AI in Healthcare Revenue Cycle: The Big Opportunity in Medical Billing Accounts Receivable

A recent HFMA study shows that hospital CFOs see revenue cycle – especially medical billing accounts receivable and denials management – as the biggest area of opportunity for AI [1]. This raises a key question: what do revenue cycle leaders need to do to prepare? Considering the complexity of AI technology, choosing a good partner with “pre-AI” revenue cycle expertise is the best approach to moving forward. 

“Six in 10 health system CFOs believe revenue cycle represents the best opportunity for AI.” This quote is from another HFMA study and it highlights a defining time for the healthcare revenue cycle [2].

Hospitals and health systems are stepping up and leveraging Artificial Intelligence to boost revenue cycle efficiency, improve results in medical billing accounts receivable, and overall lower health system costs. The possibilities for reducing friction in the revenue cycle are incredibly exciting – if department leaders can address the hurdles that hold so many healthcare organizations back. 

One of the most glaring hurdles is accessing resources for implementing AI tools. According to the survey, only 16% of organizations are adequately resourced, while a full 83% are somewhat to extremely under-resourced. The simple solution would be investing more in AI, but with uncertainty straining budgets and an AI skills shortage putting even well-resourced organizations at a disadvantage, most revenue cycle leadership teams will need to take a different approach – particularly in areas like hospital accounts receivable follow-up and medical billing denials management, where staff shortages can directly impact collections and compliance.

Based on our experience of AI implementations at 3Gen Consulting, we recommend a three-fold approach. 

• Prioritize your AI strategy: You need a robust plan for implementing AI – one that addresses concerns around security, governance, staffing, leveraging third-party vendors, and sustainability. 
• Identify use cases: Look for high-yield opportunities in the revenue cycle like medical billing denials management, medical coding, risk adjustment services, claims processing, and hospital accounts receivable. 
• Map out your most viable resources: Depending on the maturity of your AI program, you should consider leveraging internal teams, working with other healthcare organizations, and identifying potential vendor partnerships that fit your goals. 

When reviewing a vendor, healthcare leaders should consider the advantages of vendors who have experience in the healthcare revenue cycle “pre-AI”. 

There are a lot of great solutions out there, but few actually take the deep nuance and nature of the healthcare revenue cycle into consideration. Regardless of your AI program maturity level, expertise and experience is invaluable. AI is powerful for improving efficiency in medical billing, accounts receivable, and denial prevention – but it’s not a replacement for human-led expertise. Now is an excellent time to take advantage of AI technologies, but take appropriate time to find vendor partners who understand the nuances of the healthcare revenue cycle and bring more than just software to the table.