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Using Artificial Intelligence to Humanize Physicians Online
Episode

Steve Wasick, President at infoSentience

Using Artificial Intelligence to Humanize Physicians Online

In this episode, we are excited to feature Steve Wassick, President at InfoSentience, a company at the forefront of automating computer-generated analysis and communication. Today, Steve talks to us about his company, what it does, and how it can make a difference in healthcare. He also discusses how his technology is used in other sectors like sports and finances. If you’re in patient communication, population health management, or any niche in healthcare that requires dealing with huge data and creating customized reports, this is a must-listen-to episode!

Using Artificial Intelligence to Humanize Physicians Online

About Steve Wasick

Steve Wasick is the President at infoSentience. He is passionate about using technology to create content. Prior to infoScience, he was the President of S&W Capital. He was also an Analyst at Maguire Properties. Steve received his Law Degree from Northwestern University School of Law. 

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Saul Marquez:
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Saul Marquez:
Welcome back to the Outcomes Rocket, Saul Marquez here. Today, I have the excellent Steve Wasick on the podcast. He’s the president of InfoSentience. They’re at the forefront of automating computer-generated analysis and communication. And most recently, they’ve been applying their trade and tech into health care. And he’s here to talk to us about it. What exactly is computer-generated analysis and communication and how is it making a difference in health care? And obviously wanting to have everybody listening to this podcast think about what other applications this interesting technology can have to improve outcomes and and help us innovate our business processes. So with that, Steve, just really thankful that you’re here with us today.

Steve Wasick:
Thank you so much for having me, Saul.

Saul Marquez:
Absolutely. So you’ve been doing this for a while. And so I’m really curious what exactly this cutting edge technology is and how it’s being applied. You’re doing it in a lot of different other sectors and most recently in health care. So tell us, number one, what is it? And number two, what’s inspired your move into the health care space?

Steve Wasick:
Absolutely. So the easiest way to describe what we’ve built is we built the technology that can analyze any data set, figure out what’s important within that dataset, and then talk about it and write about it just like a human being would. So one of our products that I think is the easiest to understand is writing about live sports. So on CBSSports.com, we cover professional football, college football, basketball, European soccer, a bunch of other things. And basically, our system goes through the box score figures out what was interesting, and then writes up a report just like a human being. But there are all sorts of different reports. There’s a game preview, there’s a gambling focus preview, there’s a recap. There are quarterly updates, things like that. And because it’s automated, we can go really deep into the data. So it’s not just as simple as looking at the box score that used to appear in the newspaper. It’s going through the history between these two teams, every single play of the game, every single play for that team, for that season, looking at each individual player and their tendencies and what they’ve been up to, things like that can all be incorporated into the final content. But when you do something like that, that’s really complicated on the analysis side with every sort of complication that you add in that stage of the content generation process, like creating more and more possibilities of things that you can talk about.

Steve Wasick:
It creates a much more complicated system when you have to actually figure out what is the 15 sentence story going to be and how do we arrange it because there are some things that don’t make any sense to talk about at the beginning of the story, that only makes sense if other things have appeared in the story, other things that don’t make sense once you’ve talked about similar things in the story. So there’s a lot of really, really complicated aspects that go into writing that as at least an adult. If you practice writing for a long time, you just become second nature and you don’t even think about them. But there are some real, real complexities once you’ve made an analysis in actually translating that into natural language. But we think that it’s really important to be able to do that because human beings really like being able to sort of read a story as opposed to just getting a data dump. Right? like if you had somebody who was working for you and you asked for a report on something and they just came back with 20 bullet points, Right., it wouldn’t help them out if they said, well, these are all the things you need to know. They’re all right. Here are the twenty bullet points. That’s not how we like to get information.

Steve Wasick:
We actually like to get information that has sort of a beginning middle. And that has a couple of main points with context on that. And so even though we’ve done typically in the past, we started at least focusing on sports and a lot of people can do that. Just kind of think that that’s a fun thing to do. But really, the tools that are there that are within the system that we built can be applied to any dataset. And so we’ve done finance and now we’re doing how at least one health product, our first health product is actually doing automated doctor biographies. So we take information about doctors and then we can write up a biography for them, for large hospital groups that normally write these up manually. And a lot of times they don’t have all the doctors’ biographies written up. And also they’re not always updated, which isn’t great for SEO purposes and also for accuracy. So our automated system can just rewrite them all the time. And as they get new patient reviews, as they add new publications or whatever, or as they change locations, all of these things can then be reflected in their bio automatically, which hopefully allows people to get a better sense of which doctor they want to go to or what the qualifications of the doctors that they’re looking at are.

Saul Marquez:
Fascinating. Steve, you know, I’m just I’m thinking you and I have met already.

Steve Wasick:
We have?

Saul Marquez:
I’m thinking. I’m like, this sounds so familiar, Right., and so I’ll ask you, so were you ever in an office space in Chicago, like a shared office space?

Steve Wasick:
You know, I started this company in Chicago. It was never in a shared office space in Chicago.

Saul Marquez:
No?

Steve Wasick:
But I did start out in Chicago, although I think of our two competitors. Both of them are also in Chicago, too.

Saul Marquez:
Are they? So maybe it was one of your competitors that I met.

Steve Wasick:
Narrative science.

Saul Marquez:
Honestly, I don’t know, but that’s OK. But I’m like I swear, I’ve talked to this guy before and it’s like.

Steve Wasick:
We could have met in Chicago, so it’s definitely possible.

Saul Marquez:
Interesting. Interesting. OK, now that was just a side note. How could that have been Right.? Yeah, I was blown away the first time I heard about this capability and I was like, whoa, get out of here and you serious? You could go, you know, just analyze a bunch of data and then create content? I was just blown away. And so obviously this stuff is got some traction. There’s no doubt there’s an opportunity within health care with this. And so tell us a little bit about how you feel like what is the key opportunity here for our health care audience today, Steve?

Steve Wasick:
Well, I think I’d actually rely on your listeners, hopefully, to tell me, because I think we’ve really built up an expertise in the fundamental AI technology. But we definitely rely upon people who have domain expertise to really service those individual problems that could use our technology. I would say that some of the just general ideas that I think we can help out with is communicating with patients at scale. So if you have especially you don’t know the expertise level of people who you’re talking to. And so being able to communicate using natural language, something that people can just read as opposed to try to look at data or do things on their own or anything like that can really be a benefit because our system can go in there and really tailor the communications so that it’s not they’re not getting something that’s obviously boilerplate. That’s another thing that turns people off. If they’re just getting the same instructions that everybody else is getting, the same reminders that everybody else is getting, then it doesn’t feel like something that they really need to pay attention to. As much as if you can actually point to specific things within their dataset right. that they really need to know if you can talk about their history, about how they’ve been doing better about on a particular metric in order to help encourage them all these little touches that you could do so that it reads like something that actually their doctor took the time to build just for them, people are going to have a much better response to that than something that’s obviously just written for everybody. So I think that patient communication is an area that we can really help out with. But I think that there’s also a lot of things we can do on the business side of things.

Steve Wasick:
There’s a lot of reporting that has to be done within hospitals, within the medical field in general. And so I think that we can help out with that in helping to create reports and helping to analyze the financial side of health care and also building on what we’ve already got right now, which is we’re doing doctor biographies, but we think that there’s a lot of ways that we can inhibit those bios to do differently to serve different purposes. So we’re working on that and working on trying to improve our ability. So just from a marketing standpoint, to take that doctor biography information and repurpose it for different use cases, depending on what endpoint they’re trying to get their information out to.

Saul Marquez:
Yeah, makes sense. And so maybe it would help to understand what the sports companies are using it for the finance companies.

Steve Wasick:
Yeah, absolutely. So we have quite a few sports products, but the easiest one to think about is the one that we do for covering live sports. So with CBS, who we work with there, one of the largest sports sites in the country, they have a huge staff of people, but even for them, they’re not able to write up a preview for every single college basketball game in the country every week, for instance, because there are hundreds of them. And so they don’t have the time to cover every particular game and particularly from different angles. So we have gambling focused articles. We have just regular articles. We have recast. We have quarterly updates. Obviously, they’re not going to be able to do quarterly updates for every football game on the weekend. And so it’s really filling in the gaps, places where they’ve got human beings who are writing great articles, but they’re only covering X percent of the games. So they’re using our system to basically say, look, we’ve got coverage for every single game that’s out there and we’re in negotiations to add a lot more sports again, because they’re not able to cover all those. We’re going to be doing the WNBA, for instance, next year so that all those games get coverage. So it’s just really helping out to fill in those gaps. And I think that that’s, again, something that can translate pretty easily to health care, for instance, with the bios, like they write bios at IU Health, for instance, who are working. They have a lot of doctor bios, but most doctors don’t. They just don’t have they don’t have the personnel to be able to write up thousands of doctor biographies and let alone update them. So that’s where our system can come in and fill those gaps, where it’s just too difficult to have human beings do all this writing.

Saul Marquez:
Sure, yeah. It makes a lot of sense. It’s like high quantity things that need reporting or stories. And that’s why maybe you were thinking about this niche of patient communication where, you know, you have population health management, for instance, where you’re wanting to keep a group healthy, managing chronic conditions, for example. Like what exactly are you pushing out to these people? Maybe there’s a system in place that you are texting or emailing or working through voice assistance to just check-in. And maybe what you’re saying is that you can help personalize that message rather than make it boilerplate.

Steve Wasick:
Exactly.

Saul Marquez:
Gotcha. Cool. And then also on the other side, you have coverage like it sounds like a good piece of it is article writing. The opportunity might be from a content development perspective. And today, to earn trust, you really need to do it through content and adding value. And if you’re not doing it, you’re getting left behind.

Steve Wasick:
Absolutely.

Saul Marquez:
Yeah. OK, cool, cool. And so as you approach the field of health care, what would you say is, I guess the thing that makes you guys different, how is it that you would be able to to offer value to the listeners and, you know, think about it from the perspective of not just the hospitals and providers, but also companies in health care that are wanting to make a difference with patients, but also shareholders etcetera?

Steve Wasick:
Well, I think that our key competitive advantage is just the overall quality of the types of reports that we can build. So we’ve devoted a tremendous amount of time building up our AI technology as opposed to sort of building up our client list. And so we spent about five years building up a whole brand new system, and it really allows for a very high level of complexity. So if you look at the reports that we build on CBS Sports, for instance, I mean, these go directly onto the website and they need to stand up or they need to read as though they were written by a human being. They don’t want anything on that’s obviously robotic, that’s super repetitive, that’s sort of cookie-cutter, the same thing every time. We also have a report for the Chicago Mercantile Exchange doing commodity reports, which are very complex. So we have the capability to really deal with any issue, no matter how complex the data is. If you can basically we say if you can teach a human being to look at these numbers and then write up a report, then we can do the same thing. And I think that’s our big competitive advantage, really. Doesn’t matter how complicated the data is or how complicated the reporting or communication needs to be, our system can handle it.

Saul Marquez:
I love it. Yeah, it’s interesting. So, folks, if you’re hearing this interview today and you’re thinking, oh my gosh, this would be unbelievable, X because of Y because of Z, certainly let’s take advantage of the opportunity to explore this technology. So tell us where people could get in touch with you.

Steve Wasick:
Well, we do have a website,infosentience.com. My email is just my name with that after said SteveWasick@infosentience.com. Anybody can email me there. I think that’s about it. We don’t have I mean, I’ve got a LinkedIn page, but we don’t have a Twitter or any social media.

Saul Marquez:
That’s perfect.

Steve Wasick:
Somebody can just email me there and or go on the website and we do have an email address there as well. So that’s the easiest way to do it.

Saul Marquez:
Yeah. And I wanted to put that out there right now just because, hey, we’re talking about it. So you guys are looking for ways to leverage this technology. And folks, if you feel like there’s an opportunity to reach out, consider the technology that you’re using. Steve, what would you say is the biggest setback or thing that you’ve learned out of how it works and what people should keep in mind when considering it.

Steve Wasick:
Our biggest setback was just how long it took us to build sort of the recent version of the technology that we have. I started this company back in 2011, so it’s almost been nine years and came up with a pretty good technology that CBS actually picked up for their fantasy sports system. And it worked really well. And I was like, oh, I’ve got a new idea. And I just kind of figured it’d be six months or so because it was kind of it was just like an improvement on what I already built and ended up being just sort of just really, really complicated. And so I ended up being about five years to build the new system. And that was a big setback for us as a company, because sort of the whole time we were just sort of like a research project essentially disguised as a company, even though we already had technology that was out that entire time and producing millions of articles during that time period. We still are sort of hunkered down, trying to get the new technology built out. We definitely learned a lot from that. And the fact of the matter is, at the end of the day, even with our new technology, which is very, very flexible, any project is still going to have to be built from the ground up. Like every project is still going to require understanding the specific needs of that client, what they’re trying to communicate, what data points are important to them, where that data is located, whether there’s any public data out there that we can leverage to give the articles more context and more richness, all these things need to be built out every time. And I think that that we had sort of dreams of like having this A.I. that could kind of do this for anything. And it is more flexible than most. And it is it does help us in some ways to get a jumpstart on new projects. But at the end of the day, anything that we do, particularly in the health care space, is going to still need to be somewhat from scratch. And that’s OK.

Saul Marquez:
Yeah, yeah. But I mean, once you do the work, then that’s where the magic happens, right?

Steve Wasick:
Absolutely. Those you just press the button. So like within the fantasy space, which is our largest solar, our largest product in terms of scale, we produce more than well over a million unique articles every week when.

Steve Wasick:
More than a million every week,

Steve Wasick:
More than one million every week.

Saul Marquez:
That’s insane.

Steve Wasick:
Yeah.

Saul Marquez:
Wow, that’s insane.

Steve Wasick:
At DBS like at some point, we’re doing over five thousand a week. And so there’s there are some points where the majority of the content on CBS Sports is actually written by our computer during when all the sports overlap.

Saul Marquez:
Man, that is just unbelievable. I thought you were going to say a year and I was going to be impressed. You said a week. I’m like, what! that is unbelievable. And so then there’s a component of a to where you could look at numbers and garner some sort of analysis based off of those numbers too right.. So. Oh, absolutely, yeah. Like, hey, based of this data feed, here’s an article.

Steve Wasick:
Exactly. One of the things just to prove to your listeners I think that’s important is that I said that our technology is really great for situations where there are a thousand things that could happen, a hundred things that did happen. And you want to talk about the most important or interesting 15 right. So just to differentiate or explain when our technology is needed and when it isn’t, even if you have a really complicated data set, if you can boil that down to a couple of key numbers. You don’t really need our system Right. it’s really a case like in sports, for instance, you can’t say, OK, well, what was the one number? I mean, you can talk about, OK, this was the point total, but that doesn’t really tell the story of the game. There are all these other little components that go into telling the story of a particular football game, for instance. And so that’s the type of complex data sets where our system can really, really help out. And, you know, when you’re talking about patient data, talking about trying to set up communications for them, I think that that’s a lot of situations like that with patients, whether you’re talking about hundreds of data points in terms of testing information, in terms of the history of what they’ve been doing, in terms of all of their individual demographic information, all that all these things matter, and how many doctor visits they’ve had and what’s happened in those doctor visits. I mean, the data just piles up and start to really tell a coherent story about what they need to know or what’s important to them really requires doing deep, deep analysis and then also sort of picking and choosing what are the most important things that this person really needs to know. And then, of course, our AI can then arrange it into something that that reads like it was written up by their doctor.

Saul Marquez:
Very cool. So what are you most excited about today?

Steve Wasick:
I well, I’m excited to get to talk to you Saul, because I do hope that your listeners can hear this and come up with some ideas. It’s not even so much what the things that we’re thinking of that are that we’re excited about. It’s more that we’ve got this really great technology. And we think that as more and more people hear about it, that they’re going to come up with really cool ideas of their own that they’re going to talk to us about, and that hopefully, we can work on it.

Saul Marquez:
Well, the invitation is there, folks. Connect with Steve and find out more about what is possible. And that’s the only way you get things done as you figure out what’s out there and you explore the possibilities. And this is one that I’m very intrigued by. And you’re better than either Steve and I to come up with how you could use this. You’re dealing with the issues. You’re dealing with the opportunities. Reach out to see what it is that you guys could collaborate on. Steve, leave us with the closing thought. And you obviously already shared how you could get in touch with the listeners, can get in touch with you. But it’s worth repeating here.

Steve Wasick:
Yeah, I think people can get in touch with me at my email, which is SteveWasick@infosentience.com. And they can also go on to the website, which is www.infosentience.com. And I think as far as a closing thought goes, I would just say that I would just reiterate that I’d be really interested to see what people can come up with because it’s so exciting. I feel like every meeting that we’ve ever had with people where we tell the people who have problems within an industry where they hear about this technology really gets the wheels turning right. And they usually can think, OK, if I had one hundred human analysts, what could I do that I couldn’t do right now if I just had one hundred analysts that were working for free, what could I do? And, you know, usually, if you have that thought in your head and you think about it for a second, usually the answer is a lot. And so that’s the kind of fun part about our job and really that we’ve just sort of begun because like I said, we were kind of tucked away for many years and we’re just sort of getting out there and letting people know about what it is that we can do. And so it’s really exciting talking to people who are experts in their field and hearing about the particular problems that they have and figuring out ways to solve them.

Saul Marquez:
Yeah, for sure. Well, Steve, we appreciate you sharing this with us. I mean, it’s great to know the technologies that are available to better outcomes and business innovation. And we’re grateful that you’re sharing this with us today. And certainly, I look forward to hearing from the listeners and also reach out to Steve. He gave you how to do it. You could get the show notes, go to outcomesrocket.health and in the search bar type in infosentience and you’ll be able to find that or just type in Steve and all the info will come up. Steve, thanks again. Really appreciate you jumping on with us today and certainly rooting for you and the work that you’ve got going on.

Steve Wasick:
Hey, thanks so much, Saul. Really appreciate your time.

Saul Marquez:
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Things You’ll Learn

  • Analysis of huge data can be really complex and the result won’t make much sense to humans unless translated into something readable. 
  • Pointing out specific things in their dataset has a much better response from people. 

 

Resources

SteveWasick@infosentience.com

https://infosentience.com/

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