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Why big data, healthcare analytics require key partnerships

In order for healthcare organizations and providers to transition from reactive to proactive care, they will need to rely on new and emerging health IT tools that allow them to predict patient outcomes and provide intervention where necessary. This optimism for big data and healthcare analytics, however, is met by uncertainty as hospitals and physicians grapple with how to implement these solutions into their clinical workflows.
“That’s the part they’re most excited about and frankly that’s where they have the most deficiencies in terms of staff knowledge, tool sets, and capabilities,” says Curt Sellke, Vice President of Analytics at the Indiana Health Information Exchange (IHIE). “Predictive analytics is new enough for everybody that people are looking for a trusted partner.”
To prepare for the move toward predictive analytics, IHIE recently announced a strategic partnership with Predixion Software to develop a solution for accountable care organizations (ACOs) and hospitals in Indiana to reduce preventable readmissions. The partnership brings together two crucial components for healthcare analytics: a rich data set and predictive modeling.
According to Sellke, those looking to adopt healthcare analytics face a couple significant challenges. At the top of the list is access to health data.
“First and foremost is it’s very hard to sometimes to get at the data you need in order to power your analytics,” he explains. “It is spread across different organizations or so many different silos within an organization, that just aggregating, accumulating, and cleaning it is really a tough thing to do.”
Once that data is in hand, the challenge then becomes making that information meaningful (i.e., useful) to providers.
“As you begin to generate some of these analyses you begin to see some trends and measures,” observes Sellke, “Can we make that information actionable, so that not only have you identified that something is happening or perhaps is going to happen on the predictive side? What do you do to intervene to make that better? That’s the second part of this.”
Addressing these challenges is where establishing key partnerships comes into play and why IHIE is beginning its work on predictive analytics and readmissions with Indiana ACOs and hospitals. “We are starting with the ACOs because right now it would have the minimal impact on current workflows. They are laser focused on readmissions because they have both clinical and financial incentives,” says Sellke.
By demonstrating the value of big data and healthcare analytics for ACOs and hospitals, IHIE hopes to build a case for widespread adoption of these tools and services in Indiana and beyond.
“That’s why we’ve chosen the ACO side,” Sellke maintains. “That’s kind of the lowest-hanging fruit, and we figure as we roll out something new can we have it gain some traction, gain some favorable results there, and it makes the job of then bringing it out to a broader group even easier because there’s a case study behind it, return of investment kinds work, etc.”
And as the value of predictive analytics grows, so too should its applicability to other areas of healthcare, claims Sellke.
“Where we’re going to spend our energies over the next three to six months is going into our clinical data repository and sourcing the information that’s necessary to power the model,” he reveals. “There’s a notion that says we would like to be able to be in a position to produce a brand-new model for some specific use case in three- to six-month intervals.”
The adoption of intelligent tools is half of the task of the healthcare industry’s shift to wellness. The other is the collaboration of forward-thinking healthcare organizations, providers, and vendors.
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