Q: IBM has helped Geisinger to consolidate its Clinical Decision Intelligence System. What has that meant, bringing all those different data sources – EHR, insurance claims, even patient satisfaction scores – together?

A: It's critical. It's absolutely critical. I can't quite remember when we started that CDIS, but it was around 2001 or 2002, and we were just finishing the electrification of our system. We'd started the electronic health record in the ambulatory aspects of our system, and then only by 2002 or 2003 had it completely transacted throughout all of our hospitals.

But we made the commitment to do the data warehousing because we wanted to ask questions about how many of the people we were responsible for – in our 41- or 42-county service area at that time – how many people had osteoporosis? How many people had been tested with DEXA (bone density scans) for osteoporosis? And how many of those had actually had a primary care physician list osteoporosis as one of the entities on the problem list? And then how many of those folks had been treated for osteoporosis appropriately?

Now you can't ask any of those questions without a data warehouse. And then, obviously, in order to try to get a best-practice treatment algorithm, you've got to have the feedback through CDIS in order to get it out to our 70-some sites. So it's been critical. Absolutely critical.

Q: You guys are so far ahead of the game compared to so many other providers. But what have been some challenges or stumbling blocks for you along the way?

A: Oh, there's a huge number of challenges. And again, we could talk for a week about it. Again, as I said, it's really all about behavior change. And a lot of times in healthcare – particularly among docs, when we have a good idea, we just assume everybody else thinks it's a good idea. And so we've designed solutions in a number of our really important problem areas that have been duds, because the people that are actually transacting the solutions don't think they're solutions.

Another really good example: When we, as a group of providers, whether it's docs or PAs or nurses or pharmacists, when we hand an individual who's got a chronic disease a prescription, we assume that they, number one, agree with our recommendations for the treatment, and we assume they're going to get the prescription filled. Those assumptions are wrong between one-third and 50 percent of the time. Isn't that amazing?

And so we've done what I consider to be a predicated for really activating the human beings who should be partners in what we do – our insurance company members or our patients – through this effort called OpenNotes. We've opened up our progress notes throughout our entire system to all of our patients. They can do a Web-based connection and see what their doctors have said about them – even see what our trainees have written in the charts about them – in real time. With two exceptions: We haven't opened up our notes in psychiatry and psychology, and we haven't opened up our notes in the emergency room for some specific and real reasons.

We've done this with BI Deaconess in Boston, and with a cohort from Harborview in Washington State, and what we've found from the beta test, which was a relatively small cohort of primary care physicians and patients, to this big, big opening, is that patients and their surrogates are very interested in diving into those notes.

First, the frequency of interaction is extraordinarily high. Number two, we unearthed problems – either assumptions on the part of our providers that were not correct, or in terms of patients either understanding what's going on or agreeing to the treatment. And we can correct those, we can change our assumptions, we can actually get closer to a true, meaningful partnership, and that's a start on that second area of behavior change: understanding what turns patients on, what their sweet spot is.

This is a cliche, but it's a journey; it's not an epiphany. But I'm really excited about that fundamental change in the relationship between the people we're responsible for and us.

Q: There are going to be a lot of people at Healthcare Business Intelligence Forum looking to learn, looking for tips on how smaller providers could some of this stuff to work in their own hospitals and practices. What are some doable, practicable tips you could offer for putting BI tools to work?

A: I think the biggest piece of advice is to look at the functionality you want first. There are going to be people there who have more technical capabilities than I'll ever have. And understand the nuance of the various systems, whether they're hospital-based or ambulatory, or what have you.

But I think what drives us is, "What is the functionality you want? What is the end-point in the relationship between us as insurers and us as insurance company members?" Or, "What is the relationship we want between us as caregivers and as someone with chronic heart disease?"

And then work backwards, from: "What is it going to take to get a different functional outcome than the one I'm getting now?" And there's almost no outcome that can't be improved.

The second thing to consider, which I think is very important, is: "What is my capacity, based on my structure, based on my size, based on my access to capital, what is realistic to me? And if I can't achieve the optimal function, how am I going to have to change?"

One of the thing we've learned – and I'm always nervous about extrapolating to others, because you have to change from what we've done well and had success in at Geisinger, to "What works in Philadelphia, or what works in Northern Virginia/Bon Secours?" or what have you.

But basically, it's "What can I do that has a great probability of success, early on?"

I learned this from Jim Walker, who had been our CMIO for a period of about 12 years. A great partnership. He's now moved on to Siemens. He would ask, "What is it that's doable, even if it's not perfect?"

Y'know, "How can we begin to enable small practices with a non-proprietary connection to our version of Epic. And it won't be perfect, but it'll help them. And then they'll start to demand more intricacies and more complexity to move toward better, if not perfect function."

But so often, what happens is everybody wants the perfect solution immediately, and it ends up impeding taking the first step. Which is always interesting.