"One of the things I think we maybe underrate is the ability to access this analytics, seamlessly within the workflow and environment," says Shulman.

"That can help providers access additional patient analysis and population analysis from within the same environment that they're accessing their EHR and performing their documentation," he says. "We're working with clients now that have a seamless link from within their EHR to our single patient report that offers those patient and provider analytics."

He says he's hopeful initiatives such as HL7's FHIR specification, and the open APIs more EHR vendors seem to be embracing, will pave the way toward more meaningful use of clinical intelligence.

"Can an analytics tool using data from multiple EHRs, like ours does, from multiple claims and payer sources, create a more meaningful transition of care or care planning capability than what currently exists?" he says. "That could be a game-changer."

Healthcare – which as recently as a decade ago was predominantly paper-based, let's remember – has shown an impressive willingness to go where the data takes it these past few years. More and more providers, for instance, are adding a new C-suite role: chief data officer.

One of the newest and highest-profile CDOs thinks that's a trend that will continue.

"We're moving beyond a system where it's, 'Send us the claims and we'll write you a check,' to one where these organizations will have to effectively manage patient populations," says Centers for Medicare & Medicaid Services CDO Niall Brennan.

"They'll have to learn to interpret performance data that they're receiving back from payers and integrating clinical data from the their electronic health records; unlocking the data that lives in EHRs will be key for many organizations to attain success in this rapidly changing landscape."

Into that landscape, more and more companies are coming to hopefully broaden the adoption and appreciation C&BI tools, such as Apervita, a platform that enables the sharing of health datasets, evidence-based algorithms and other tools, enabling providers to share and access them to a market of other providers.

One recent example is Mayo Clinic, which is sharing some of its algorithms for cardiovascular care, with the hope that other providers can learn and improve using the insights it's gleaned over the years.

"We are sharing our algorithms to empower others to deliver patients the best healthcare," said Paul Friedman, MD, Mayo's vice-chair of cardiovascular medicine, in a statement. "One algorithm we are sharing through the Apervita Market assists physicians by quickly sifting through data, and automatically identifying patients at risk for sudden cardiac arrest for an appropriate consultation."

Meanwhile, analytics advancements continue to offer new, more user-friendly approaches to EHR user interfaces and clinical decision support – including one advance that can help fight the dangers of alert fatigue.

HIMSS Analytics Executive Vice President John Hoyt recalls getting an email from a researcher recently that read: "Pop-up alerts are so yesterday."

"What he's saying is they have a lot of these background processes that are running that have these multiple variables," says Hoyt. "And you're going to get a little yellow flag when I think your patient might be going down hill; it's going to turn red when the patient truly is going downhill.

"It's not one pop-up, it's just a series of values: lab, respiratory, all kinds of things," he says. "And that's a background process that's running constantly. You don't know it's there until it starts to sense something is wrong. That's the next future."

Hoyt points to another similar project he's seen that involves "a 42-variable algorithm running constantly, predicting the likelihood of this patient being readmitted in 30 days.

That's the future. It's not just if/then pop ups; it's these background processes that are analyzing multiple variables."

When HIMSS Analytics awards Stage 7 status to an elite group of a couple hundred hospitals, a strong deployment of clinical and business intelligence is one of the biggest must-haves: "Their analytics program has to become robust," says Hoyt.

What does that mean, exactly?

"Look for problems," he says. "Use your analytics to find problems – of quality, safety or efficiency. Redesign your processes and use your analytics to show improvement. That's what we require of Stage 7: Show us three case studies of a problem where you've made some modifications, and you're tracking improvement."

Crucially that "has to be something profound," says Hoyt. "Don't just tell me, 'We've figured out our patients come from the following ZIP codes. Big deal. We could have done that 30 years ago. Show us clinical, safety or efficiency issues you're trying to fix."