The flood of data entering healthcare organizations will only grow as more information is shared between more healthcare entities in an effort to more accurately approach patient care, especially in regard to data analytics.

What’s behind this data push? Right now, I’m seeing two trends prompting a shift toward greater data analysis: 1) healthcare reform’s shift to value-based care; and 2) ever-growing concerns around patient safety. From growth in the number of ACOs to team-based reimbursement structures and rewards for healthy population outcomes, accurate review, sharing and measurement of data has never been more important. Likewise, to increase patient safety and quality care, accountability for both treatment successes and errors must be measurable and actionable.

The takeaway is that, going forward, all healthcare data will matter. And analytics will become crucial to forwarding all aspects of care. But as organizations continue to struggle with data silos and disparate storage systems, it’s clear much infrastructure change is still needed.

In the end, to achieve greater data integration across structured data (lab reports), unstructured data (images, notes), EMR files and patient-generated data, visualization must be achieved. This entails optimizing the data architecture for the most effective analytics capabilities. At a high level, this solution boils down to balance — of the compute, storage, software and network aspects of a healthcare organization’s data infrastructure.

With balance comes the key to unlocking the true potential of data analytics for patient care.

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