Dale Sanders is SVP of Healthcare Quality Catalyst of Salt Lake City, UT. He is also senior technology advisor for the national health system of the Cayman Islands and a senior research analyst for The Advisory Board Company.
Tell me about yourself and the company.
I’ve been in IT since 1983. I’ve got bachelor’s in chemistry and biology. The Air Force sent me back to their version of an information systems engineering master’s program. So the first half of my career, 15 years, was in the military and national intelligence and then manufacturing. Then I got into healthcare about 15 years ago and I’ve been there ever since. It’s been a great transition.
At our core, Catalyst is a company that specializes in data warehousing analytics for healthcare. We are commercializing through Catalyst not only the technology, but the cultural alignment and exploitation of data. All of us that are involved have had the background in that operationally. This is the opportunity for us to make it more available in the industry.
I’m fascinated from your background that you were a nuclear launch officer on Looking Glass, the plane that stayed airborne to launch retaliation in the event of a nuclear strike. Did you ever almost lean on the wrong button and start World War III by accident?
[Laughs] No, never quite that. There’s a lot of checks and balances. But that was an awesome job. I mean, considering how young I was and the responsibility that the Air Force places upon you, it was phenomenal.
Here’s a weird little twist. I was actually working on a nuclear decision support aid for the Joint Chiefs of Staff when I stumbled upon healthcare. I was reading about the use of computers in healthcare, and the idea was that I was going to apply what healthcare was doing to nuclear decision making. But as it turned out, I came away from those studies and I went, “Wow, if that’s the best that healthcare can do with computers, there’s a lot of opportunity ahead.”
Thank goodness you didn’t take what healthcare does and apply it to nuclear strike decisions.
[Laughs] The parallels are very direct. It’s all about false positives and false negatives and diagnosis and the appropriate response. Not over-treating, not under-treating. It’s amazing, the parallels.
The next most fascinating thing about your background is that you went to the Caymans. I’ve been there and mostly remember that the water’s really nice and the biggest industry is bunches of post offices boxes that are the only physical presence of offshore banks. How did you end up there? You’re still working there, right?
I’m still consulting there. I plotted out this high-level strategy in my career. I wanted to work for an integrated delivery system and I wanted to work for an academic medical center.
Then I saw what was happening in the US, and I thought I’d love to get out and work for a national healthcare system. I was actually headed to Canada, but out of the blue, this opportunity in the Caymans came along. I literally turned around within a matter of just a couple of weeks of heading to Canada and went there to work in this more laboratory-sized setting on a national healthcare level. It was the best experience of my life.
One of the nice things about my life is every job that I’ve had is better than the last one. The Caymans is exactly that. It was fascinating. What was really fascinating, talking about the financial arena, is that they pull off a national healthcare system without a national income tax system. They basically operate on what amounts to a national sales tax. There’s no income tax. It’s just fascinating from an economic perspective how they fund healthcare as well as the entire government without a national income tax.
I would assume – maybe incorrectly – that they’re not big technology users.
It’s a tiny little country, only 60,000 people, and talk about isolated from skilled labor. They implemented Cerner about nine years ago. It was not a good implementation. That’s one of the values that I brought down as we turned that around.
But they’re actually very, very capable. Technically, very capable. They were in a bad state of affairs when I took over, but they supported me very well and we turned it around.
Now we’re doing things down there that the US system isn’t even doing. We just implemented a real-time claims adjudication system that adjudicates your claim right at the point of care. The physician signs off on your encounter, and by the time you get to the checkout desk, your claim is submitted and returned, and if there’s any self-pay portion, you manage it right there.
Everybody dreams about a healthcare system where automation adds value to the patient instead of getting administrivia done. It must be frustrating to be back in the middle of this mess we call the US healthcare system.
I’ve had to learn to temper my impatience working in the US system, that’s for sure. But I’m actually very encouraged. I think we finally reached the tipping point. My theory is that whatever happens with federal legislation, the employers aren’t going to tolerate what they’ve tolerated for so many years.
I think we’re at the tipping point now. I think we’re about to enter a very fun period in healthcare in the US.
Suddenly everybody wants to know what you know about data warehouses and business intelligence. A lot of organizations tried stuff before that flopped, often not because of the technology, but because they didn’t have the leadership or culture to act on what business intelligence was telling them. How would you assess the current state for data warehouse and business intelligence and what are hospitals doing now?
Well, it’s kind of funny. I was reflecting … you know, I love your “Time Capsule” reflections, so I was doing that myself. Then I found a paper that I wrote – it was 10 years ago to the month – for HIMSS. It was entitled, “Standing on the Brink of a Revolution: Healthcare Analytics,” I think was the title of it. It was basically the summary of my experience at Intermountain and what we were doing.
I was convinced at that time that data warehousing and analytics were going to take off in the industry. Of course, that was 10 years ago and it hasn’t moved very far, but I think we all see now that analytics is absolutely fundamental to the future. We’ve been in the EMR deployment phase, which is about collecting data. We’ve been in the HIE phase, which is about sharing data. Now we’re finally getting into this age of analytics and exploiting all that data.
It’s really fun to be a part of that and I’m really grateful to be involved with it again. In particular, I’m grateful for Catalyst. I started the Healthcare Data Warehousing Association in 2001 with the idea that we would stimulate best practices and greater adoption of analytics in healthcare. HDWA has done OK, but not great. I think there’s something like 300 member organizations, but it’s not as good as it could be. For me, the involvement in Catalyst is now an opportunity to make best practices available in the market in a commercially sustainable way. It’s a lot of fun.
We’ve been seeing all these debates about whether there is value in the deployment of EMRs and if you drive healthcare costs up or down. I really believe, having watched this now for 15 years, that the return of investment from an EMR comes from the deployment of the data warehouse. For about one-tenth the investment of an EMR, you can implement a data warehouse. I can show all sorts of data that proves the return on investment from a good data warehouse is 1,000 to 1,500 percent in two to three years. You can’t show that with an EMR, but there’s plenty of studies that show tangible measurable ROI from the data warehouse.
Some people would argue, me probably being one, that the real value of an EMR is really at the very front end and the very back end. On the front end, you’ve got decision support that may influence decisions, and on the back end, you’ve got analytics that may influence decisions more broadly and get into population management. Everything in between is a utility. Are people beginning to realize that the EMR isn’t the end of the project, it’s the beginning of the next project?
That’s a great point. I think that’s exactly where the market is right now, and we’re seeing that in kind of the market timing in Catalyst. It’s a little bit like the Wild West — their pulse rate is still pretty high from deploying EMRs. Now suddenly everyone’s saying, “You know what, you’re not done yet.” It’s really about analytics, and the EMR is really a means towards to the end state, which is analytics. People are a little confused by it right now. It’s a little bit of Wild West going on, but it will calm down in the next six to 12 months, I think.
I’m sure a lot of the calls you get are from the average Cerner or Epic shop wondering what you can do for them.
The EMR vendors are – and we would expect them to be this way – very EMR-centric. If you look at Cerner’s and Epic’s offerings, it’s really been around the aggregation of data that they collect, which is all well and good. But if you look at the ecosystem of data that you have to analyze in healthcare, it’s way beyond the data that’s collected in the EMR.
Even if you have a full-blown suite like we did in the Caymans — or as is more commonly deployed now with Epic customers — there’s data outside of the boundaries of Epic and outside the boundaries of Cerner that you have to have in order to understand the full continuum of care, and especially to manage the risk of care and capitated payments.
You have to have claims data, outside pharmacy data, mortality data, and you may want benchmarking data from other organizations. You want to mix that all together into an enterprise data warehouse. And that’s the challenge that Cerner and Epic have never really addressed very well.
Epic is coming out with a new product. It’s a little more extensible. Cerner has been toying with that for a while as well, but they’re a little bit late to this. That’s OK, because the reality is, we leverage what they do. For instance, if you have PowerInsight, if you have Clarity or Cogito, the new Epic product, we will attach to that and leverage that in our data warehouse solution. We’ll pull data out of those EMR-centric designs and pull that into a more extensible design in Catalyst.
The guy who will be running the proposed Vermont statewide ACO said what he wants most is data, because if they’re approved as the statewide Medicare provider, they will get to see Medicare claims data for individual patients – how often they seek hospitalization and for what purpose, more of a population health view. Would you be able to manage government data like that if you could get it?
Yes, absolutely. I can’t say that I’ve ever had the opportunity to pull in Medicare or Medicaid data back into a data warehouse, but we certainly have a strategy for utilizing the data that goes through an HIE. It adds a lot of value to the content of the data warehouse.
I might also mention that some folks are looking at HIEs as being the primary source of data for their enterprise data warehouse. But again, it doesn’t provide the complement of data that you need. In particular, you can’t do what we focus on. You can’t do waste analysis with an HIE data stream, for example. It just doesn’t provide the fidelity or the granularity of data that you need, and there’s no costing data in that data stream.
A big part of what we do in Catalyst is to knock out all of those relatively simple but non-differentiating reports — internal reporting and external reporting to Joint Commission and Meaningful Use and that kind of thing — that everybody has to abide by. There’s no differentiation there, so we try to make that as easy and as quick as possible to deploy.
Then we focus on what we call the upper layers of the analytic adoption model. That’s where we get into waste elimination. We philosophically believe that the emphasis on accountable care and the physicians who are taking great responsibility for a patient’s outcome is a pretty tough accountability to swallow. Depending on which study you look at, 40 to 70 percent of the healthcare costs are lifestyle related. We don’t really know how in the near future a CEO for a healthcare system is going to take accountability for those lifestyle changes that are required to drive healthcare cost down.
But the one thing that is within the complete control of the CEO is waste management within the boundaries of his or her own organization. What we try to do is get people up the analytic adoption model as fast as possible into those areas that allow them to quickly identify waste. It’s not unusual for us to find 25 to 30 percent opportunity waste and that can be returned right back to the bottom line of your organization.
The challenge, I would think, is trying to get the attention of prospects where every vendor of every system that can export to Excel claims they have an analytics suite. What’s the message you have to send to get people’s attention that just having a bunch of raw data isn’t really business intelligence or analytics?
We see that going on right now. In fact, when I talk to fellow CIOs about this, a lot of them are deer-in-the-headlights right now because there’s so many different options in the market.
We’re hoping that that calms down a bit. We hope that as people become familiar with us and they see our track record and they see the history of what we’ve done in our clients — and not only with our commercial clients, but our background as operational data warehouse developers in places like Intermountain and Northwestern — that they’ll see the value that we offer. But, yeah, it’s the Wild West out there right now, that’s for sure, and the options are overwhelming to most CIOs.
Suppose somebody came to you and said, “Give me your best success story so far.” What’s the best outcome someone got from using your products and services?
About $10 million savings in readmissions is probably the big one, within a year and a half. We have numerous success stories in the $4 to $5 million range of tangible, measurable return on investment and savings. Those stories are gaining momentum all the time. It’s very fulfilling.
What effort and resources are required to implement your product?
The combination of a culture that’s willing to exploit the data along with the technology of analytics. Those are the two fundamental pieces you need no matter what your organization or what vendor you’re looking at. You have to have the culture that’s willing to exploit the data, and you have to have robust and extensible technology.
We’re a little different from a lot of vendors in that we try to commoditize the technology and get that implemented as fast as we can. At one of our largest clients, we were able to implement the core analytics solution for them in seven weeks. Our whole goal is to make the technology as commoditized as possible and then move into that cultural exploitation of data just as quickly as we can.
Time to value is a big deal for us. We keep trying to compress that all the time. The message that I share with my fellow CIOs is that if there’s ever a vendor that tells you you have to engage in a multi-year data warehousing project, you need to look somewhere else. You need to measure these data warehousing projects and their deployment and their time to value in weeks and months now. The old 18- to 24-month time to value for a data warehouse is just not acceptable any more. We’re pushing that down. We’re trying to compress that more and more and more.
One other comment on that is that as soon as we deploy the raw technology, the raw data warehouse, one of the things that we bundle on top of that is a waste analysis right away. It gives organizations this compass about where their greatest waste opportunities reside. We’re big believers in the Pareto principle. What we typically find is that most organizations have huge opportunities for waste elimination by just focusing on 10 to 20 care processes and disease states.
It’s very fun to watch that happen. We run this analysis that we call it a key process analysis. We present that to the leadership team, and it just leaps right out at them where they should focus first. Not only have we sped up the adoption and technology, but we’re speeding up the cultural exploitation of the data, too, by giving them this compass.
How does a CIO keep or increase their organizational value as the healthcare reimbursement model changes?
Maybe five or six years ago, I wrote an article for HIMSS, “The Role of the CIO in Healthcare Economic Reform.” I was reading that the other day and there’s a lot that you can do. It ranges from keeping a lean organization internally to IT, rather than always asking for more money, try and compress your budget while still delivering greater value. Simple things, like working with physicians so that medication preferences are listed in generic format first. There’s all sorts of economic benefits to that.
I’m a little bit biased here, but I think as a CIO, the most satisfying part of my job has always been around the analytics that I help endear to the organization. A lot of times, I run into CIOs that don’t have a strong background in data, in data modeling or data management or data analysis. If everyone who feels they need to would spend some time beefing up their skills in that regard, the CIO can be the champion for the data warehouse.
People remember me at Intermountain and at Northwestern, not for all the other things that I did there, but for the data warehouses that I played a part in. Knock on wood, I’m very grateful for that, but it’s the data warehouse and the analytics that has been most kind to my career. It’s a great time to be a CIO if you can lead the organization down that path.
Do you have any concluding thoughts?
We are soon to announce a couple of major partnerships that will address this $750 billion a year waste issue that Don Berwick and company identified in the JAMA article. These two partnerships in particular are going to enable and make available this Catalyst solution on a much broader basis than we’d be able to do on just our own without the partnerships. I’m very excited about that.
Going back to who should lead these, I would encourage the CIOs to step forward and take a big leadership role in these projects. Typically what happens is that the CIO will lead the implementation and lead the selection, then over time, the day-to-day management of the data warehouse tends to migrate elsewhere — towards the chief medical officer, the chief quality officer. I’m a big advocate of the CIO, because so much of the initial implementation is technically driven. I would just encourage CIOs to get out there and really dig into this.
Wearing my other hat for just a minute, The Advisory Board just presented at their national conference in Chicago a really good slide deck on what we should be thinking about in the CIO space around business intelligence. If you can, get your hands on that slide deck and maybe schedule some time with The Advisory Board to go over it. I think it will be a good roadmap for most organizations, and it’s a great tutorial if you don’t have a background in analytics.