Both the FDA and the EU Commission have defined requirements for Unique Device Identification (UDI) for medical devices. A new report from Berkeley CA-based consulting firm Brick42 outlines how RFID-based Surgical Instrument Tracking enable the type of ubiquitous tracking described in the EU and FDA regulations, as well as the rapid return on investment that can be achieved using the technology.
As tag costs have fallen and RFID tag performance has improved both on metal and within the context of harsh sterilization processes, more hospitals are implementing the technology for tracking a variety of medical devices. According to the report, this type of “Internet of Things” (IoT) solution should be first implemented in operations where the value of each item and the lifecycle costs are the highest.
“Sterilization and processing of surgical instruments is a perfect example of this kind of high value system where the return on investment could be exponential, even though, as mentioned above, the challenges of such an implementation are technically daunting,” says report author Tom Brooks.
Deployment in the U.S. of Xerafy Surgical Instrument Tracking solution
The data from RFID and IoT solutions will provide a foundation for healthcare organizations to utilize artificial intelligence technology.
Artificial intelligence (AI) will be increasingly adopted for healthcare applications, but those solutions will rely heavily on the data generated by sensor, RFID, and Internet of Things (IoT) systems in order to provide operational and outcome improvements.
A recent report from Deloitte indicates that investment in AI solutions for IoT applications is increasing, and Gartner predicts that by 2022, more than 80 percent of enterprise IoT projects will include an AI component.
The oil and gas industry collects a lot of data, but has a poor record when it comes to analysis. A new report from ARC Advisory Group outlines the challenges.
Global oil and gas producers are under pressure to reduce cost and risk and doing so will require new approaches to data analysis in order to improve knowledge transfer for the workforce and improve operational efficiency.