Trevor Strome is process improvement lead in the Emergency Program at the Winnipeg Regional Health Authority in Winnipeg, Manitoba, Canada, as well as an assistant professor in the Department of Emergency Medicine, College of Medicine, Faculty of Health Sciences, a the University of Manitoba.
This spring, Strome published a new book, Healthcare Analytics for Quality and Performance Improvement, published by Wiley, and available on Amazon. He also blogs regularly on a variety of healthcare topics.
Strome is one of the conference chairs for the Health IT Summit in Seattle, to be held August 19-20 at the Seattle Waterfront Marriott, and sponsored by the Institute for Health Technology Transformation, or iHT2. Since December 2013, iHT2 has been in partnership with Healthcare Informatics through HCI’s parent company, the Vendome Group LLC. Strome spoke recently with HCI Editor-in-Chief Mark Hagland regarding the publication of his book, and his perspectives on healthcare IT, quality improvement, and executive management in patient care organizations. Below are excerpts from that interview.
Congratulations on the publication of your book. What made you decide to write it?
I’ve been working in the field for a long time, and the work I do crosses over from technology into management and leadership, and quality improvement. I work a lot with these different teams; and in my experience, technology, management, and IQ were always tightly linked in their activities, but acted as though they were living on different planets, right? So the QI guys would have all these requirements for data, but didn’t know how to connect to IT. And the people in IT didn’t know the first thing that these Six Sigma black belts needed. And the management and leadership teams sort of saw these groups as being in different worlds, and didn’t know how to bring them together.
So when I was leading QI teams, I was always frustrated that there wasn’t as much connectedness as needed. So when I was given the opportunity to write the book, I wanted to help connect the dots between and among those three groups.
Making all this work successful requires bringing everyone together at the same time, all the stakeholders, and speaking the same language, to get good initial data inquiries/queries, then, correct?
Every analytical question starts out best with a good, well-formed question, right? So what are we trying to do? Decrease sepsis? Decrease lengths of stay? Improve patient satisfaction? So there’s got to be a good question about that. And then once we know what we’re tackling—the projects that work the best start with a good perspective. So say we’re doing a lean rapid improvement event, or a Six Sigma DMAIC project [define, measure, analyze, improve, and control]—we start out with integrated teams. I’ll make sure we have strong clinical representation from medicine and nursing, strong management representation, and obviously strong QI representation; and then the IT folks and the analytics folks—and sometimes, they’re the same people and sometimes not.
And then the QI people start to formulate a way to better understand the problem; the IT and analytics guys can work with them to sort of better work out how to proceed, and they become familiar with concepts like run charts and other ways to present data—improving their familiarity with QI concepts. So then what we’ve seen is an incredible amount of brainstorming and synergy happening, where the data guys and the IT guys are able to deliver information that’s useful, and are able to come up with information that’s more useful, and more useful vehicles. So we’ve been able to generate dashboards, monitoring, real-time alerts, etc.
How do you see the role of IT managers and leaders in these performance improvement projects?
The way I think IT managers need to be is they need to be enablers. And they need to understand that our best work projects happen when the people with the creative ideas are unencumbered. Ideas will percolate naturally out of QI brainstorming. And if we keep QI and IT separate, they’re working in their own separate worlds, so the QI people don’t know what’s possible, and the IT people don’t know what the QI people need. So we get into this traditional cycle of QI people having to track down the data or ask for a data dump or whatever; but now, when our teams work together, all this innovation can happen. And the QI and IT people are talking from the beginning, and can build things better. So it all has to start at the very beginning, because if the QI and IT people come together too late on a project, a lot is lost.
How do clinical informaticists—physician, nurse, and pharmacist informaticists—fit into all of this?
Those are the types of people who do have that vision of everything coming together. And they see how IT and QI can come together, and how that synergy can then improve management’s work on quality across the organization. We are lucky enough to have a CMIO here at Manitoba eHealth, who has great vision, and he and I have some very outstanding fruitful discussions in terms of the role that Manitoba eHealth, our IT group, can play, in facilitating a lot of these projects. So he works as an enabler and cheerleader and works to help us overcome barriers and eliminating silos. He has a lot of credibility that those of us who are not clinicians may not have. And the thing is that our CMIO has, and the best CMIOs have, that enthusiasm for leveraging technology to solve problems.
Can you provide any examples, either from your organization, or more broadly, from the industry?
Having effective analytics within an organization sometimes is a bit of a chicken-or-egg situation. I personally believe you need to have very strong vertical connections between what’s happening at the tactical level and at the strategic level with senior management, per the overall goals of the organization. You need those kinds of connections for analytics to function well within the organization; and you need the analytics to help things get established. I’ve noticed in our own organization and more broadly, that things start to polarize in a good way, when things start to align. So when senior management sets aside three or four very salient quality goals, and then create metrics around what we’re trying to achieve, and various departments within the organization are able to rally around those goals, and then they define their own sub-goals and targets, to achieve that overall goal. And then everyone starts to work towards the same goals and objectives. And the analytics tools help both senior management and the tactical level have visibility. And that starts to move things forward, so when we start to achieve some of our quality goals in a unified, aligned sort of way, we can move forward on additional quality objectives.
And I think that this is different from in the early days of analytics, when we were faced with tons of ad hoc, unrelated requests. Obviously, not every single thing that every ward is going to do is going to align with the overall strategic goals, but at the high level, it should. There’s a parable about putting the big rocks in your jar first and then the small rocks, and then the sand, to fit the maximum amount in a jar. That’s sort of what we’re trying to do here.
Do you think the level of understanding of all this is advancing in North American healthcare?
I think it is. And we see a lot more discussion around making sure that everyone’s on the same page. And a lot of the lectures I’ve been doing in the past year have been focusing on what I covered in chapter 3, establishing an analytics framework—making sure we have the right tools, the right infrastructure, to support these activities. And there are some templates in the book to help with that. And all that material has been very popular. People are interested in addressing these analytics gap. There are a few gaps: there’s a talent shortage; but then there’s also a gap in what healthcare organizations need to know about their performance and quality, versus what their analytics are currently providing them. So I think when those two major gaps are addressed, healthcare organizations get a lot more value out of the tools and people they have, and are able to get performance improvement done in much more effective ways.
When we meet in Seattle as a group, what will be your hope for some of the discussions?
I think there are really some good discussions to be had on population health management. And one of the speakers I was able to bring in, who’s from Vancouver, Jat Sandhu [Jat Sandhu, Ph.D., the regional director of the Public Health Surveillance Unit, Vancouver Coastal Health Authority]. And I think that at the last several iHT2 events, as well as a few of the other events I’ve been going to, there’s been increasing discussion and understanding of population health management, and around how we can use big data and analytics to keep populations healthier. And obviously, healthier populations result in longer-term reductions in costs. And that benefits everybody. But we’re in such a state of flux right now. And with the Apple/IBM merger and other developments, there’s a lot of promise for healthcare-related apps. We haven’t even scratched the surface in terms of gathering together data about our populations. And I think that’s going to blow everybody’s mind.
And I do a lot of work with emergency department stuff. And if we’re doing population health management data, imagine if we can predict what kinds of situations people will be bringing into their ED visits with, right, based on what’s going on on their Fitbits, for example? Or looking at the use of social media to predict emergency department visits? There’s been at least one paper on linking things like Google flu trends… We’ve been comparing some of our data to Google flu trends and have been finding connections between Google searches around the flu, and correlations with ED visit volume for flu, for example. And in the summertime, things get pretty hot, and if we had a program where we could scan comments in Twitter about the heat, we might be able to predict increases in ED visits for heat exhaustion, and such. We’re in the very earliest days for being able to do that, so that’s where some of the value will come out of big data and analytics. And we want to be on the forefront as that technology becomes stable and usable.
What would your advice be for CIOs and CMIOs in all this?
I guess my advice would be to recognize that we need to start thinking outside of our silos. And is it really a bad thing if our business intelligence and analytics resources want to be trained dup on things like Lean and Six Sigma? Is it a bad thing that rather than keeping your BI guys and analytics developers at their desks all day, but instead put them out on the front lines to learn what’s going on? At the end of the day, I think we all need to be agile. The needs of healthcare are changing, and we need to be responsive, and getting better at being proactive. And the only way that’s going to happen is by having tight connections between our IT folks, quality folks, and clinical folks, and getting everyone on the same page and working together on our healthcare transformation initiatives.