by
John R. Fischer, Senior Reporter | August 08, 2022
From the August 2022 issue of HealthCare Business News magazine
New hires may not have access at their facilities to proper servicing training. As a result, providers should partner with OEMs that offer training programs, as well as courses in clinical education and product security requirements.
“In-house healthcare technology management teams are typically measured on improving repair quality and reducing the cost of service,” said Stevens. “It is incumbent on OEMs to work closely with in-house service teams to support their quality and cost performance goals.”
Training can be in-person, online, or incorporate both, with each format offering unique advantages. “Online training delivers highly affordable, self-paced learning, testing and tracking; and onsite classroom training at our technology and innovation centers feature state-of-the-art equipment and a small instructor-to-student ratio,” said Thakkar.
Predicting servicing needs in advance
With remote monitoring technologies, OEM service teams can be alerted ahead of time when a device is at risk of breaking down or experiencing a setback. This allows them to address the issue proactively, mitigating damage and downtime, as well as potentially saving the provider time on costly repairs. GE Healthcare, for instance, utilizes its Tube Watch system to predict tube failure in CT scanners, and OnWatch to monitor critical components in CT, interventional, MR and mammography systems.
In some cases, fixes can be made over the phone or from behind a computer. In others, OEM servicers can use predictive AI to determine and inform providers of what the onsite technician will require for the job.
“This way, the technician is not starting from zero,” said McCallum. “He has the parts and the action plan to follow, so we can fix it the first time rather than having to revisit.”
In 2020, Canon Medical partnered with Glassbeam, an AI vendor that develops solutions for data and predictive analytics, to enhance its service capabilities. Utilizing machine learning, the company’s Clinsights flags equipment at risk of breaking down. It also offers feedback on physician performance, physician referral and exam scheduling, and benchmarks practices against its competitors. Canon deployed the system across its install bases for CT, MR and vascular lab systems in the U.S. and credited the technology for helping its customers maintain effective operations during the pandemic.
“These analytics enable predictive maintenance, thereby maximizing customer uptime and customer satisfaction,” Suresh Narayan, director of service life cycle and installed base for Canon Medical, told HCB News at the time. “Service operations are streamlined with the reports that Glassbeam analytics provide, enhancing operational efficiencies.”
