Health IT Pulse

Jun 21 2013   12:55PM GMT

Clinical data analytics still in infancy, as big data gets bigger

EmilyHuizenga Profile: EmilyHuizenga

clinical data analytics

When it comes to optimizing clinical data analytics in hospitals, IT leaders say the age-old adage rings true: If you can’t measure it, you can’t manage it.

In a recent webinar, IDC Health Insights research director Cynthia Burghard said even though healthcare hasn’t historically been a data-driven industry, organizations are starting to realize that outcomes aren’t necessarily improved by clinical endeavors alone.

“When you start to have really strong data behind you that allows you to make decisions that impact the business, that’s when you start to see the value,” she said.

Burghard said in the past, payers have utilized retrospective data for analysis. Strategically streaming data access is new to hospitals. According to a 2012 IDC Global Technology and Industry Research Organization IT survey, 50% of payers invested $1 million to $100 million in big data and analytics technologies last year, while a little less than 20% of providers did.

“Providers are bogged down by implementing electronic health records [EHRs] and meeting meaningful use requirements,” she said. “They typically invest more slowly in technology because their investments in the clinical arena are more significant.”

But, Burghard continued, the volume of healthcare data is increasing. As new structured data emerges from insurance claims, EHRs and remote patient monitoring sensors, it will add to a heap of unstructured data gleaned from clinician notes and trends in social media.

“The ability to manage the speed of that data coming in, to understand how to parse it and decide what to save, is going to determine the value the data drives,” she said.

Burghard said the survey revealed another discovery: the biggest challenge providers cite in using big data and analytics is not technology, nor hiring the right IT staff with the right skills; it’s deciding which data is relevant.

“There is a lack of understanding of how to operationalize the big data stack and capabilities. Hospitals ask, ‘Once I have the information, what do I do with it?’” she said. “Decisions of what to analyze are driven by the business question being asked, and the ability of organizations to consume that degree of technology is going to lead to new business models.”

Burghard addressed what she called “vendor clusters” as well. She described an influx of niche infrastructure vendors who specialize in data organization and management or analytics and discovery, sometimes building out applications for other functionalities for healthcare providers. But, she said, few can do it all.

“It’s going to require a number of different vendors at play,” she said. “Vendors may offer different capabilities, so the challenge is going to be integrating them to make a stack that addresses the assets and skills of each.”

Furthermore, she said, some vendors are facilitating “tremendous” use cases for fraud detection and waste reduction, as some hospitals use data analytics to prevent extraneous spending. Meanwhile, other companies are taking human genomes into consideration to personalize medications.

Looking forward, Burghard encouraged hospitals to start by taking a step back and seek out untapped data assets they already have.

“Recognize the implications of operating without critical information, [then] ask yourself how you can become a fact-based decision maker,” she said. “It’s not so much the data, it’s what you do with it, and that’s why return on investment is difficult to calculate. What’s the ROI on our ability to make better decisions?”

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