Future predictions for PACS

未来预言为PACS

Carol Ko, Staff Writer | February 20, 2014
From the January/February issue of HealthCare Business News magazine


Mother tongue
Collaboration is a large part of what’s driving one of the biggest trends in PACS and one of the most buzzed-about terms at RSNA this year: structured reporting.

The ultimate goal for health care is to be able to form a master database of patient data, informatics, and image archives that spans all hospitals in the U.S. Ideally, doctors should be able to pull up a patient’s medical records across multiple facilities, not just one. Whether hospitals will achieve this dream without further government intervention remains to be seen.

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Currently, hospitals lack a standard way of recording patient data, meaning some hospitals jot down codes in a non-standardized, and often haphazard, way. This is slated to change in the fall when hospitals will be required to standardize their universal coding and disease classification to ICD-10

“What we’re being driven toward is a much more precise vernacular,” says Steve Hamburg, director of RIS Sales at Advanced Data Systems.

If, say, a patient was admitted into a hospital for a torn knee ligament, the ICD-10 coding would be specific right down to whether the right or left knee ligament was torn.

The coding can be specific almost to the point of being comic. “There are actually ICD-10 codes for accidental injury for paintball guns,” Hamburg says. “There are 14 different guns relating to paintball gun injuries.”

Hamburg predicts this will rock the industry, likening it to a sudden natural disaster rather than a trend. “A trend is gradual. This is like a tsunami,” he says.

The advantage of a universal coding system is clear: doctors will be able to access macro-level data around, for example, a certain kind of slow-healing fracture. “You never had that data before, but now you do,” says Hamburg.

Ultimately, more precise coding leads to better data around the efficacy of treatments. It also ties in with a larger trend around increasing the level of quantitative data in imaging.

“Once you have structured reports, the data can now be available for data mining,” says Primo.

At the New York Imaging and Informatics Symposium last September, Dr. Eliot Siegel, professor of diagnostic radiology at University of Maryland, gave a presentation in which he stressed the importance of mining quantifiable data from images.

He envisioned every patient’s image studies being saved and incorporated by decision-supporting algorithms to help physicians make better choices when treating patients. “Every patient’s medical care would become a clinical trial,” he said.

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