In this third session, Rebecca and Jim take their conversation further and will share how forward-thinking organizations are using data to unlock measurable savings and consistently deliver better claim outcomes. Let's dive in. 

Rebecca Morgan (RM): Hi, Jim. Great to be back with you for another episode.

Jim Harris (JH): I am really looking forward to this one Rebecca.

RM:   Me too. Today, we're taking the conversation a step further and looking at how data can do more than just guide decisions.

JH: Exactly. We're talking about how forward-thinking organizations are actually using their data to drive measurable savings and are consistently delivering better claims outcomes.

RM: It's not just about reacting to data anymore, it's about proactively using it to shape smarter strategies and get ahead of challenges before they become costly.

JH: And when that happens, the impact is real across cost, efficiency and overall recovery experience.

RM: Very true.

JH: So, let's kick this off and talk about how we're using data and analytics to help clients control costs and workers’ compensation and auto claims.

RM: It's amazing the impact you can have on a claim when you can see it going off the rails early. It's really about early intervention and getting those early warning signals, and for years we've had the ability to do that using predictive analytics, and such.

But we're in a world now where we've got a lot more in our toolkit, a lot. More technology that we can use to get these early warning signals. So it's about, understanding relatedness of the claim, right?

We want to make sure that we're looking at the related injuries and such. It's about understanding outliers. It's about understanding trends and those are the things, the insights that we work to draw out of data and analytics initiatives so that we can help to surface those to our clients to be able to control costs.

Now all of this is being enhanced by the use of, you guessed it, AI, to gather data from unstructured sources. For decades we've been using structured, relational data.

Now we can use unstructured sources. What do we mean by that? Narratives, medical records, claim notes, etc. We can use all of that. To draw out relevant insights.

Before, we would only know what a claim system could tell us about a claim. You send us this hundred set of fields and we'll work with those fields to try to surface relevant insights.

But now we can rely on this unstructured data. The sky's the limit to augment that information and provide these early warning signals. Jim, I know we've had a lot of success with that already.

JH: Yeah, at Enlyte we're so fortunate because we have so much data.

We have so many views into what's going on with the claims and I think it's imperative that we have an obligation to take advantage of that, whether it's the injured party’s demographics, the financial information from bill review, clinical information oversight through utilization review, there's a wealth of information and being able to pull all of that together really can help not only control costs, but really improve programs as well.

RM: All right. Well, Jim, here's a question for you. What are the main cost drivers you focus on from an analytics perspective to help clients better manage their claims?

JH: Yeah, like I said, bill review data is a wealth of information. Where you can see what are the treatment patterns that are taking place? Who are the providers that are providing the medical treatment and is it going the way you want to?

We look at a lot of things. We look at provider performance as far as what are they charging? How long are they treating? And being able to look at this within jurisdictions, within specialty. Even you know provider to provider on like diagnosis really gives us insight into who the best performing physicians are that we might want to utilize.

And then I talked before about the costs and trending and identifying the types of injuries that are occurring through the workers' comp and auto claims and coming up with strategies on how to help reduce that, partnering with safety groups and things along those lines.

And then ultimately looking at the claims themselves. Who are my outlier cases? Who are incurring the most expenses? And then what strategies do we need to put on these to help control those costs? Do we need a more experienced adjuster to set those reserves at the appropriate levels and manage that through? Do we need case management on it to help interface with the treating physicians and talk about strategies on moving them towards maximum medical improvement? Do we even want to use other things like surveillance or other things along those lines to help move the claims along? So really a lot of data, a lot of real-time data is needed and can really be utilized to help manage those claims.

RM: You know, Jim, I've heard you say this before that we have to look at it both prospectively and retrospectively. You got to look at a 360 view of this thing and throughout every step of the process, right, to get that full picture. Well, another question for you. How can clients use data to identify opportunities for cost reduction without compromising on claim resolution?

JH: Yeah, I think that's the key, right? You want to deliver the medical care that is appropriate for the claims, but you also want to help move them along. And I think there's a lot of things out there that you can use. There are treatment guidelines that are driven by data that can be measured against the success of what's going on with your claim.

You can also use data for trending as I talked about before. To see how your specific injured parties performing and treating and what's the durations on that. So there's really a lot of things that you can do. I don't think with any of them, you should worry about reducing the quality of the claim resolution because they're all tools that are in our customers' arsenals that are going to really help them make better decisions on their cases, hopefully bring them to earlier resolution and ultimately save money.

RM: You know, we've talked about this before. It's really incredible the impact you can have on the outcome of a claim by making some minor modifications early on gets about early intervention, right? Well, can you share any success stories where data-driven insights lead to significant cost reductions in work comp or auto claims?

JH: I’m going talk about something I think maybe all of us have seen first off. In our business we travel a lot. If you've been on an airplane recently, and you've seen a flight attendant, maybe a shorter stature individual, one of the problems they always have is trying to close those overhead bins. And if you notice, now a lot of them have tools that they can reach up and pull those bins without straining, stretching, hurting their back, hurting their shoulders, etc. And I can't say that I was directly involved in that, but I think that's a great example of that industry, the airline industry, looking at their types of injuries that are occurring for flight attendants and making changes.

One of the areas that I was involved in was working with a large hospital chain who was seeing a lot of injuries happening with their housekeepers. Two fold, a lot of them were getting injured when they were making the beds and stretching across the beds to fit those dreaded fitted sheets around the mattress.

There was also a lot of repetitive injuries to their backs, from stooping and bending as they were bending on their carts to get the towels or the sheets and the process of cleaning the rooms. And again, data was used to help identify increases in these types of injuries. Then we partnered again with our team on the ergonomic side making minor adjustments if they always are having to bend down to pick up towels, why not put the towels at the top of the cart and then they don't have to bend over. Little changes like that can make a big difference in ultimate reduction of costs in that you're preventing those injuries from happening at all.

RM: Well, that's the best way to manage a claim is to prevent it from ever happening in the first place, right?

JH: Absolutely, absolutely. If we want to talk about the future of data and analytics, where do you really see that evolving to for claims management over the next three to five years?

RM: Well, if you think about that for a minute, most of us have used, either in our personal or professional lives, ChatGPT or some other, generative AI chat tool. And it's very conversational, right? You just ask it questions and it answers in human readable text. It's incredible the insights you can get from these types of technologies.

Now expand that. This is a very realistic application of technology that's available today. We've got all of this data sitting out there in structured databases and then layering on top of the unstructured data, the medical records, the notes, etc.

Conversational business intelligence. I think that is one really important direction where this is going to evolve. If you think about instead of having to go in and create a data visualization or run a report or whatever particular business question you're trying to answer. With the advent of AI business intelligence tools more self-serve type questions will be answered. It won't be a matter of running a report, but I can just type into a ChatGPT-like user interface and just ask the question that I'm trying to answer. It'll be a lot quicker and easier than running the report, then going to sit and analyze. And what did this report tell me to answer that question. Data assets will become more conversational, including both structured and unstructured data.

JH: Absolutely. So what challenges do you think clients face when using data to control costs and how are we at Enlyte overcoming them as well?

RM: Yeah, too much data. That's what I would say is maybe the number one challenge. Too much data or data that's not quite clean the way everybody wants it to be, to look at it. Really there's a lot of great tech now that can help us overcome those challenges.

We use that structured data and layer on the unstructured, using AI prompting to draw out the relevant data. Another challenge that we have is data in multiple places. We've got so many different people who are touching a claim throughout a claims lifecycle, from the injured person to the nurse, the adjuster, the physicians, etc. They're all using different systems and we have to have a way to bring that data together. We've got tools like back-end data warehouses today. We here at Enlyte use Snowflake to bring all that data into one place. Just terabytes upon terabytes of data. And then integrating that data from system to system so that we can look across the entire claims life cycle.

The other thing that is a challenge that we all have to be aware of as we venture into this brave new world of artificial intelligence technology is hallucinations. We've heard about hallucinations, right? And how artificial intelligence can actually hallucinate an answer that doesn't actually exist. And so we've got to guard against that as we come into this new era. We can do that in a couple of different ways.

First of all, keeping a human in the loop. That can be done in a couple of different ways. We can have a human that validates that response from the artificial intelligence. Also, another way that we are looking at things is where we begin to automate certain functions. We have human oversight on at least a certain percentage of that function so that we can understand if the AI is starting to go awry a little bit.

And I think that AI is going to continue to evolve more and more. We're all gaining more and more confidence in it and it will of course continue to evolve. It's going to accelerate. It's going to rapidly transform our entire industry. But in the meantime, we're going to have to keep tabs on it. Keep humans in the loop and make sure that we understand what it's doing and approve of what artificial intelligence is doing for us. Which is going to be incredible in the overall process of managing claims.

JH: Yeah. And speaking of humans, I think one of the other challenges customers face is getting access to the data. Having to go here to this login or that and I'm really excited about Enlyte360 where customers can go to one place and really access all the different tools in one location. Making it easier for the adjusters, the customers to get to their data I think is another big challenge that they face. Making things actionable. Let's not just show it 'cause it's cool or pretty, but making sure that it's meaningful, ultimately to the end users as well.

RM: I’m really excited about that tool as well. We look at more and more integrated programs that are using solutions across the entire claims lifecycle. We integrate those programs on the front end like you're talking about and on the back end, all the data in one place. It just provides some amazing insights. 

Well, Jim, it's been another insightful discussion. I really appreciate you being here and helping us unpack how data is shifting from reactive to proactive.

JH: It's always great spending time with you, Rebecca. And, I think it's exciting to see how much potential there is when organizations start using their data more strategically.

RM: Absolutely. Today we explored how it's not just about looking back at what happened, it's about using data to shape what will happen. That shift is key to unlocking real savings and better outcomes across the board.

JH: Right. And you know, the companies that are embracing this approach, they're seeing the difference not just in their bottom line, but also in the overall recovery for their injured individuals.

RM: That’s such an important point. Thanks again for everyone who tuned in. If you're finding these conversations helpful, don't forget to subscribe and share with your network.

JH: Yes, and please feel free to reach out as well. We're always interested in hearing how others are applying these ideas in the field.

RM: Thanks for listening. Until next time.

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