‘IT cannot explicitly drive your analytics and big data efforts; the drivers need to come from the business and clinical side’
May 12, 2015
HIMSS Analytics’ DELTA Powered Analytics Assessment, developed in conjunction with the International Institute for Analytics, is an industry-first maturity benchmark to track how well health providers are making use of their data for clinical and business intelligence. (The DELTA stands for Data, Enterprise approach, Leadership, strategic Targets, and Analytical capabilities.)
[See also: Some providers more ‘mature’ than others]
While provider progress on the scale has been incremental over the past year, says James Gaston, senior director of maturity models at HIMSS Analytics, the embrace of C&BI tools has certainly been in earnest.
“The biggest thing we’ve seen is a huge amount in the healthcare provider space to begin to build up basic analytics capabilities or advance current capabilities,” says Gaston.
[See also: Allina goes all in for outcomes with Health Catalyst]
His colleague Lorren Pettit, vice president for market research at HIMSS, has seen similar signs that healthcare – at long last – is starting to see the transformative potential of analytics, just as most other industries have for years.
Attending the American College of Healthcare Executives’ 2015 Congress on Healthcare Leadership this past March, Pettit noticed that “a lot of the focus and discussion was on the need to bring data analysts into our industry.
One topic that was much talked-about was the fact that “it’s not necessary that healthcare people are the analysts,” he said. “There are data scientists that do a lot of this work.”
Many of them would be more than happy to help make sense of some of this stuff for clinicians, staff and IT folks with so much else on their plates these days. With hospitals swimming in data, smart analysts could be better brought to bear on deriving insights from it all.
“That seems to be a gap that’s being acknowledged more and more by those who are in the know,” says Pettit. “When we talk about big data, people are now starting to recognize that there are a lot of challenges. And part of that is just: ‘Who’s going to do the heavy lifting on this?'”
The question, he says, is “how do we bridge that gap between people who are data scientists and the need to tell the story in the context of healthcare.”
Outsourcing may be one strategy, for those so inclined – even if it’s not on the scale of the bold deal announced in January by the 12-hospital, 90-clinic Allina Health – which, in exchange for a $100 million investment in Health Catalyst, will outsource its data warehousing, analytics and performance improvement projects to the company.
Even if pure outsourcing, even on a much smaller scale, doesn’t quite look to be a looming trend, however, “people are recognizing the challenge,” says Pettit. “We have this skill set is required; where are we going to get (analysts) from, how do we engage them?”
And there are challenges to bringing in analytics mavens who may not be able to speak the lingua franca of the modern hospital, he adds.
“One of the ways big data could actually fall apart is if we bring in data scientists and they don’t know how to connect with the audience,” says Pettit. “If they’re all about talking about their methodology, but are unable to connect and tell (senior leaders) why it’s important, that’s one way that the audience would just marginalize them and move on.”
That sensitivity to the business or clinical imperatives of an organization is key, says Gaston.
“IT cannot explicitly drive your analytics and big data efforts,” he says. “The drivers need to come from the business and clinical side. And what I’ve seen in most organizations recently is they’re putting a lot of this focus on data from the CMIO’s office.”
That particular C-suite role “has a pulse on how is the organization delivering healthcare,” he explains. “He or she has the best opportunity to identify areas that could benefit, whether it’s with just plain Jane basic analytics and reporting, or more advanced predictive analytics or leveraging big data.”
On the other side, of course, are the business decisions, normally under the purview of the CEO and, especially the CFO, who is “driving accountable care contract negotiations,” says Gaston. “Or they’re beginning to wrestle with the transition from fee-for-service to fee-for-value, and contracting and organizational cost structures that begin to protect they’re competitive advantage.”
On both sides of the coin, one thing holds true: None of these decisions are optional. The transition to value-based care is here, and here to stay. Even more than that, CMS has set even more ambitious timelines in recent months, aiming to increase the speed with which even larger percentages of patient encounters are done within the rubric of accountable care.
Slowly, providers are starting to realize this.
“One of the first things we’re seeing organizations do is begin to stratify their organization,” says Gaston. “They want to stratify their physicians, and how they practice and what they charge and how they bill. They want to stratify their patient population: Who are their patients? Where do they come from? How do they engage with the organization? Is it primarily acute care setting services? Is it ED services? They want to see how frequently their patients engage with their organization.”
Next, he says, “they begin to stratify their organization as a whole: ‘At what level are our departments performing at, holistically? And how does all of this work together?’ It boils down to how do we identify those areas that might help us with fee-for service billing, but could be seen as a liability or great expense for the fee-for-value area we’re dipping our toe into.”
And how does the technology itself fit into all these big plans? Are providers making the right choices when it comes to IT deployments?
“I think a lot of providers aren’t necessarily jumping off a cliff and buying big data warehouses and big analytics solutions right now,” says Gaston. “A lot of providers are leaning toward homegrown solutions and using readily available tools.”
Even something as seemingly humdrum as Microsoft Excel, after all, can help turn raw data into insights and knowledge.
Providers are “using what they have on hand, in beginning to find their way around their data,” says Gaston. “We’re still at the point where we’re trying to develop analytical skills and capabilities, and this hasn’t been broadly operationalized yet.”
At HIMSS15 in Chicago there were countless companies purveying all types of clinical and business intelligence tools, touting the analytical insight they could offer toward better population health. Still, it’s early.
“There are certainly a lot of vendors out there doing exciting things, but there’s no one tool or collection of vendors where you can say these are the leaders in this space in healthcare analytics,” he says. “There’s a lot of play out there and a lot of opportunities.”
Healthcare may lag other industries in its analytical prowess, but just think how far it has come.
“When managed care was proposed and tackled decades ago, the IT horsepower wasn’t there to back it up,” says Gaston. “People didn’t have the data, we certainly didn’t have electronic medical records. Or as broad access to claims data as we do now.
“Other industries have led the way in information technology that supports analytics and data-driven decision-making, and it’s very well-refined: retail, manufacturing, Internet companies have advanced that tremendously and there are examples all around us,” he says.
“But healthcare is a much more complicated industry, and that leads to some of the problems why some of the traditional tools don’t fit very nicely.”
But certainly “the horsepower is there across the board,” says Gaston, “and some of the best opportunities are being exploited and developed by a big broad swath of people eager to demonstrate analytics prowess.”
Geisinger has spun off its C&BI tools into its xG Health Solutions subsidiary, bringing its renowned accountable care and pop health technologies to market. UPMC is marketing its analytics. Mayo Clinic, too.
“And it’s all good stuff,” says Gaston. “I think the trick is going to be what is right for your organization and a good fit. For your geography and demographics. the size of your organization. And your maturity – are you ready to embrace those tools and put them into play?” So much “depends on the organizational dynamics,” he says.
Still, there’s no question that skepticism remains about just how much all this data can actually accomplish for your garden-variety provider.
“When you think of the Gartner Hype Cycle, big data is sort of right near the pinnacle of the hype cycle,” Pettit suggests. “If we follow the cycle, I wouldn’t be surprised if (soon) we start getting into the downside. There’s been a lot of hype, promising the moon, now what does it actually look like. Is it worth it? There will be a lot of questioning around that.”
That said, “big data does have big promises,” he adds. “But we need to be discerning in what these promises really are. And as with anything – as we saw with EMR adoption – there are costs associated with it. It’s not going to bring world peace. But it is going to bring improvements in healthcare.”