Data analytics programs are supposed to help you determine workers’ comp trends and predictive analysis. So why isn’t your program delivering? In today’s Inside Workers’ Comp, data analytics expert Jim Harris explains how factors such as aging claims systems and inconsistent data input could be preventing you from capturing, reporting, and trending the information you need to make important claims decisions.
Tom Kerr (TK): I’m Tom Kerr. The use of data analytics in workers’ comp has been steadily growing over the past decade. Yet, turning that data into actionable results remains a challenge for some. Data analytics expert Jim Harris explains why in today’s Inside Workers’ Comp.
Jim, thanks for joining us.
Jim Harris (JH): My pleasure, Tom. I love talking about data.
TK: How has data analytics in workers' comp evolved over the last few years?
JH: Wow. You know, it has changed so much. As everyone knows, workers' comp has always lagged behind other industries like group health, and analytics is certainly one of those areas that we've struggled on.
In the past, work comp was always good at widget counting — what happened, this is how many losses you had, this is how many lost‑time claims that you had, this was your indemnity spend —but it was never really good at looking past that.
Meanwhile, group health is marching ahead. They're looking at treatment activities, they're looking at what kind of services can be done to prevent treatments from happening and prevent more serious conditions from developing in the future.
But I think now workers' comp is finally catching up on the analytics front. Some of the more sophisticated companies and vendor partners are now venturing into predictive analytics to implement early intervention programs. They're using data, they're using machine learning to determine when to act on claims, when to assign case management, when to skip conservative courses of treatment and move straight to surgical interventions.
TK: Is there a reluctance for some work comp professionals to truly embrace data?
JH: I don't know that there is as much of a reluctance as maybe a lack of understanding of what data can do. Some people are just not used to looking at information that way or they claim not to be a numbers person.
I know that when we show results to our customers across various managed‑care programs, additional thoughts, questions, ideas pop up from us and from our customers as well. So, I think that getting people to think differently or think forward is the real challenge here, especially in an industry that has a lot of tenured individuals. But once people see what can be identified and what can be accomplished with analytics, I think they become very active participants moving forward.
TK: What are some challenges in implementing an effective data analytics program?
JH: One of the main challenges our industry faces is the consistent capturing of data. Many companies are faced with aging claims systems that just don't allow them to capture, report, and trend the data they need.
There's also challenges with data integrity. Adjusters, nurse case managers or other participants are required to enter a lot of information, and getting it to be entered consistently is one of the challenges that we all face with this.
If you can't get consistent information captured, you can't report on it as well. So, I think as systems get replaced or enhanced, it's important to build in data integrity components, too, so that this information can ultimately be reported on in the future.
TK: You stated earlier that you loved talking about data. What are the rewards of working in this specialty?
JH: You know, one of the things I enjoy the most in working with data is finding those nuggets of information that can have a true impact on the customer's programs. When you're caught up in the day‑to‑day activities of managing claims, it's sometimes hard to take a step back and identify those trends; so, myself, my team, other people in my profession, are given that opportunity to really take a step back and help show customers where you can make improvements and really have cost‑saving impacts on their programs.
TK: What’s the future of data analytics in workers’ comp?
JH: The next steps in this is moving more towards predictive analytics in the workers' comp industry — seeing what's going to happen and trying to impact that before it does happen. So, using machine learning, taking all the information that we have, using computers to analyze this and coming up with conclusions is really the future of where I think we're going.
And I think, in order to be a player in the future — whether it's a third‑party administrator, an insurance company, a managed‑care partner or vendor — you have to have that kind of information to be successful and to have a true impact on the cases.
TK: Thanks, Jim. And just a reminder to our listeners that you can now catch all episodes of Inside Workers’ Comp on Apple and Stitcher. As always, thanks for listening.