Aidoc on how AI can reduce healthcare disparity
Elad Walach, the CEO and co-founder of Aidoc, discusses how AI can reduce healthcare disparity and support the healthcare labour shortage.
Hi Elad! How did you get into healthcare?
“My journey began in the IDF’s prestigious Talpiot program conducting AI research, which taught me valuable lessons about the use of AI in identifying anomalies. That’s where I came to understand its applications for healthcare, founding Aidoc in 2016 with two other Talpiot graduates.”
What has the COVID-19 pandemic taught you about healthcare?
“I’ve come to understand the importance of optimising both efficiency within and between departments and connectivity - ensuring that hospital departments are not siloed and always communicating on patient care.”
How can AI reduce healthcare disparity?
“One way is through stronger health system coordination, between patients receiving care at larger facilities and smaller ones. Smaller medical facilities often transfer patients to the larger medical centres for special procedures, which involve manual processes that lead to delayed care and potentially worse patient outcomes. AI can improve upon this gap by digitally organising and mobilising a health system’s response teams and facilitating instant, clear communication on patient treatment. This can cut down transfer delays and the disparity between treatment times in smaller and larger centres.”
How can AI bring different hospital departments together via informatics?
“Radiologists - healthcare’s informatics experts - are currently standing at a very important turning point in healthcare, where they can lead the enterprise-wide AI strategy. Imaging is very often the first step in care, giving them the power to be the champions of this technology in their institutions. As more health systems compile more data and integrate multidisciplinary response teams, they’ll need the right tool to facilitate department cohesiveness for care coordination. AI is that tool and radiologists have the know-how to lead its implementation across service lines.”
Can AI make a difference in the healthcare labour shortage?
“Definitely. For example, in radiology, there’s currently a shortage of radiologists in many countries, which means each one, on average, has to manage reviewing more cases. AI can compensate for the higher workload by flagging the positive cases in a worklist, ensuring they are reviewed first and care for those patients is expedited.”
