Coronary artery calcification (CAC) is a prevalent condition, affecting over 90% of men and 67% of women over the age of 70. Initially thought to be a natural process, CAC is now recognized as a precursor to severe heart diseases, including potential future cardiac events like heart attacks and strokes. Early detection and management of CAC become critical in preventing such diseases. More follow-up procedures and preventative therapies have consequently been implemented for patients with CAC to ensure their well-being. Despite these advancements, access to specialized care for CAC isn’t always equitable, with underserved communities facing hurdles in receiving timely diagnosis and treatment.
Artificial intelligence (AI) offers promise in addressing these disparities. Healthcare AI has demonstrated its potential in assisting care teams with CAC detection and risk assessment, improving equity in healthcare services. AI can analyze medical images to quantify the severity of CAC, thus automating time-consuming tasks and allowing care teams to prioritize patients in need. AI-powered decision support systems can also extend quality care to patients, irrespective of their location.
AI has shown effectiveness even beyond hub hospitals. According to Dr. Eric Eskoglu, former EVP, Chief Medical and Scientific Officer at Novant Health, AI has helped provide patient equity by extending care to rural communities. In essence, the use of AI in radiology protocols ensures patients in rural areas receive the same treatment as those in urban locations.
AI’s ability to extend expedited care benefits to patients in rural and underserved hospitals can improve patient access to healthcare in such localities that have faced healthcare disparities, reducing gaps between urban and rural or underserved and affluent areas. In doing this, AI elevates the baseline care for patients who might otherwise be neglected, helping them receive the follow-up they need.
In conclusion, AI plays a crucial role in ensuring equitable healthcare access, particularly with respect to Coronary Artery Calcification. It holds tremendous promise in identifying potential CAC cases, automating complex tasks, and offering a more equal distribution of healthcare services irrespective of a patient’s location. By doing so, it can bridge the healthcare disparity gap between urban and rural communities or between underserved and affluent populations, improving the overall standard of care available to patients.
