

Sri Ambati, H2O.ai: Absolutely, and I was actually also curious how Northwell has been dealing with the transformation likewise. I would love to hear about what you have heard from Commonspirit and Houston. 

Christopher Hutchins, Northwell Health System: There are a lot of similarities to the last point in terms of being one to make data available. We had a burning platform and we had to get a lot of answers relatively fast to be able to manage search. We are licensed for roughly about 3,000 beds, but we were adding roughly about 200 a day as we’re approaching the Apex. And so there were a handful of folks from across the organization that all have oversight of the operational, financial, clinical quality from a number of different organizations. 

We were having these touchpoints on the fly constantly adjusting the models to try to make sure operations folks understood how many beds they need for for ICU, how many ventilators are going to need, how much staff, do we have enough PPE, how are we managing our emergency services in a very large network. That was really critical for us to have regular touchpoints. We had a lot of learnings with regard to how we’ve organized. We would come by acquisition over a number of years and a lot of our groups on enterprise platforms in the data structure are accessible some of them are not yet there. So we had to do a lot of things on the fly working directly with some of the vendors to get critical data to help them understand operations and workflow in those parts of the organization. It also is required from a state perspective, we had to report things with the public health. 

There were tons of lessons learned – Agile development on steroids I would say. We had DPS and executives on the phone at 10 o’clock at night, coming in and out of our meetings and grabbing their staff to add data elements to our feeds that typically would have been a political arm wrestling match but it was happening in minutes on the fly looking at the screen. It was amazing.

Learn more and watch the full video on YouTube: https://www.youtube.com/watch?v=e6s1TS0aiQ8&t


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