Key Barriers Slowing Down AI Adoption in RCM

AI is already solving some of the most pressing cost challenges in RCM, resulting in increased revenue capture.

Fremont CA: Although artificial intelligence (AI) is not new to the healthcare industry, it has lagged behind other sectors in terms of its adoption and use. A growing number of healthcare executives are now using AI. According to a recent survey, nearly all hospitals anticipate using AI for revenue cycle management within three years (RCM). However, many people have yet to use AI in RCM because they perceive impediments to it. The technology's application is limited and doesn't usually span the revenue cycle from beginning to end for those who have.

While healthcare experts have a variety of opposing opinions on AI and the hurdles to RCM, three areas could stymie progress:

Budget and cost concerns

AI is already solving some of the most pressing cost challenges in RCM, resulting in increased revenue capture. For example, AI provided a comprehensive picture of how processes operate regularly, allowing them to focus on areas where they would be most effective in eliminating inefficiencies. As a result, administrative waste may get drastically minimized, and RCM activities can proceed more quickly by automating data-driven procedures.