Feature
Medical robotics
Understanding medical needs and measures of success
By Zachary L. Bercu, MD, John T. Moon, MD, Deepak Iyer, Peter Ju Park, MD, Kamil Arif, MD, Judy Gichoya, MD, Janice M. Newsome, MD, FSIR, Kaesha Thomas
sick to reach the specialized medical center for an embolization (or a global pandemic triggers resource limitations and inability to transfer patients). All this demand is occurring in the setting of burnout among healthcare workers and social events like “quiet quitting.”
In short, how do we provide more IR services to more patients more efficiently and more effectively without adding any resources or increasing risk of burnout or adverse event?
new technology. I
CT scanners were paid for and deployed in an era when the questions were two-fold: “Is it cancer?” and “What type of cancer is it?” In today’s clinical trials, there is an increasing demand for more frequent biopsies and tissue analysis, driven by the need to advance immunotherapies and biomarkers. The addition of CT scanners remains
nterventional radiology is at a critical juncture. In many medical centers, demand is high and ability to deliver is limited—as is space for
cost and space prohibitive for medical centers and radiology departments. Furthermore, labor shortages among technologists, nurses and proceduralists would limit utilization even if additional technology could be deployed.
Endovascular procedures like prostate artery embolization (PAE) are available to patients with access to highly specialized medical centers but remain elusive to those in settings where specialists are not available. At times, critically ill patients who may need experienced proceduralists are too
The potential for robotics The current pace of healthcare mandates the development of a new platform technology that would address these clinical needs. Medical robotics has the potential to reflect that platform.
Previous devices have entered the market but have failed to gain widespread utilization. This can be attributed, in part, to their exorbitant costs, large device footprint, significant learning curves to successful utilization, cultural inertia to adoption and absence of well-defined needs-driven problem
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