Aidoc Staff

How is AI Used in Healthcare? 3 Real-World Examples

In the wake of ChatGPT, Artificial Intelligence (AI) has exploded in popularity and has a strong hold on mainstream conversations. One area of impact that is less in the limelight, however, is the utilization of AI in healthcare. While those less keen on the inner workings of AI might initially think of robotic physicians when hearing about healthcare AI, the reality is far more in line with a “man and machine” dichotomy. AI applications in healthcare have effectuated a wide range of benefits both for health systems and, more importantly, patients. In this article, we’re going to outline three real-world examples explaining how AI is used in healthcare, making drastic improvements to hospital workflows for a variety of pathologies.

AI in Radiology

The role of AI in healthcare is as expansive as it is effective, leading to a sizable impact on varying service lines. As the cockpit of innovation, one area that was particularly ripe for the benefits of AI from the outset was the reading room. 

As it stands, AI provides exceptional support in mitigating radiology workloads that are only increasing as the  field experiences a palpable shortage of physicians. One study has found that AI-based reprioritization of the reading worklist with AI “has a beneficial effect on the turnaround time for interpretation of head CT with intracranial hemorrhage.” The results included a reduction in queue-adjusted wait time between “negative (15.45 minutes) and positive (12.02 minutes), saving time for patients in immediate need of medical intervention. 

A separate study for incidental pulmonary embolism patients found that AI-based triaging led to a “median iPE wait time reduction of 90% (863 minutes).”

AI in Other Hospital Service Lines

As the enterprise-wide platform approach takes hold over AI in healthcare, additional service lines outside of radiology have begun to reap the benefits of the novel technology in several areas, some expected and some unexpected.

AI in Neurology

The application of AI in neurology had led to some remarkable improvements in not only triaging in the radiology department, but offers various benefits to service line specialists, including:

  • Image analysis
  • Patient capture
  • Patient follow-up
  • AI-based alerts, mobile image view and care team chat tools

In fact, one study conducted at Cedars-Sinai Medical Center found a decreased hospital length of stay for ICH patients after adopting an AI-augmented radiological worklist triaging system, highlighting the impact that AI is having not only in health systems but on patient outcomes. 

The graphic below shows an example of a stroke patient’s time to treatment, the first scenario in a health system without AI, and the second in a health system with AI:

Infographic highlights benefits of AI in healthcare, showing patient’s journey in hospital with and without AI.

AI for Cardiovascular Treatment

Amongst the many types of AI used in healthcare is cardiovascular AI, which, thanks to a variety of AI-driven tools, have found similar benefits to the neuro field, including:

  • Patient management solutions
  • System-level analytics platform for clinical, financial and operational impacts
  • Deep EHR integrations to provide access to real-time information

The aforementioned Cedars-Sinai study also found a connection between AI adoption and length of stay for pulmonary embolism patients, resulting in a 2.07 day reduction (26.3%). 

Another case study from Yale New Haven Hospital showed that AI’s support of their pulmonary embolism response team (PERT) increasing advanced therapy at a spoke facility by 40% thanks to:

  • Faster and better patient treatment and evaluations
  • Notification of Yale’s comprehensive PERT center at the time of diagnosis, instead of relying on referral centers at local hospitals
  • Secure text communications about patients, including notifications about CT scans on cell phones
  • Streamlining of communications between members of the PERT and increased collaboration between hospitals

The Future for AI in Healthcare

Despite its strong impact throughout radiology, neuro departments and cardiovascular workflows, AI is still gaining momentum worldwide. As hospitals continue to see the impact on performance metrics like turnaround time, length of stay and increased advanced therapy, AI’s application in healthcare will continue to grow, and we’ll see its positive impact in areas we may not have expected. 

Want to learn more about the impact of AI on healthcare? Check out our eBook AI’s Promise for Healthcare.

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Aidoc Staff