Across the healthcare industry, advances in AI technology remain a topic of conversation. Much of the focus surrounds its clinical applications, such as how it could help physicians predict the likelihood of future diseases among patients. However, AI’s potential in other areas, such as for streamlining the revenue cycle, have been viewed with a greater measure of mistrust.
Part of this reluctance on the part of healthcare providers is the byproduct of information overload. AI is either humanity’s next great technological innovation or the end of civilization, depending on whose forecast you’re reading. The reality is not nearly so dramatic.
While the hype surrounding AI may be new, the use of the technology is not. AI and machine learning may be buzzy, overused terms, but they have been refining clinical outcomes and revenue cycle management for years. If you haven’t turned to AI to transform your billing processes, the barriers to entry are far lower than you may expect.
The Value of Incorporating AI into RCM Dashboards
Medical labs and healthcare providers are inundated with data from multiple sources, and ensuring data quality is an often complex undertaking. As a result, your team’s ability to track down issues such as underpayments and claim denials are very difficult with a conventional billing system.
For labs and healthcare providers struggling to manage limited resources and a tight bottom line, AI can seem like an expensive solution. But with the right approach, you can secure your lost revenue and minimize claim denials in a way that’s transformative and cost-effective.
With the help of AI, your organization can optimize its RCM processes. Decision trees and regression analysis can predict underpayments, forecast revenue, and determine clean claim status. According to a study by Ingenious Med, an organization that specializes in optimizing hospital performance, incorporating automation to deliver the insights from AI could increase lab revenue by more than 25%.
AI Transforms Trend Analysis into Actionable Insights
One of the core difficulties that are inherent in these conventional billing systems is they function as a backward-looking resource. Your team can see what happened, but they often aren’t notified with enough time to resolve the problem.
Fundamentally, you need to ensure your dashboard notifies your team about changes in revenue trends. If a payer suddenly stops covering a service, your team needs to identify the issue and resolve what went wrong. But it’s not feasible for one person or even a team to identify changes in average payment rates and denial causes in near real-time. However, with the help of AI, your system constantly reviews your revenue data and compares what comes in against established baseline patterns and thresholds.
The right algorithms can compare your expected revenue against the new information your business receives each day. AI delivers rapid insights that enable your team to intervene when claim issues arise and prevent disruptions before payment is due.
Starting Small Is Crucial to AI Adoption in Healthcare
Among the greatest anxieties associated with AI is the misconception that you need to reinvent the way your organization approaches billing. But you don’t need to implement a comprehensive machine learning model into your RCM to see real benefits from the technology. You only need to focus on a single area that’s important for your business.
If you try to develop algorithms to suit every aspect of your revenue cycle, you introduce too many variables and combinations of data. You’ll struggle to get any new system off the ground. Instead, focus on the high-priority services that are the bread and butter of your business.
If you target your efforts toward examining a single payer or procedure responsible for 80% of your reimbursements, you deliver impactful wins for your business. However, if you dedicate your energies toward incorporating a universal data set, it’s going to introduce more variables and derail progress for your organization.
Governance Is Key When Incorporating AI into Revenue Cycle Analytics
The inputs and outputs of your organization’s data are too complex to simply hand off to an outside vendor, or for your IT department to incorporate advanced analytics. You have to apply guidelines to ensureany team understands your business rules and how your data functions before turning to AI-powered tools.
Through AI, you can automate your coding processes for the services you deliver and scan claims to identify potential errors. Plus, you can reduce denials by identifying missing claim information before any claims are submitted for payment. But you first have to establish the right rules governing the expectations for your data.
Even with the right data governance, no algorithm is a set-it-and-forget-it application. Flu season, the end of the school year, or workflow variability tied to the COVID-19 pandemic are all potential pattern disruptors that impact your ability to predict your revenue cycle.
As you open your revenue data for analysis, you need to consistently review the outside factors impacting your business. When your business changes, your algorithms need to change as well to ensure you’re generating accurate results from AI-generated conclusions.
The Right Partner Streamlines Your AI Journey
One of the fears surrounding AI is the idea the technology will replace the people who monitor your revenue data. More accurately, AI will ensure that your team’s time is put to better use. Instead of chasing down errors in a mountain of spreadsheets, your team uses AI to identify issues faster. Then, they can investigate the causes and have an immediate positive impact.
But AI requires expert guidance. You can’t send just any vendor all your data and expect them to interpret what you should be doing differently. And you also don’t need to start hiring a team of data scientists as your models grow more complex. However, with the help of the right partner, you can maximize the benefits to your bottom line.
Ultimately, AI enables you to unlock lost revenue in a way that’s cost-effective and won’t overly tax your existing team. But you have to work with the right technical experts who understand the unique challenges of the healthcare industry and your business. If this sounds like a service that would help your organization,we should get started