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.