Some providers more ‘mature’ than others

April 18, 2014 in Medical Technology

 

“The percent of hospitals with clinical data warehouse and data mining has grown considerably in the past year,” said Gaston. “Hospitals are collecting more data — what they are doing with that data is another thing.”

[See also: Geisinger shows how data drives change.]

As providers strive to implement and then effectively use business intelligence tools — moving from descriptive analytics to prescriptive analytics, to, ultimately, predictive analytics — many of them are still trying to figure out the best way to go about it. 

The findings of the survey bear this out:

  • Most providers say analytics as important but have only reached moderate levels of maturity.
  • Leadership is key: organizations with chief analytics officers on the executive team are more advanced than those that don’t.
  • Big data is viewed as one of the least important competencies by hospitals — a big contrast to other industries.
  • Executives are much more critical of their analytics performance others in their organization.
  • Providers with the highest analytics maturity place high importance on the use of data throughout the organization.

That last one is key, said Gaston: “We expect it to apply across the entire organization — not just to the clinical side, and not just to the business side.”

 

From the C-suite to clinicians to administrative staff, “everybody needs to embrace analytics for it to be part of the culture and mature,” he said.

 

The DELTA assessment is meant as a new tool for organizations to be able to benchmark their analytics readiness and point the way toward strategies to improve.

 

“How do you know if your organization is good at analytics? For a lot of us, who aren’t Geisinger, we have to figure out,” said Gaston.
 

And that’s not easy. Gaston remembered back to his time working at a provider, where business intelligence amounted to an “analyst with messy data, working on a PC In a back room, whacking at it, trying to make sense of it. And coming to a conclusion about what should be done, or what happened, after the fact. Not necessarily in real-time.”
 

Even that arduous process is valuable, however: “What that does is it allows you to understand what your data is saying, what your data quality problems are — and begin to streamline and understand that model that you create around that particular decision point,” said Gaston.
 

“It’s a struggle,” he admitted. “You’ve got lots of data and you’re trying to enable people to make decisions. How does that actually happen? There’s no turn-key solution. There’s no pixie dust.”

Download a copy of the DELTA Powered Analytics Assessment Benchmark Report here.
 






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