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November 10, 2020

How Transparency, Technology and Data Analytics Are Transforming Employee Benefits [Part 2]

Artemis Health

Artemis Health CEO Grant Gordon recently participated in a discussion on transparency, technology, and data analytics in the employee healthcare industry. We wanted to share some of the discussion and insights from this webcast panel with you, and we’ll be doing so over the next few weeks in this multi-part blog post series. Read Part 1 here. 

In addition to Grant, the panel included Rion Shearer, Senior Employee Benefits Consultant at USI Insurance Services, and Lester J. Morales, Co-founder and CEO of Next Impact. Let’s dive into their discussion. 

Lester Morales:

Rion, walk us through, because I know you and I worked on a prospective client, right? So, now let's chat on these screenshots that we have. It was actually a prospective client that you and I worked on. That was a smaller group, so you didn't have any claims data. We couldn't get anything. Talk to us about these types of tools that are out there that give you an avenue to be able to get the data that maybe not what everybody on the phone has heard before.

Rion Shearer:

Yeah. Sure, Lester. This situation is probably a very common one for most of the folks on the phone. When you're in that 50 to 150 employees space, more often than not the group is fully insured or level-funded. With under a hundred employees on the plan, it creates some challenges as an advisor to properly make recommendations to the client on a renewal strategy. So, getting the data is key like we're discussing.

In this particular instance, the client didn't have any claims data. Seventyish employees enrolled on the plan, and the incumbent broker has not provided any data or reason premium versus claims, et cetera. So, we did some analysis and identified that there are some tools out there that will allow you to effectively scrape member EOBs (Explanations of Benefits) to aggregate some high-level data that will help identify current plan performance and risk, which allows competing carriers maybe to get a little more aggressive. Or it allows me as an advisor to accurately identify if the current pricing is accurate or favorable, or if fully insured is the right funding, or if a move to level funding would be a better fit.

Lester Morales:

What I love about this, and I want to make sure everybody heard this correctly: there are platforms out there that can actually, if you're familiar with, the personal finance tool, there are platforms out there like Mint that scrapes my Bank of America account and my Wells Fargo account and my Merrill Lynch account. There are technologies that actually can scrape EOB data. So, now think about it: every claim that's incurred has an EOB attached to it. Those members are eligible to get through their access. And, now they can scrape that data. So, we've got some screenshots on there and it produces what looks to be like a claim form.

This is the transparency that we're talking about. We now know which member IDs had what service and how much was paid for it. We also know the type and the provider that they're going to. So, this is huge data to be able to be, to Rion's point, proactive and say, "Hey, I now know, and I'm about to show you a real life case that the carrier was asking for." This is 33 lives. The carrier was asking for a 61.2% rate increase. When we did the scraping of the tool, they had a less than 16% loss ratio. 

So the broker was going in blind. They only get a renewal if they basically “take it or leave it.” We got an alternative, but it starts with everybody on this phone demanding more and taking the flag of doing something different. In past years, 9 out of 10 advisors would have just taken that and said, "Well, we shopped it to all the other people at this is what they had."

The reality of it is, a 16% loss ratio versus a 61% rate increase is just absurd. So, again, some key tidbits on the access to data: make sure you're getting the carriers to write into their contracts, that they will provide a level of data before you award them the account. Make sure you're putting in performance guarantees and the calculation of them, so you understand how that's calculated. Lastly, there are different tools in the marketplace that could make you not only a better advisor, but also differentiated in your approach.

Lester Morales:

Now, Rion, we've got a client. We've got data. Talk to me about the top three ways you're using it and the results. Not only the financial results, but I like to use the word “value” because if you're producing results for your client, that also increases the value that you're able to provide for them. So, talk to me about the ways that you're using data.

Rion Shearer:

Yeah. Great question, again. You have to get the data first, and then using it effectively is going to be key. I use it offensively and defensively, Lester. When I say offensively, I mean I'm using it to my advantage as the incumbent advisor to go into my client and talk to them about new ideas, new strategies, financial impact, and things that we can do with that data to control and reduce their costs going forward. 

On the other side of that, I use it defensively to effectively disarm my competition. We all know how competitive this business is and how many different ways there are to get in front of a prospect and spin a story. My personal position is that the more data I can obtain on behalf of my client, and the more I can educate them and share with them and show them that I'm on the ball so to speak, the less opportunity there is for my competition to come in and use that data against me, if that makes sense. Or, use that data to drive a wedge and create an opportunity with my clients. That's one of the key ways I use the data.

The second, obviously, would be to help put my client on a longer term strategy to control cost. When I started out in this business, I was the traditional broker where I would get the renewal, I would shop it, hope for something better, use that as leverage against the incumbent carrier in hopes that I could do some more favorable results, and hope that the client gave me an “attaboy” for getting the renewal down from 20% to 12%.

The way that I'm using the data today is to negotiate a fair and accurate renewal before I even talk about competing offers from other carriers. If I feel that the renewal should be at 12% and that carrier is at 20%, I want to use that data to get the number to 12 before I even talk about what my competing carriers are willing to offer from pricing. What I've seen with that strategy is ultimately on delivering a better renewal outcome for my clients than just approaching them with a competing offer. Does that make sense?

Lester Morales:

It makes sense. I wanted the walk through some of the ways because I've got the data here. This is obviously off of one of your clients that you and I work with. Walk us through this particular client, because this is an epitome of going from status quo and evolving that client using data and technology.

Let's break up using data into three buckets. So, we talk about cross date: how do I get my clients crossed down? In this transparency conversation and this use of data conversation, walk us through this conversation right here with these numbers, and people can't probably see the numbers. But just so everybody is showing, Rion, outline to the client, line by line of every hospital that they were actually accessing care, what the discounts they were receiving before and after the move to a more transparent model. So, Rion, talk about this and how that was received by the client.

Rion Shearer:

Yeah. As you can see from the data shown on the screen here, what Lester mentioned is we were bringing transparency to the client around pricing on some of their higher dollar lower frequency claims at their local hospital systems. We were trying to identify what type of reimbursements we were saying, how that was impacting our health plan, and essentially what we could do about it in terms of helping employees make better decisions around accessing care.

When we did the analysis, we identified that there were a few major hospital systems in the area that employees were using, and we identified that some were charging significantly less over the same type of procedures with no real difference in quality or outcomes. So, what we're doing with the data, Lester, is we're sitting down with the client, we're talking about the structure of the health plan and the incentives and disincentives for employees to access care at certain providers. 

That has brought more transparency to the conversation. I've armed my client with the data. I've shown them the numbers. They now have transparency into where their healthcare dollars are going. Now they have an advisor that can give them input and ideas, how to proceed forward and navigate the health plan, and incentivize and de-incentivize their members.

Lester Morales:

What a great, I mean, a precise way of talking about something so easily done, but brilliantly executed. I give you a lot of props for this because this was a very educated user. I happen to know the client and I know that they understand the healthcare process. They understand this. So, what Rion has now been able to do is put in a planned design for those employees that, when they go to the places that are making good decisions, they get the waiver of out of pocket expense.

Back to Rion's mission, and my mission (and it should be all of our missions) of adding value to the end person, that person that is going to work every day, a $3000, $4000, $5000, $8000, or $10,000 reduction in their outlay of dollars over the course of the year when people are making 40 to $50,000. We're talking about 10, 15, 20% of somebody's take-home pay, just by understanding, "Hey, by the way, we get this kind of deal over here. And seven miles over there, we get this deal." We're talking about Atlanta: there's huge healthcare opportunities in Atlanta. It's just been a great thing.

Rion, talk to me about this one, because it’s the same client. You now put in a transparent PBM conversation, and boom. First quarter we've got a couple of drugs we're able to do something about. Talk about that strategy, and then also how, again, getting the data where you weren't used to getting that data, and the flexibility of transparent model really helped.

Rion Shearer:

Yeah. Another area of opportunity for everybody on the phone, obviously around the pharmacy conversation, that's starting to be a bigger portion of the dollar on the claim spend, and as we all know there are some significant specialty medications, gene therapies, et cetera, that are coming down the pipe, so to speak, that are going to be very expensive claims on your employer’s health plan.

And even in a fully insured model or even in a self-funded model with a national carrier has a lot of restrictions around the contract terms, the pricing, even access to the data like we’re discussing. And that creates a lot of challenges as an advisor. How could you effectively advise your client on what programs and strategies and education, et cetera, that they should be using without obtaining the data? 

And so, with this particular client, being that they were a little more aware of healthcare and how it works, and the spend, we made some decisions to move to a transparent PBM model with a lot of flexibility. That would allow us on-demand reporting to see prescriptions in almost real time to see what was hitting the plan, but also to pick up on prescriptions that may have opportunities outside of the health plan. And when I say outside of the health plan, things like patient assistance programs, manufacturers coupons, tier one, outsourcing of the medications, and every dollar that we're able to pull off of the plan obviously is saved by the company, saved by the self-insured plan and allows us to preserve those dollars going forward to help mitigate some of these large increases.

At the same time, these programs are very valuable to the end member because, more often than not, the member's going to qualify for these programs that produce heavily discounted, if not free, medications to them. So it's definitely an opportunity to create a win-win scenario.

Lester Morales:

A great explanation, because just one Humira can be a six-figure number on the plan. So we've talked about quality, but there's a quick way to get into the last section here, but what we did with the data is understand that in Atlanta, if you could get people to the highest quality doctors, healthcare is reduced by 30%. So this is a huge thing because at the end of the day, getting people into the funnel, into the healthcare funnel and focusing on quality lowers the cost. And I don't care if you're sitting on top of a PPO; if you're doing a more transparent pricing model or whatever it is, it's all about the quality of the health care that's being provided.

And here's the last thing I want to talk about is what I call fishing, where the fish are or using a fish finder. I really think that our job ashealthcare advisors is to be risk managers of a health plan. And so having the data, Rion talked about these advanced analytics tools that we're using that allow you to truly understand where people are spending money, who's spending the money and talk about any ideas that you have thought of or use that actually allow, some incentivization around this or anything that's proactive as opposed to, “Oh man, we spent $874,000 on diabetes this year. Hopefully that gets better next year.”

Rion Shearer:

Yeah. So again, taking the data and utilizing it to identify the areas of opportunities, the key message, right? So you're looking for what's driving the claim costs, things like gaps in care or heavier utilization in particular settings that may seem out of line with the norms. And then identifying vendor partners that can help you mitigate those costs going forward. You talked about diabetes, right? I mean, there are a number of programs out there that once you identify your at-risk population and how those are stratified, you can layer in those type of programs to bring down those risk scores, if you will, associated with those utilizers and ultimately impact the spend on the program. Each case is a little bit different, but I would say the advances with the tools and the technology that are out there that can make this data very easy to interpret and to identify where the dollars are billing is key objective number one.

Lester Morales:

And you hit the nail on the head, right? Everything's a little bit different, but the good news is if you have the data, not only can you look at that client as a whole, but anywhere like on this slide where you see an underlying thing, that's a live link and you can keep digging and knowing exactly which members may be at risk. So if we're talking about again, fishing where the fish are, well, if you want to impact the most claims, you’ve got to know where people are spending the dollars. And so it's all about accessing the data and then more importantly, what you do with it. 

Stay tuned for further parts of this blog post series on technology and transparency in healthcare data analytics. Want to learn more about Artemis Health’s software platform? Watch our 2-minute demo video now. 


Excerpted from How Transparency, Technology and Data Analytics Are Transforming Employee Benefits, published on October 7th. © 2020 ALM Media Properties, LLC. All rights reserved.

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