Ekahau will implement the largest medical real-time positioning system in the United States
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The Ohio State University Medical Center (OSUMC) will begin installation of the largest medical real-time positioning system in the United States to date, using existing Cisco Wi-Fi infrastructure and Ekahau Wi-Fi tags to locate assets and personnel. The system will cover 5 million square feet and include more than 40 buildings. The installation of the system will take approximately three weeks, according to Ekahau Business Development Director Tuomo Rutanen.
Once the installation is completed, Rutanen said, the system will initially use only 1,000 asset tags, but it is expected to apply 15,000 Wi-Fi RFID tags in the next two years to identify and track assets, patients and employees. The hospital will use Ekahau Positioning Engine positioning software on its server to locate the location of each tag, and conduct business analysis based on the location information.
The hospital first started looking for a wireless asset location system about four years ago, said Chad Neal, OSUMC’s technical director. Initially, the center wanted to purchase an RFID system and install readers throughout the center. However, it would be time-consuming and costly to install a positioning system in a large area like OSUMC to capture the ID code and location of the tag. . It would be impractical to use this system only in some areas of the center, Neal said, because the center cannot track the location of labelers or objects when they leave the coverage area.
In the end, OSUMC judged that the best solution was to use the existing 802.11 Wi-Fi network in the hospital. However, the center also learned that the technology was not yet mature at that time. Therefore, the medical center temporarily shelved the RFID application plan, waiting for the cost of the technology to become lower and the efficiency to increase. At the same time, the hospital also upgraded its Wi-Fi infrastructure, installing nearly 3000 Cisco Wi-Fi access points and 30 network controllers.
In September 2009, the hospital compared the RTLS solutions of the two companies and conducted a concept test, one of which was Ekahau. The hospital applied 100 tags on two four-story buildings to collect the parameter values of tag reading accuracy-for example, when the tag icon was displayed on the computer screen, how long did it take for workers to locate the tagged assets; It shows how far the position is from the actual position of the label; whether there will be layer skipping, such as the actual position is one layer higher or one layer lower than the marked position in the figure.
According to Neal, tests have shown that Ekahau’s solution is more accurate-the location of the tag is within 3 meters (the other is 5 meters), and the sense of service and professionalism are also stronger.
In the next few weeks, once the system software is installed and tested, Neal said that the hospital plans to initially label only infusion mercury and other high-priced medical equipment. Each piece of equipment is equipped with a T301A Ekahau label. The Cisco Wi-Fi node reads the unique ID code of the tag and sends the data to the back-end server. The Ekahau Positioning Engine software on the server calculates the position of the object based on the signal strength. The tag can also receive information, such as receiving instructions to send a sound signal, as an alarm (for example, if an item should not be used). The center can use Ekahau XML API software to perform business analysis based on the location of specific items, such as equipment leaving the area, or mixing clean equipment and dirty equipment, entering the laundry area, and the system sends email or text message alerts.
When the medical center completed the labeling of high-priced equipment, Neal said that the next step would be to label the beds at the OSUMC Arthur G. James Cancer Hospital, and then issue RFID wristbands to patients in the Central Neuropsychiatric Hospital. In the next few years, OSUMC hopes to use sensor tags to track the temperature of refrigerated equipment and electric blankets in operating rooms. If the temperature exceeds or falls below a preset threshold, the software will send an alert to authorized users. The hospital also hopes to adopt RFID employee badges with text transmission capabilities.
How to obtain a hospital floor plan is the biggest challenge in software design, Rutanen said. Ekahau had to input hundreds of computer-drawn floor plans. “This workload is huge, and we hope to complete it within three weeks.”
In the long term, Neal stated that he hopes to use software to build an alarm system that will enable the hospital to better plan the location of employees and equipment. However, it will take several years to achieve this goal.
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