Exploring the Benefits of Member Engagement and Use of Big Data

^{By Julie Gould and Edan Stanley}

Mary Jane Konstantin of AxisPoint Health (AGS), explains why member engagement is important for value-based care and details how the use of big data helps improve patient outcomes while lowering the cost of care.

To get us started, could you just please tell us a little bit about yourself?

Mary Jane Konstantin:  Sure. I've been with AxisPoint Health (HGS) for about three years. My background is in managed care, I actually started out as a registered nurse, but most of my career has been spent more on the business side.

I joined primarily because I really felt that there were some new, innovative, and interesting things going on with population health that had the potential to be enormously powerful in terms of not only helping individuals, but really helping health plans to support appropriate treatment approaches that really just save avoidable admissions, and avoidable emergency department visits.

Can you explain why member engagement is important for value-based care?

Mary Jane:  It's really critical. When we think of the objectives of value-based care, that's to support really positive outcomes from a treatment approach. The provider has the ability to accurately diagnose, to prescribe a treatment regime that he or she feels is going to be successful for that unique individual, but the member, the patient, and the family or whomever is helping out as a caregiver, are the ones that have to follow through.

Otherwise, nothing changes, nothing happens. Without member engagement in their own health, without member engagement with either their health plan or their ACOs or provider organization, nothing's really going to change and they're not going to see that either stabilization or improvement in healthcare that everybody's looking for.

What are some of the challenges with implementing member engagement?

Mary Jane:  The first is just reaching the member. You think about it, it sounds easy. You can send a letter to their house, but maybe they're staying with relatives and they're not getting their mail. You can reach out by phone, but like most of us, many of the members that we are trying to reach don't answer the phone if it's not a phone number that they recognize. Just reaching out and connecting the member is, frankly, the first challenge.

Then after that, it's really critical that the population strategy is providing something that the member values, so they see that they're getting assistance in areas that are important to them.

Otherwise, they're just going to drop out of the program, they're not going to pay attention. In order to support that goal of compliance with the treatment plan, the members just got to be engagement, got to have that connection with the member.

Can you highlight the importance of addressing social determinants of health?

Mary Jane:  I think the widely reported number that I always see is that 80 percent of treatment outcomes depend on something other than the clinician and the clinical care. Some of that may be genetics or lifestyle behaviors, but a lot of it is social determinants.

Think about a member who wants to be compliant with their medication, maybe it's something to treat high blood pressure, but they can't afford it. Or, they don't have a way to get to the pharmacy to pick it up.

Or, they just quite can't wrap their head around medication compliance because they're being evicted from their home or they have food insecurity. All of those things come into play. They're a much bigger, greater concern for the member, and that stand as a barrier to medication adherence.

Unless we're able to address those types of social determinants, we really aren't going to be able to resolve a gap in care effectively. We've got to take that into consideration, and we've got to treat it with the same priority that the member gives to it.

How does the use of big data help improve patient care, and how does it aid in lowering costs?

Mary Jane:  There are two key ways that see big data improving both of these. To me, they're connected. If members are getting the care that they need, at the right intensity, at the right time, it's going to prevent much greater, higher spend. To me, good care follows an overall control over the costs.

By using big data, multiple data sources, to pinpoint the members with the greatest acuity, the highest risk members, and those who have gaps in care which left open, left unaddressed, will result in near-term, high-cost, avoidable ED visits or inpatient stay.

By using that big data approach, we can do a much better job of pinpointing not only who will benefit the most from this type of outreach, but also exactly what we should be working on.

In the absence of that, certainly clinicians do an excellent job of identifying need, but to really pinpoint who specifically should be outreached to, what we have found is that our predictive analytics tends to do a better job than practitioners' patient, by patient, by patient, kind of identifying who needs those additional resources. We find it a much more effective means of getting at those extremely vulnerable, high-risk members.

Can you briefly explain how the use of predictive analytics can identify and target members for focused interventions, and how do these interventions help improve patient care?

Mary Jane:  In terms of how predictive analytics works, it's really looking at combinations of historical experiences, typically through claims, that create a profile that we know pinpoints someone who is likely to have an exacerbation or worsening of their condition. We can also add in non-clinical data, even consumer marketing data, to get a much better understanding or profile of these members.

Identify who is more likely to have supports, family, friends, well-engaged, helping them out, because we know that someone who is a little bit more socially isolated, or doesn't have others that they can count on to help them out, that in and of itself raises their risk factor. Using that big data approach, we much more precisely pinpoint those individuals who are at the greatest risk.

Then, in terms of using that information to intervene and to lower that risk for that individual member, we look at gaps in care. I mentioned med adherence before, if someone is not compliant with the mission-critical medication, the likelihood that they're going to have a near-term hospitalization goes up significantly. We also know based on clinical evidence that for certain conditions regular follow-up with the provider is incredibly important in keeping an individual stable, keeping a condition from worsening.

We can use the data to understand not only the cadence of refill of their prescription which is a great indicator of how compliant they are on their medication, but we can also match patients to providers to make sure that patients are getting in to see their provider on a regular basis.

These are just two examples of how we look both the risk level of the member and then where is there an opportunity for an intervention or an action that will improve that health trajectory for that particular member.

Are many health plans using big data to improve member engagement?

Mary Jane:  We can tease that apart a little bit. Health plans absolutely use data all the time to identify which members they want to after, to try and work with them, help them out, eliminate barriers for members to get care. In terms of linking the big data and engagement, I think health plans are across the spectrum. Some are using it with varying degrees of success.

Some really aren't marrying that data approach with anything that would necessarily help improve the engagement, rather they're using the data just simply as a source of identifying here's the list of people that we really want to be working more closely with.

What challenges arise when payers and providers implement use of big data, and how does the benefits outweigh the challenges?

Mary Jane:  I think there are couple things. It certainly takes a level of sophistication on an analytics perspective. In our case, we have a number of people with advanced degrees, including several individuals with PhDs. There's a cost associated with it that can be a challenge, especially for a smaller health plan. The other is access to all of the data sources in a meaningful way.

I will say that's something that's shifted dramatically over the last even 5 years, but certainly 5 to 10 years. Integrating claims data, encounter data from multiple sources is increasingly easier to do. I think that the other piece of it is understanding what's actionable in the data, really thinking through.

Great, we know who has a higher risk opportunity, but thinking through what do we do about it? How do we construct a program that alters that risk, that lowers it, that shifts it?

I do see that as a challenge, often, for plans. In terms of how do interventions help to improve patient care, again, where we are able to pinpoint someone who would dramatically benefit from better adherence into that treatment plan, that to me is just a golden opportunity, and frankly, everyone wins. The patient is encouraged and aided in becoming more compliant with that treatment regime.

As I said before, that appropriate care at the right time, that consistent follow-through, especially for individuals who are chronically ill, absolutely will lower overall costs. The health plan wins, the patient wins, and frankly, the provider's treatment plan gets better attention, so nobody's pushing back against the provider. Everybody's working towards that same common goal. I think that's a tremendous advantage.

What would you say are the major takeaways of member engagement and the use of big data?

Mary Jane:  I think any plan that isn't look towards it is missing a tremendous opportunity. Through the use of big data, it really gives us a tremendous power in better pinpointing where additional interventions can be helpful.

I think that as organizations are looking at how they can better connect with their members, how they can do a better job of changing behavior towards more compliance, that big data approach is just an incredibly important component.