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The use of automatic identification and data capture (AIDC) technology in the healthcare industry has grown rapidly in recent years. As technology evolves, the industry has a multitude of opportunities to grow and change through adopting new methodologies and devices. Manufacturers are continually improving the features of scanners, mobile computers, printers and other devices to make them better suited for applications in healthcare.
The implementation of barcode and RFID technology has reduced errors and increased efficiency and quality of care in the industry over the years. Through these methods of scanning, prescriptions can be assigned, administered, and tracked more accurately, as can patient records and identification. By increasing the accuracy and efficacy of patient and prescription tracking, the industry can cut down on errors in treatment, data breaches, and HIPAA Privacy Rule violations. The net effects include improved patient safety, better record keeping, fewer errors and better coordination of service to the patient.
In addition, to accommodate the unique needs of the healthcare industry, general use equipment is being replaced with healthcare-specific equipment that has been designed with new features. Many scanners are now available with hypoallergenic handles, wearable devices are available to maximize hands-free access, and asset tracking has been adapted to ensure healthcare facilities don’t run out of crucial supplies. Hospitals and clinics have embraced these technologies for patient care, inventory management and equipment tracking.
There are opportunities for VAR’s and ISV’s who invest in learning how to develop and implement solutions for the growing healthcare market. These technologies are changing rapidly to accommodate the industry’s needs, and there can be much to gain for a VAR or ISV that is able to master selling these solutions. As regulations change and demands on the healthcare system evolve, it will be more important than ever for companies to maintain compliance and efficacy, and cut down on human error by automating many processes.
Co-contributor: Matt Schwietering