Auto-Surveillance Tool to Help Boost VA Health Data

A new computing method created by a national lab can help the Department of Veterans Affairs route out machine-generated errors and help bolster overall quality and safety of healthcare data.

A study led by Oak Ridge National Laboratory looked at the interface between VA’s healthcare data system and the data itself to detect the likelihood of errors and designed an auto-surveillance tool.

The technology can scan data for more than 1 million patients and send system error alerts for VA to review and address.

“Similar surveillance tools can detect human errors, but our major focus is routing out machine-generated errors that could lead to unintended consequences in health IT,” said ORNL’s Olufemi Omitaomu, co-author of the published study, in a June 3 announcement. 

The next stage entails machine learning techniques for smarter, faster error detection. ORNL said over time, the VA technology will run smoother, more accurately and efficiently in real time, allowing a faster response to potentially dangerous conditions in or functionality of health IT.

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