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Aidoc Staff

Closing the Gap: AI's Role in Equitable Healthcare Access for Coronary Artery Calcification

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Coronary artery calcification (CAC) is pervasive. Over 90% of men and 67% of women over 70 have been found to have at least some degree of CAC. The condition, originally thought to be a relatively harmless and natural process, is now regarded as a precursor to other severe heart diseases, increasing the likelihood of significant future cardiac events. Detecting and managing CAC is crucial for preventing events such as heart attacks and strokes. This understanding has led to more follow-up procedures and guidelines for patients with CAC and enabling the use of preventative therapies.   

However, access to specialized care for CAC detection and follow-up management is not always equitable, with underserved populations facing barriers to timely diagnosis and treatment.
 
In recognition of American Heart Month, we are exploring the role of artificial intelligence (AI) in aiding care teams by flagging suspected CAC cases while also addressing disparities of treatment in underserved communities.

The Role for Healthcare AI in Underserved Communities

There has been remarkable promise shown in AI and its ability to assist care teams with identifying suspected CAC and risk assessment. By analyzing medical images and quantifying the severity of CAC, time-consuming tasks are then automated, thus enabling care teams to prioritize patients in need. Moreover, AI-powered decision support systems can assist health systems in extending quality care to patients no matter where they are. 

In discussing the effectiveness of AI reaching beyond hub hospitals, Dr. Eric Eskoglu, former EVP, Chief Medical and Scientific Officer, Novant Health stated that “it [AI] also helped us provide patient equity, because we’re able to extend this to our rural communities[…]When we use AI in our radiology protocols, patients in an uptown Charlotte location get the same treatment as those in rural North Carolina.” 

In other words, AI enables patients in rural and otherwise underserved hospitals to be granted the same expedited care opportunities as more profitable hospitals with higher patient volumes. 

AI can help improve patient capture in these localities that have experienced inequity in healthcare, thereby bridging the gap between the two areas: Urban vs. Rural, Underserved vs. Affluent. In this regard, AI is helping to elevate the baseline for care for patients who are in need of follow-up who may otherwise fall through the cracks.

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