HEALTHCARE LOOKS TO INCREASE ITS 'BUSINESS INTELLIGENCE'
By Brendon Nafziger, DOTmed News Associate Editor
Accountable care organizations and later meaningful use stages will require providers to marshal vast quantities of data to meet government requirements. And for many hospitals and clinical groups, data are in a bad state: siloed, buried under redundant entries, and rarely integrated into a single, workable form that executives can use and act upon.
This represents what health care consultant Laura Madsen refers to as the "perfect storm" for the data-centric management philosophy known as business intelligence.
The founder of next week's Healthcare Business Intelligence Summit and the author of a forthcoming book on the topic, Madsen serves as health care practice leader for Lancet Software, a BI consulting firm. She has more than 15 years experience in the field, and has helped dozens of companies with BI initiatives.
Recently, she spoke with DOTmed News about what BI is and why it might be coming to health care in a big way.
DOTmed Business News: To start with, what exactly is business intelligence and why is this becoming more important for health care?
Laura Madsen: I think if you Google business intelligence you get about 3 million hits, and most of them are rather odd, and not very helpful, descriptions of what BI can do.
For me, what BI is, is integrating data from disparate source systems into a visually appealing user interface, so that end users can make better decisions with data. So what does that mean from a usability perspective? There are all kinds of examples of what business intelligence has done for organizations.
In retail, they use it to determine what they're going to put on their shelves. They use a lot of it in coordinating with their customer service manager, to send you very specific coupons. So if you've bought diapers in the last three weeks, they know that you're going to continue to need diapers. So they'll send you coupons for diapers and other baby products.
Hospitals have been using business intelligence in a different way. For example, we're definitely late to the game from an adoption perspective in health care. But if you've been to a hospital recently, a lot of them have flat screen TVs up in the waiting room, that have queues on them, to tell you where your loved one is in the process of getting a procedure done. That's driven by data, that's driven by BI. The billboards we see saying, "6-minute wait times at St. John's," that's BI driving those things.
DMBN: In health care, where is BI most prevalent?
Madsen: If we would categorize maturity level against other industries, like retail and finance, we are behind the times, so to speak. If you categorize it within health care itself, payers versus providers, I would say that payers are pretty well advanced compared to their provider counterparts. And obviously ACOs will force that issue quite a bit.
DMBN: How will ACOs push providers into using BI?
Madsen: The interesting thing about ACOs is the spirit of the "requirements" for ACOs is really metric driven. [Providers] have to prove that care is being approved and costs are being driven down. And what payers and providers are coming together to form ACOs have recognized, the payers are far more advanced in their data management methodologies, their data warehousing capabilities, and their ability to analyze these data. And providers are starting to feel a little bit of pressure to up their game, because they have to come to the table with their corresponding data.
In order for ACOs to be successful, that's a requirement: providers have to improve their data management capabilities. That, along with meaningful use, of course, has certainly forced the issue for providers, and I think that's what we're seeing for health care BI.
DMBN: When it comes to BI, is it harder for smaller hospitals, rural hospitals, clinical groups or imaging centers to adopt these methods - just in terms of having people on staff to implement this? Is it harder to bring to smaller organizations?
Madsen: It is. That's one of the challenges we have as a health care industry, when we start talking about data management, or BI, the majority of our care is delivered through these smaller organizations, at least from the patient's perspective. And these folks don't have the kind of money lying around to create a really large, enterprise-scale BI or IT team, to meet the spirit of a lot of these requirements.
For instance, I've talked to a number of groups that have decided not to proceed [with meaningful use, stage 1]. They've done some analyzing, they realize their Medicare and Medicaid billings don't make up for the gap from a spend perspective, and they decide to hold off for a couple of years, to see where it shakes out, because of the potential change in administration in the next year or so.
I do think it's a real challenge for these small to mid-sized organizations. That's actually where we specialize, where Lancet specializes. I work almost exclusively with small and mid-size companies.
DMBN: What are the failure rates for BI implementation?
Madsen: Well, it sort of depends on who you ask. But it's been quoted as being as high as 70 or 80 percent for the first time out for an enterprise BI program. It's very challenging to do these programs and do them well. It's sort of like boiling the ocean. I don't feel that health care organizations, as a whole, are in a position to boil the ocean right now, with everything going on. And to be honest with you, I think that would have been true regardless of the HITECH Act of 2009. These types of enterprise programs are really tough to do, and I don't know that that's the most efficient way to get things done.
I think a very thorough, thoughtful, pragmatic approach, that maintains a lot of agility, that's what I've seen work. So for example, I've worked with a provider organization in Louisiana, and what we did was build out a program - a series of dashboards for them - in the first six months. And those dashboards were very specific to the key performance indicators they used to run their organizations. That meant integrating a lot of data, including financial data. And once they got that part started and they got their users to understand what this could be, then they started doing little things to continue. So they began adding more data, they added traditional ETL scripts (Extract Transform and Load, a concept of data integration that brings the data together from a financial perspective as well as clinical perspective). Those very short sprint projects that deliver value to your end users as quickly as possible, those things are what are really successful.
DMBN: Are there common failure points that organizations should watch out for when starting up BI?
Madsen: That's a hot-button topic in the BI industry - lots of argument about that, and some heated ones too.
It's like the show on National Geographic, "Anatomy of a Crash." The idea there is there's never one thing that brings down a building or a bridge or an airplane. It's always a series of mistakes that in and of themselves seem really minor, but in connection with all the other things that we do, tend to bring down bridges. So for example, in a BI deployment, there are a couple of what I consider keystones, really critical things you have to build out for a BI program to work. And if you skip those, it could lead to the "Anatomy of a Crash" - from a BI perspective.
For instance, I personally believe that from a programmatic perspective, you need executive sponsorship. Your executives need to at least buy into the idea, and give you a little bit of leeway to get the job done.
You also need to build a really solid foundation, and that is both data modeling and this idea of ETL capabilities. A data model is, if you think about it, a blueprint for how data relate to each other. And for health care, that's incredibly important because of the nature of the relationship between a patient, a physician and all the corresponding things to go with that: procedures, lab reports, claims, prescriptions. All these things are related. If you don't have that blueprint that shows you how they relate, the hallway going to your bedroom and bathroom, so to speak, you're going to build a house or data model that won't allow you to gain access to your bedroom. You need to build that infrastructure, that data model, early in your stages to build the right foundation. You have to build in good ETL scripts to provide the right kind of translation from the raw data to usable data, and that's the primary function of ETL. Health care data in its raw form is pretty unusable.
DMBN: What are some problems your customers wouldn't have been able to solve if they hadn't implemented BI?
Madsen: So a provider organization out in Louisiana, one of the challenges they had was they had grown through acquisition and they had about six different EHRs. And they didn't have a good integrated perspective of their data, neither from the financial nor the clinical side. They were providing care to the elderly and infirm, and they really needed to understand how many interactions they were having with any given patient on any given day, and they didn't have good access to that because of the disparate views of their data. So we came in, we integrated these data for them, we created dashboards that would allow them an integrated view of their financials as well as the number of times they were interacting with their patients, versus how many times they had planned on interacting with their patients, so they could identify gaps in care.
DMBN: It seems like in the next couple of years, with later stages of meaningful use, the establishment of better medical product tracking codes, etc., there's going to be a lot of data hospitals will have to deal with.
Madsen: It's all part of the perfect storm. Data is rushing in. I like to say, "Data, data, everywhere, but not a drop of knowledge." We really need to find a way to take advantage of the data and have that data provide us with information. Data by itself is just bits and bytes; it doesn't help us make better decisions. We really need information that can help us. That means you have to decide what information you hold in your data warehouse. And really the best way to do that is through these formal processes that have been well-practiced in other industries, called data warehousing and business intelligence. And I think that health care organizations have realized that this is the way to go.
About the Healthcare Business Intelligence (BI) Summit
For more information, check out the Healthcare Business Intelligence (BI) Summit, to be held Oct. 12 from 7:30 am to 4:30 pm at the University of Minnesota's McNamara Alumni Center in Minneapolis, Minn. To register or learn more, go here: www.healthcarebisummit.com.
About Laura Madsen, MS
Laura Madsen, MS, helps companies understand the value of their data and how to optimize its use. She is currently the healthcare practice leader for Lancet, a provider of business intelligence design, analysis and implementation. She previously served as BI director at a pharmacy benefit management company where she led an enterprise-wide BI project, and is a veteran of United Health Group, where she managed a BI tool suite. In Madsen's 15 years of experiece she has started or supported dozens of companies with data modeling, warehousing, analytics, and reporting. Madsen founded the Twin Cities chapter of The Data Warehouse Institute (TDWI) and is frequently called upon to write and present on healthcare BI best practices.