Transitioning Radiology into the 21st Century
"Information focused Imaging" is a new challenge for Henry Ford Health System, as well as for other U.S. healthcare providers. Despite enormous amounts of data in our imaging and electronic medical record archives, translating that into effective actionable information has been difficult. Algorithms, machine learning, and AI tools have showed some promise in focused areas, but have had little impact to date impacting overall workflows. It remains challenging to predict who will need an imaging study, what that study should be, when is the best time to perform it, where that test should be performed, and how to route the results once completed. This leads to secondary challenges in cost of care, quality of service, and resource utilization.
One of the most significant challenges in this area is managing and categorizing the flow of large volumes of image data and associated metadata at all stages of the process, from order until finalized report. Tools to improve these processes could include algorithms for image processing, AI-based tools for workflow optimization, NLP software to better understand orders and reports, all within the framework of a broad integrated electronic medical record. Innovative approaches to improving realtime access to this data are expected to improve workflow, resource utilization, cost reduction, and ultimately overall patient care.
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