Leveraging the insights that radiologists facilitate, however, requires a plan that considers the user experience of physicians, meaning it must fit in the workflows of patient care teams and be patient-centric. That plan starts in the radiology departments.
Today, radiologists want technology solutions with simple, intuitive interfaces that easily integrate current IT investments into their preferred workflows. The best of these solutions should provide an elegant physician experience -- a consistent, singular interface that doesn't require clinicians to log into multiple systems, swivel their chair to look at another screen, or otherwise waste time.
It goes without saying that these solutions must support better patient outcomes. But they could also offer new tools, like harnessing the cloud to gain access and share prior imaging and even broader patient insights to enhance clinical confidence and overall productivity.
New AI tools can do all of that and more. They make the most innovative technologies simpler while reducing the inefficient workflow practices that contribute to costs and physician burnout. Most importantly, they enhance both the diagnostic and treatment process, with the patient as the ultimate benefactor.
Urgent solutions needed
Technological advances in radiology and healthcare are more necessary than ever because the COVID-19 pandemic has deeply impacted hospital budgets and caused shortages in staff and equipment. These shortages won't necessarily disappear when the pandemic abates. Around 40% of U.S. hospitals could have negative margins by the end of 2021, according to an American Hospital Association study.
At the same time, consolidation is occurring within most health systems -- from clinical practices to digital infrastructure. These changes impact how clinicians and staff deliver care in and out of hospitals.
Unfortunately, this consolidation also brings another set of problems -- various tools and technologies used by different groups that aren't integrated or compatible with each other. In response, healthcare management teams are cobbling together inefficient workarounds and temporary fixes without focusing on long-term solutions.
AI can now address these issues head-on to improve workflows and patient care. For example, AI can facilitate data collection, diagnostics, and even budgeting. The key is making things simpler for clinicians. And the place to start is radiology.
Radiology departments are under pressure to reduce unnecessary diagnostic imaging and related costs while increasing efficiencies and improving diagnostic consistency. These circumstances, coupled with the incredible advantages of AI in the field, make radiology an exciting target for innovation.
In a widely shared cartoon, a manager points to an AI mainframe while facing a frowning colleague and says, "His decisions aren't any better than yours, but they're WAY faster..."
Under the supervision of radiologists, AI is emerging as the clinical workhorse in diagnostic imaging. It has quickly become a vital part of the physician's toolbox for identifying lung nodules on CT scans, abnormalities on mammograms, and as a second opinion for stroke patients.
AI-informed diagnoses support accuracy that's similar to a trained professional, yet it can do so far faster. Of course, that doesn't mean that AI insights will be replacing clinicians anytime soon. But it does mean that AI is already here to create time-saving synergies.
Because radiologists have already embraced AI and deep-learning systems, the key to unlocking the full power of this technology and extending the value of radiology throughout the hospital enterprise is elegantly designed intuitive user interfaces. Today, that means platforms that enable multiple doctors across multiple systems to view and collaborate on images -- simultaneously and seamlessly -- as part of the entire patient record.
These innovations are already happening to great success. Physicians who used AI tools such as voice-driven engagement or automated clinical guidance enjoyed more direct time for patient care than those who did not, according to recent research. The same study found that increased AI usage reduced non-value-added activities; freed up physicians' time; and increased productivity, precision, and efficacy.
Care before systems
Artificial intelligence has evolved to allow clinicians to use real-world data, patient information, and test results more simply and effectively than at any time in the past. Now they can access those data, including diagnostic imaging, from anywhere and on any device -- including a tablet -- with a patient's broader care team.
Of course, doctors won't make critical diagnoses on mobile devices. But they can more easily access data to help inform their next steps or share their insights with colleagues.
That ease of use is a win for patients, too, if doctors can complete their work more quickly and efficiently. After all, extra time means clinicians can focus less on systems and more on patients.
Renee Stacey is Product Marketing Director at TeraRecon, a leader in advanced visualization and enterprise-level artificial intelligence solutions.
The comments and observations expressed are those of the author and do not necessarily reflect the opinions of AuntMinnie.com.
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