HPM Institute Live National Podcast: "How Brokers Can Use Technology to Help Clients Achieve Lower Health Costs and Better Health Outcomes"

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HPM Institute Live National Podcast: "How Brokers Can Use Technology to Help Clients Achieve Lower Health Costs and Better Health Outcomes" Featured Guests: ERIK DAVIS and SCOTT HAAS, Wells Fargo

1 HPM Institute Live National Podcast: "How Brokers Can Use Technology to Help Clients Achieve Lower Health Costs and Better Health Outcomes" Featured Guests: ERIK DAVIS and SCOTT HAAS, Wells Fargo Insurance Services for Integrated Healthcare Metrics Moderated by GEORGE PANTOS, Executive Director, Healthcare Performance Management Institute PANTOS: Welcome to the Healthcare Performance Management Institute podcast on "How Brokers Can Use Technology to Help Clients Achieve Lower Health Costs and Better Health Outcomes." My name is George Pantos, and I am Executive Director of the HPM Institute, a think tank dedicated to research and education on healthcare performance management principles designed to reduce costs and improve health outcomes through the use of innovative technology. Our featured guests today are Erik Davis and Scott Haas of Wells Fargo Insurance Services, the largest bankowned insurance brokerage company in the world. Erik and Scott work in the Portland, Oregon, office of Wells Fargo Insurance Services USA. Erik is the practice leader for Integrated Healthcare Metrics, and Scott is Vice President, Integrated Healthcare Metrics. Scott is also a member of the HPM Institute Advisory Board. Welcome, Erik and Scott. DAVIS: Thank you. PANTOS: Well, we can get started. Maybe the first question would be directed to you, Erik. Could you set the stage for our listeners with a brief description of the healthcare services provided by clients of Wells Fargo Insurance Services with particular reference to the Integrated Healthcare Metrics program? DAVIS: Yes. Within our practice, our clients are used to an approach that is much more of a risk management-based, data-driven approach to understand the cost drivers within their programs. To that end, we look for opportunities that are specific within the given population of each client. In many cases, there are similarities from one group to the next, but typically by drilling deeper into a given population's own information, you're able to identify nuances that are specific to that group that allow you to create customized strategies that are unique for each particular client that we represent. PANTOS: Great. And could you kind of say a word or two about what kind of clients you service? DAVIS: Most of our clients are large self-funded employer groups. We also work with health systems, managed care organizations, which include Medicaid and Medicare contracted providers, but we also work with fully insured groups, as well. The type of backgrounds that we have allow us even when we are not given the same type of data we can get for our self-funded employers in managed care groups, kind of a knowledge base and expertise that allows us to service those fully insured groups in ways that are unique to them as well. PANTOS: Erik, could you elaborate a bit on this concept known as "data benchmarking," also on claims analysis? How do these play a role in the work that you do?

2 DAVIS: Well, being able to look at a client's data and then benchmark it against a larger population many times allows you a quick way in which to identify anomalies within a given population spend that are different than a typical norm. It just gives you an efficient way in which to identify where you need to drill deeper into that particular group's problems in order to identify where there are opportunities to create solutions. PANTOS: And does this play any role in your clients' renewal strategies of their funding or in plan design? DAVIS: Yeah, because I think a key issue that's important to understand is when we say data, we're referring to claim-level, line-item, granular data that comes out -- typically directly out of a payer's claim system versus reporting information that comes out of a payer's data warehouse that's already been predetermined and formatted. What that allows us to do is to -- on an ongoing basis evaluate the information that we receive and respect to the plan sponsors or the organization's goals and objectives as it relates to fiscal targets, and also we're able to blend in clinical review of that information to really take a good look at the practice patterns of providers, the effectiveness of underlying hospital and provider contracts as it relates to a respective health system's contracts or PPO contracts, as it may, and then to be able to identify those areas that may be important then from not only a fiscal but a clinical perspective as it relates to the outcome and the results of the spend within a population. PANTOS: Scott, this is pretty much mirroring some of the points you make in a white paper that you have written titled "Healthcare Data is a Plan Asset," and I think you have given us a good insight into the thrust of that paper. Could you talk a bit about how you use the concepts in your white paper to work with PPAs and ASOs and how it benefits the work they do? HAAS: The very first thing that we do when we engage with a new clients and then we make sure that this is all structured appropriately with existing clients is in the administrative service agreement, making sure that it is extremely clear that any service provider or payer is in an administrative capacity to the plan sponsor. That's critically important in getting the point across not only philosophically but legally to the service providers that they are a servant and the master is the plan sponsor. Many times, we encounter resistance and obstacles from service providers in the self-insured environment whereby they will claim that their data is theirs, and it s proprietary versus the concept that the plan sponsor is the master and it's their data and they own it and it is a plan asset. Now, the courts are somewhat vague in the definition of data as being a plan asset. There will is no case law or study that we are aware of that basically says that, because under ERISA, the majority of the case studies and cases that are out there that relate to plan assets have more to do with investments and those types of things that are supportive of trust funds. But I believe that as of this marketplace is evolving that it's critically important, and we believe that as we move forward, especially into the environment of healthcare reform as it's currently structured, that data is the most important asset to any healthcare plan sponsor. DAVIS: George, this is Erik. I'd like to add to that a bit as well. When you look at plan assets and the ERISA definition of what ownership is from a financial standpoint, if you have a thousand employee life group that is spending anywhere from 6- to $10 million a year in claims, there is a fiduciary liability that the plan sponsor has to show that they have done what is expected of them as the fiduciary to the plan, and if they are not taking the steps needed to completely understand the risk that they are managing, they can get themselves in the position of liability as well. PANTOS: So, Scott, following up on your point, would you say that a self-insured group health plan has an advantage over an insured plan in accessing plan data, and if so, why is this so? HAAS: The answer very clearly is yes. It's a readily accepted business practice among service providers and plan sponsors in a self-insured environment that they understand the fact that service providers are in an administerial capacity to the ERISA plan sponsor, and that information is typically very available at a granular claim level, line item level.

3 The resistance we usually run into is typically within certain Blue's plans, not all of them but certain Blue's plans, and some of the indemnity insurance carriers. However, most of them as they have engaged in the ASO environment and then as we engage them and make sure that when we negotiate the administrative service agreement on behalf of our clients, that their consideration for a piece of business is contingent upon them accepting that administrative service agreement. Now, as it relates to fully insured opportunities, many times what we're able to do is to enter into a business associate agreement with the insurance carrier as the covered entity and receive the same type of data that we would receive within a self-insured environment; however, we have to keep the plan sponsor at that point in time at arm's length, because technically they are not the covered entity, because they have selected a risk transfer methodology that moves all that risk to the covered entity, which in the fully insured market is the insurance carrier. And so the way that we approach that environment is that we will get that data. We will do the analytics. We keep the PHI at arm's length from the plan sponsor. However, we then work collaboratively with the carrier and the plan sponsor to validate the results of what our observations are through the processes that we employ, and then we create a collaborative environment that the carrier and the plan sponsor really come closer together. And we are then able to collaborate on solutions that are specific to that particular client. PANTOS: Erik, you and Scott have mentioned that you focus as a business associate under HIPAA rather than a fiduciary. So that means as a business associate, you are entitled to use plan data once you can access it to develop workforce risk profiles and targeted wellness campaign. Could you say a word about how as a broker or as a consultant even, consultant or a broker, how does this help the client control costs in a meaningful way? DAVIS: Well, as a business associate that's allowed access to that type of information in a self-funded environment, it truly allows us to customize the solutions, and those solutions could be what we do with this those designs. Those solutions could be what we do with network design. Those solutions could be how we pay claims. Those solutions could be certain coordinated care management programs. Really, by being allowed access to the type of detailed information that you can get with encounter-level data, it really provides you the empowerment to evaluate solutions that are going to have significant change for a plant. It's much different than going in with high-level reporting and making cost shifts based upon little to no information. We now have the information to utilize in order to create solutions that are going to give the most effective return on investment to our client. PANTOS: Erik, I assume you mean by that, that you have access to this data in a self-insurance plan context through the TPA, but could you discuss how access to that data differs in any respect between a TPA and an ASO, which an ASO being an administrative entity of an insurer? Is the data as transparent to you in your capacity from ASOs as it is from TPAs? DAVIS: It can be. It depends. When you work with a third party administrator as opposed to an ASO carrier, typically you are dealing with a client that wants to create their own solution. Where the TPA is strictly paying claims, we go out and evaluate networks and specifically define who the networks are. We pick coordinated care management solutions. You really pick everything a la carte. In those types of environments, the third party administrators that our practice works with are very open to data sharing. When you get into a client that is more apt to want an ASO solution, typically this is a client that wants a turnkey solution where they are able to have a vendor, a one-stop shop, to so speak, that brings the network, the coordinated care management, the payor, brings everything in one solution. In those environments, we do have carriers that are very open to us. We have others that we struggle with. It's typically a case-by-case basis, but it also is a situation where you're working with that vendor to internally coordinate themselves to provide the best solutions possible to their client versus in a TPA environment where we're out selecting each vendor for each particular specialty individually and bringing best in class and then tying it all together into one solution.

4 PANTOS: In your role as a consultant broker, Erik, how do you leverage plan data such as pharmaceutical prescription drug claims data? Does this play a bigger or a lesser or an equal role to clinical data, medical data? HAAS: George, this is Scott. I'll take that one. PANTOS: Okay. HAAS: We are actually very active in the PBM marketplace in that one of our partners and principals of our consulting practice is a clinical pharmacist, who has built two PBMs from scratch, and our unique approach to the marketplace related to the PBM industry is designed to eliminate spread pricing, and it is extremely valuable. Prescription drug data is readily available under the NCPDP data file format, which under HIPAA is the industry-accepted file format. That data is very granular, and it is readily accessible from any PBM platform. PANTOS: Okay. HAAS: Using that data, we are able to create a procurement process to the marketplace that has nothing to do with discounts off of retail, and it allows us to basically define and structure PBM contracts that are based on a unit cost methodology in the marketplace that allows us to move away from AWP pricing that, quite honestly, contains the opportunity for a lot of abusive practices within the industry, and so -- PANTOS: Well, you have written a very good white paper on the use of data to evaluate workforce health risk. I assume that means through analytics as well as in designing care management and wellness programs. Could you just talk a little bit about them, the results that have been achieved with your clients in accessing plan data to help bend the cost curve? Could you be specific in terms of, let's say, what results you've seen? HAAS: One of the key aspects of data that's very readily illustrated is really in the PBM side of our business practice. A source that we have validated, in 2010, we engaged with a large Medicaid managed care organization that had about 175,000 members, and we approached them initially on a PBM evaluation. When we received their initial data that, again, was at a very granular level, we went through and did an evaluation and identified that within the pricing structure of that particular PBM, there was approximately $14 million of spread pricing revenue that was not being disclosed by the PBM in that particular circumstance. The client engaged us, and we moved forward and put an RFP process together that resulted in a price point for that particular client that in 2011 at the end of the year, we went back and we evaluated what the actual results were. And the results far exceeded the initial $14 million projection that we looked at. Now, the relevance of that is that not only did we fix the fiscal relationship of that PBM relationship, but as an example, the metrics on their type 2 diabetics that had also had comorbidities of hypertension and hyperlipidemia, the annual cost of treating those people went from under the previous arrangement at about $3,000 per employee per year or per member per year to down to about $300 per member per year. So the impact on that and one of the studies that's now being currently engaged is the relevance of valuebased care as it relates to compliance when the cost basis of that care is lowered in a manner such as what we've just described. PANTOS: Could you touch on, if you could, briefly on any similar examples in the private side with your work with TPAs and ASOs? Are there any examples you could give of how you have bent the cost curve down through the use of data with private clients? HAAS: You know, there's a number of them. One on another PBM example, a local account here in Portland, Oregon, with about 200 employees, when we reengineered their PBM solution, we on 220 employees were able to reduce their PBM cost by $50,000 in the first year, and that account is in a negative trend and has been in a negative trend for the last 3 years.

5 On the healthcare side, one of the key opportunities that we've recently uncovered within a healthcare population is the ability to identify methodologies through which to reduce their emergency room utilization. We went through the data, and using the benchmark relationships, we saw that this particular population was really primarily accessing primary care through the emergency room. So we were able to see the types of encounters that were occurring and able to then go out to a local primary car organization and create our own pseudo primary care medical home solution that is beginning to drive primary care, urgent care away from the emergency room, and at the same time eliminate all of the carrier-based disease management programs that were in place and shift that revenue stream to those primary care providers and then create around that disease management programs that are face to face at the primary care level. PANTOS: How do you see that evolving under so-called Obamacare or health reform legislation as this ACO vehicle becomes more visible? Do you see the role of data being an integral part of the emerging ACO concept? DAVIS: George, this is Erik. Absolutely. You know, the State of Oregon is one of the leaders nationally in this concept. Our governor out here is a physician, and most recently, they have been picked as a pilot by CMS in order to drive this medical home concept. In order to do that, you have to be able to create data capture at the types of levels that we've been discussing as well as create conduits of communication through electronic medical record that allows these clinical experts to coordinate themselves and create protocols that provide our patients the right care. Over time, we'll see how this strategy involves; however, it is going to be the way in which medicine is practiced in the United States for years to come, and it's simply a matter of how quickly we are able to mature towards this type of a model. PANTOS: Do you see that model impacting the world of insurance? In other words, as this trend unfolds, a shift from the coverage of health claims by insurers to, let's say, the ACO model, which would be more provider driven? DAVIS: You know, you look at the way in which the broker or the consultant has typically placed themselves as an advisor to an employer. You have two types. You have consultants that really look towards opportunities to create solutions, and then you have those that are more product-placing brokers. So as a consultant, brokering a product may be part of an overall risk management strategy. As a broker, you really look at brokering a product as your value proposition. I don't see a standard broker being able to stay in this marketplace. As a benefit consultant and broker, the way in which to define a niche for yourself in the future is through creating solutions that we're discussing today in order to provide out-ofthe-box strategies that allow our clients to stay ahead of the curve. PANTOS: Very good. I just wanted to emphasize at this point that the Institute has sponsored a series of three webcasts on this topic of new trends that relate to cloud-based services and ACOs in the private, in the public sector, as well as the technology engines that are driving these changes, which will be published soon through the Institute. Well, I want to thank Erik and Scott, Erik Davis and Scott Haas, for a most interesting discussion of the broker role and controlling healthcare cost and improving health outcomes. Thank you, Erik. Thank you, Scott, for a most interesting discussion. DAVIS: Thanks, George. PANTOS: We hope this podcast provided listeners with useful information about how data and analytics are helping companies and service providers cope with healthcare plan performance challenges and cost. More information about this podcast and the Healthcare Performance Management Institute is available by calling that's or by going to Thank you again. - -

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