The next frontier in revenue cycle management (RCM) is already upon us—denials management powered by artificial intelligence (AI) and machine learning (ML). Whether hospitals and healthcare providers embrace or ignore these burgeoning technologies will have significant repercussions in the decades ahead for their fickle revenue margins.
AI-enabled approaches are instrumental in optimizing hospital and provider margins through various strategies. AI-powered solutions offer healthcare providers the ability to predict and address denials management challenges proactively. These solutions analyze claims data to forecast potential issues, enabling timely interventions to prevent denials.
Moreover, AI plays a role in identifying inaccuracies in claims and extracting relevant information from payer guidelines and contracts to help drive payer adherence. By leveraging AI in these ways, healthcare organizations can improve financial outcomes and operational efficiency. For a bird’s-eye view of AI-powered RCM and its potential to change the denials-management landscape, here is an insightful article by Aspirion’s Chief Executive Officer, Amy Amick.
What contributes to the success of AI in RCM?
There are four key pillars healthcare organizations must have in place when implementing a successful AI approach:
- Use Cases
- Data
- Platform
- Talent
Use Cases Serve as the Foundation for Effective AI Strategy
“It really starts with use cases,” says Aspirion Chief AI Officer Spencer Allee. “As you think about what problems you are actually trying to solve, it’s remarkable how often somebody builds tech without a clear understanding of the problem that they’re solving. And then often, that tech ends up not really getting the traction that’s needed.”
Examples of use cases include processes such as:
- Automated Coding and Billing
- Claims Denial Prediction
- Appeal-Letter Generation
- Forecasting and Optimization
Achieve RCM Excellence by Harnessing Data with AI
After use cases, the second pillar of a successful AI approach is data. Robust data is crucial for creating reliable AI solutions that provide accurate predictions, mitigate biases, and improve over time.
Examples of data types include:
- Claim-Level Data
- Clinical Data
- Payer Policies and Guidelines
- Metadata
Platforms Streamline Development and Deployment Processes
The third pillar in building a winning AI strategy is having the right platform. An optimal platform provides the tools, infrastructure, and capabilities to develop, deploy, and manage AI solutions effectively.
Here are some must-haves of effective platforms:
- Unified Data Access and Management
- Intelligent Workflow Automation
- Predictive Analytics and Forecasting
- Customized Insights and Reporting
The Power of Skilled Talent in Driving AI Strategy Success
Finally, we come to talent, the fourth pillar of successful AI implementation. Skilled talent facilitates the effective development, application, and management of AI initiatives to ensure success.
Skilled talent comes from an array of areas, including:
- Data Scientists and Engineers
- Product Managers
- RCM Operations Subject Matter Experts
- Learning and Development Specialists
We’ll be diving more into the intricacies of all four pillars of AI-powered denials management, designed to improve revenue integrity, in our upcoming Level Up Revenue Cycle webinar later this month. Let us know here if you’d like to receive an invitation.
Yet another tip you should know as your organization embarks on its RCM AI journey is the imperative nature of building a lightweight AI strategy. Don’t try to “boil the ocean” or “bite off more than you can chew.” Start by asking yourself these questions:
- What are the most important business problems you need to address?
- How will AI help?
- How will you source or build the solution?
- How will you measure success and over what timeframe?
“AI is already in everything that we do on a day-to-day basis,” says Allee. “This is not just a fad or a trend. This is a step-change function in how we do business in the same way that the internet was. AI unlocks a lot of new capabilities that are really going to change the way we work over the next decade plus.”
It’s not a question of if or even when, Allee said, but rather a question of how and how fast and what makes sense for you and your business.
Ready to begin your journey toward optimal AI-powered denials management? Contact us today.
