Does every healthcare organization need a well-thought-out analytics strategy? Or can some skate by, case-by-case, with ad hoc data projects? For advice on this question, one could do worse than checking in with Geisinger Health System.

The short answer? Not necessarily.

"The point at which you really need a strategy around your data is the point at which you decide to start making secondary use of it," says Nicholas Marko, MD, Geisinger's chief data officer.

Data gets generated every day, in every care setting, large or small. The strategic question is what happens to it next.

"If you're going to bank it and just use it in your EMR in a transactional way to provide care, there isn't a ton of strategy associated with that. You just have to make sure you manage your EMR right."

The real need for a data strategy emerges when "you decide you're going to start using your data as an asset to do something specific with, to extract some kind of value from," Marko says.

An even shorter answer, in other words: Yes.

Because in this fast-moving new era of value-based care, of quality measures and accountability, risk and reward, healthcare organizations of all shapes and sizes need to be doing things to derive efficiencies and improvements from their data. Otherwise, they won't last long.

"When you decide you're going to start mining your data, using your data to ask business or clinical questions, when you're going to start looking at the information you collect, that's when it pays to start being strategic," says Marko.

Marko cautions that data initiatives don't usually show direct outcomes at first. 

Learn more at the Healthcare IT News Big Data and Healthcare Analytics Forum in San Francisco, June 14-15, 2016. Register here.

"They're the thing that allows somebody to do something else that allows someone to do something else that generates an outcome. You're always a step or two removed from the real point of value-generation or implementation. That can be very frustrating for people: 'We're doing all this data stuff, but it's hard to put numbers on paper.'"

So what an organization has to decide, early on, is "how am I going to know if I'm doing it right?" he says. "How am I going to know if I'm being successful – based on whatever my definition of success is – with the things I'm doing with this data?"

The good news? "It doesn't have to be elaborate: You may not be planning to do a whole lot of different things with it, and so you may not need a very complicated strategy – just plotting a course for where you need to go," he says. "Or you may decide you want to engage in some giant enterprise project, in which case you may need a more comprehensive or more complex strategy."

This article is part of a series focusing on big data and analytics. Other pieces include: Geisinger's guiding principles for moving away from one-off analytics projects toward a data-driven culture and Analytics or BI? Centralized or federated data? Geisinger's CDO shares insights.

Twitter: @MikeMiliardHITN
Email the writer: mike.miliard@himssmedia.com

Like Healthcare IT News on Facebook and LinkedIn