FEB 12, 2013 11:54am ET

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Validating Medical Device Data Streams

FEB 12, 2013 11:54am ET
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Medical devices produce data almost continuously as a byproduct of their main tasks, such as dispensing medication, keeping the patient supplied with air, or monitoring vital signs.  Two HIMSS presenters from The Ohio State University Wexner Medical Center will describe how the hospital is capturing, validating, and using that bounty of data.

 

“We can put a couple of hundred different data elements into a flow sheet and incorporate it into clinical documentation, and all the clinician needs to do is look at it and either agree with the computerized interpretation or update the record with their own interpretation,” says Kevin Jones, assistant director of information technology.  

OSU has used an EHR from Epic Systems, Verona, Wis., since late 2011, and last year it implemented medical device integration software from iSirona, Panama City, Fla.  Monitoring equipment and ventilators were the first devices to feed information to the EHR, and anesthesia devices are up next.

For HIMSS, Jones and Lynn Kuehn, director of clinical applications, will present research showing how often and how soon after collection the device data was looked at and validated, how often it was accurate, and the labor savings that resulted. They studied the data flow for all ICU patients during a single week. They found that 93 percent of the vital signs saved in the EHR were collected directly from the devices, showing that clinicians had found the information to be reliable, and 95 percent of vital signs were captured at least once per hour. Clinicians validated 81 percent of the device data within an hour of its collection, and most of the rest within two hours.

ICU nurses told the research team that they save significant amounts of time by validating the device data rather than having to manually enter it. “They tell us it’s a godsend,” Jones says.

Medical device integration is allowing the medical center to pilot a “modified early warning system,” or MEWS, which flags ICU patients in danger of crashing. It works by tracking small increases in their pulse rate (as little as one beat per day) and correlating them with other variables that in combination have been shown to presage crises. “Continual tracking lets doctors highlight those patients,” Jones says. “We are really using the data to see a bigger picture.”

Education session #13, “Stage 7 Hospital Leverages Medical Device Integration for Safer Care,” is scheduled for 9:45 a.m. on March 4.


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