AI-driven healthcare solutions can enable radiology departments to become stronger and more productive than ever before, with more visibility into their operational issues, from equipment maintenance to scheduling to post-imaging follow-up. It all starts with data, which delivers actual information and insights into what is happening. Then, AI and predictive analytics offer further foresight, enabling staff to better respond to what is likely to happen.
Still, these capabilities do not stand to replace the responsibilities of clinical or technology professionals. What they do, however, is provide these individuals with greater information, layered alongside their years of experience, enabling them to work more efficiently, improving operations and ultimately enhancing the patient experience.
From an equipment maintenance standpoint, AI makes zero-unplanned-downtime a possibility. By collecting data from all imaging machines, service and bioengineering professionals can better predict if a system is going to have unplanned downtime or may otherwise need preventive maintenance. For example, technology managers may find that every three months a machine consistently displays the same error and slows clinical workflow, although a regular software patch update can prevent it. Having the right data can enable teams to predict such an occurrence and issue patches proactively, to avoid downtime, maintain workflow, and provide a better experience for the staff and their patients.
Most importantly, radiology professionals must have a clear idea about how the data might be translated into practice—what it could look like and how it will impact the way they work. AI is not meant to replace radiologists and staff—but to help them perform higher-level tasks that demand human ingenuity, creativity and compassion. By helping staff to understand the technology, data and goals, radiology departments will be more likely to embrace AI-driven solutions. It’s critical that everyone understand how these solutions will benefit the entire practice and patient care in the long run.
We are just beginning to scratch the surface with artificial intelligence in radiology operations. What’s happening today will transform healthcare tomorrow – and it all starts with connecting data, technology and people in new ways.
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