The financial case for an AI workforce in providers’ revenue cycle operations
AI workforce solutions have shown significant promise in improving efficiency and effectiveness of revenue cycle management teams, who facilitate reimbursement and payments at healthcare providers in the US. In this white paper, we put forward a novel, quantitative framework that will help leaders assess the financial impacts of these solutions.
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Summary of key messages:
This paper addresses a key question for healthcare leaders: with limited resources to invest in AI workforce solutions, is prioritizing revenue cycle management (RCM) the right choice? That is, why consider RCM as a priority use case for AI?
RCM operations have long been a focus for operational improvement efforts. But in the last 1-2 years, rapid growth and increased investment in AI-driven technology companies and tech-enabled services have created new opportunities to support RCM teams and drive better performance. Leaders may ask: are there new sources of value to be tapped here?
Based on our research, yes. The potential for additional financial impact from an AI workforce is substantial. Previous generations of technology have not fully solved known problems, leaving teams to manage a high volume of manual, repetitive processes. AI-driven technologies are able to augment human efforts in ways that were not possible five years ago. And some complex tasks are now fully automatable and can be handled end-to-end by an “AI workforce”.
Through cost reductions and revenue uplift, healthcare providers and billing companies can achieve significant margin expansion. Using AI workforce resources in place of human time and effort leads to labor cost savings. There are also potential revenue opportunities from redirecting human energies to reduce revenue leakage, aided by an AI workforce to target efforts precisely and manage risk throughout the revenue cycle.
The bottom line is that any investment in AI should be focused where there is a sufficient ROI for your organization. Therefore, understanding the potential financial impact across different levers, relative to your current baseline, is crucial.
In this paper, we lay out the potential cost, revenue, and cash flow implications of AI workforce solutions in RCM operations and help you to size the opportunity as you develop business cases for AI initiatives. Figures provided are estimates that do not reflect the cost associated with vendors, technology, or implementation.
Aggregating all financial drivers at healthcare providers, margin improvement of 85-500 basis points (depending on baseline performance) appears achievable by leveraging the latest advancements in AI workforce and ensuring a high degree of execution. We detail an example scenario with an ~250 basis point opportunity and also provide a companion tool that you can use to tailor assumptions to your circumstances. Please request access through the link to use the tool.
Billing companies stand to benefit by as much or more (weighted more heavily toward cost), depending on their starting point with automation and labor costs.
