Richard Holada knows a little something about big data and analytics.
At the end of January, he joined Truven Health Analytics as chief data and technology officer, where he’s been charged with aligning the information services company’s core healthcare analytic and data capabilities which, according to Truven, includes the world’s largest database of private sector health insurance claims. Holada was most recently with IBM, where he was in charge of Big Blue’s predictive analytics and business intelligence products and VP of IBM’s Watson Legal offering. Prior to that, Holada was the CTO at analytics software firm SPSS, which IBM acquired in 2009.
Holada spoke recently with Information Management’s editorial director John McCormick about his role at Truven, the challenges of dealing with big data and the benefits the technology may bring to healthcare. What follows is an edited transcript of their conversation.
Can you tell us more about what you’ll be doing at Truven?
One of the biggest assets that we have is the 9 or so petabytes of historical data on hundreds of thousands of lives. By having that much data, I can apply analytics to that data and find real interesting insights. I’m focused on really exploiting that wealth of data by applying higher-level analytics to it and then using the services arm of Truven to help drive that knowledge, that insight, into our customer systems, whether it be payers or providers.
There are now a number of accountable care organizations (payer-provider partnerships), and all of these different organizations are looking for an edge. And that’s what analytics is all about.
In health care, it’s about understanding the person and being able to predict, for instance, whether or not the person is likely to keep up with his or her medication.
If they’re not keeping up on their medication, they’re going to get sick, they’re going to wind up back in the hospital, and that’s very expensive -- which is a bad outcome for everybody.
However, if I can predict that someone is not likely to keep up with their meds, I can spend a small amount of money to hire a health care advocate to go out to the patient and ask if they’ve taken their medicine and, if not, give them a strategy for remembering to do so next time. I can get huge ROIs by going and inspecting a large number of people in a small way.
If you think about it in terms of population health, which is kind of where the market is headed, how do you predict which patients are going to wind up with sepsis? Or how do you predict the disease progression for a particular patient?
More and more it’s about making sure that the people that I’m responsible for never become patients, to intervene. There are two benefits to this. One, it saves the payer a lot of money because they don’t have a sick person. And it keeps a person healthy, which, in the end, is really what health care reform should be about.
Are analytic technologies mature enough to do the things that health providers want them to do?
I think that there’s a bunch of different analytics technologies out there that are at different levels of maturity.
We’ve done a lot of work in sales and marketing, we’ve done a lot of work in fraud detection. But I don’t think we’ve done enough in the health care area. Most of that’s because we didn’t have the data to be able to do it, quite honestly, until just recently. There is a wealth of untapped knowledge in healthcare data -- interesting insights that would really help make the practice and the care of patients better. And that’s kind of where the exciting stuff is right now.
So are the data challenges greater in health care than in other industries?
I think that the challenges are really the same. When you build analytics you view data as data, you’re looking for patterns in data.
But I think the value of the analytics is much greater in health care than in other areas. One of the things that I did in a past life was work on a predictive model that looked at what kind of after-care drug treatment should be applied to a patient who has had a heart valve replacement. And based on the lifestyle of the person, and demographic and socioeconomic data, we came up with a model that predicted what drug regimen would work best for a particular patient.
At the end of the period of time that we tested, which was about six months, we reduced the mortality rate by 6 percent. Now that seems a whole lot more important than raising the top line revenue number for a business by that 6 percent.
I get charged up by the fact that what we’re doing with analytics now is really making the world a better place -- it’s literally saving lives.
What are the key to developing these healthcare solutions be it on the provider side or the vendor side?
You need three things to create a solution. You need domain knowledge, you need data, and then you need analytic expertise.
And the reason I came to Truven was because I wanted to go to an organization where I could take all the analytic sort of horizontal knowledge that I had built up over time and I wanted to apply it to data and analytics within a specific vertical. And I don’t think there is any more meaningful or exciting vertical right now than health care.
What are you goals?
My goals right now are really measured on speeding up the organization. I think one thing that we need to do is to take advantage of technology much faster than we do. So I’m really looking at how to ramp up the number of analytic insights I can create in a short period of time.
Product cycles used to run a year. I don’t think you can have a product cycle that’s longer than a quarter anymore. The world’s changing too fast and we have got to be fast enough to keep up, so we can be there to meet our customers’ needs.
And I think if we already have the data and the architecture in place to do that.
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