At Geisinger Health System, advanced analytics pave the way to better outcomes

Geisinger
Geisinger Health System's Unified Data Architecture collects and analyzes data from various internal and external sources.

Using a high-powered data analytics program, Geisinger Health System is harnessing the power of big data to improve patient outcomes and reduce surgical costs.

The system’s Unified Data Architecture (UDA), implemented in 2015, collects and stores data from patient electronic health records along with external data sources that provide a more robust visualization of each patient’s health, while offering real-time practical feedback to physicians, according to a post published in Harvard Business Review by a group of doctors and physicians at Geisinger.

“The power to process troves of data from various sources, combined with the ability to integrate and store large volumes of data, makes the UDA uniquely positioned to fill the gap left by traditional healthcare data systems,” the authors wrote.

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“The integration of data from Health Information Exchanges, clinical departmental systems (such as radiology and cardiology), patient satisfaction surveys, and health and wellness apps provides us with a detailed, longitudinal view of the patient.”

Over the last two years, the Pennsylvania-based system has seen tangible improvements to patient care as a result of the UDA’s capabilities. For example, the system can quickly scan patient images to detect abnormal abdominal aortic aneurysms allowing the hospital to intervene in high-risk cases.

By integrating specific vital signs, lab results, and antibiotic prescriptions, the system has improved the way physicians identify and treat serious cases of sepsis, an infection that relies heavily on early detection.

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Lastly, surgeons use the UDA to track outcomes as well as surgical waste, allowing the hospital to identify areas of potential cost savings and negotiate new agreements with supply vendors.

Geisinger executives have previously pointed to the system’s early adoption of EHRs that allowed it to integrate data into everyday practice. Although healthcare had been generally slow to utilize broad sets of data, in some systems, analytics has improved antibiotic stewardship and personalized mental-health care.

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