September 01, 2017 12:05 - x 00, 0 - 00:00
Big data analytics is turning out to be one of the toughest undertakings in recent memory for the healthcare industry.
Providers who have barely come to grips with putting data into their electronic health records (EHR) are now being asked to pull actionable insights out of them – and apply those learnings to complicated initiatives that directly impact their reimbursement rates.
For healthcare organizations that successfully integrate data-driven insights into their clinical and operational processes, the rewards can be huge.
Healthier patients, lower care costs, more visibility into performance, and higher staff and consumer satisfaction rates are among the many benefits of turning data assets into data insights.
The road to meaningful healthcare analytics is a rocky one, however, filled with challenges and problems to solve.
By its very nature, big data is complex and unwieldy, requiring provider organizations to take a close look at their approaches to collecting, storing, analyzing, and presenting their data to staff members, business partners, and patients.
What are some of the top challenges organizations typically face when booting up a big data analytics program, and how can they overcome these issues to achieve their data-driven clinical and financial goals?
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