Provider organizations need to embrace advanced technologies for revenue cycle management (RCM) to address low cash reserves, rising denials, and high burnout rates. Claims denials are increasing in number, value, and complexity, while resolution times are lengthening and yield per claim is decreasing. Labor shortages exacerbate these challenges, making it difficult to navigate the complex claims process.
Advanced technologies like artificial intelligence (AI) and machine learning (ML) can streamline denial pattern recognition, extract evidence from clinical documentation, and highlight root causes of denials. When integrated effectively into workflows, these tools can maximize yield, accelerate collections, and reduce administrative burden. The key is to apply technology in a way that complements the expertise of seasoned revenue cycle professionals, rather than replacing them.
Implementing AI and automation in RCM can present technical and operational challenges, including insufficient infrastructure, lack of quality data, and shortage of skilled data scientists. To overcome these obstacles, providers can leverage industry-leading RCM innovators like Aspirion, who have proven success in using AI built on large industry data sets. Collaboration with partners skilled in large language models (LLMs) is also recommended for risk mitigation.
Successful AI implementation requires employee buy-in, clear communication about its value, and collaboration between AI Product/IT teams and finance leaders. Interoperability is crucial for routing the right data to models and integrating results into operational workflows.
As the AI landscape evolves rapidly, businesses must maintain adaptability and avoid overcommitting to a single technology. Aspirion, for example, uses a wide array of AI tools and maintains both self-managed and vendor-managed solutions. While hospital margins are beginning to stabilize, optimizing performance in the revenue cycle remains critical for financial health.
Read full Becker’s Hospital Review article.