ERISA Recovery
“The lift on our end was minimal and the benefit to cash was immediate.”
Matthew Stojakovich, Executive Director Revenue Cycle Shared Services, University of Miami Health System
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When AI Moves Too Fast: The Importance of Accuracy in Denials Management

When AI Moves Too Fast: The Importance of Accuracy in Denials Management

AI Is Moving Fast. Healthcare Cannot Afford to Move Carelessly

There is a lot in the news right now about the potential dangers of artificial intelligence and whether AI development is moving too quickly. Some of the conversation has even centered on whether the industry needs to slow down. But slowing the pace does not mean abandoning the technology. AI has tremendous potential to transform healthcare and revenue cycle management. The key is making sure that as AI becomes more powerful, it is closely monitored to ensure the results are accurate, reliable and actually useful. In denial management, where decisions can directly affect a hospital's commercial revenue, moving quickly without the right safeguards can create problems that ultimately fall back on the hospital's staff.

More Claims Identified Does Not Always Mean More Revenue Recovered

AI can be extremely effective at recognizing patterns in large datasets, but identifying a claim is only the beginning of the recovery process. A denied claim can involve payer-specific rules, documentation, filing requirements, contract language and circumstances that may not be obvious from the data alone. An algorithm may flag an account as recoverable when it is not, overlook important context or prioritize an account that ultimately has little recovery potential. The problem is not necessarily that the technology is incapable. It is that an AI-generated recommendation still requires validation before it becomes an operational decision.

The Hidden Cost of AI Inaccuracies

For hospital revenue cycle teams, inaccurate AI output can create a second layer of work. Staff may have to review accounts that should never have been prioritized, investigate why a claim was flagged, correct inaccurate recommendations and determine whether an account is actually worth pursuing. Instead of reducing administrative complexity, poorly monitored automation can simply move that complexity downstream. That is particularly challenging for hospitals already managing staffing pressures and increasingly sophisticated payer requirements. The technology may be doing more work, but if the results are not accurate, hospital teams can ultimately be left doing more work themselves.

The Right Role for AI in Denial Recovery

The answer is not to slow down innovation or abandon AI. It is to use it appropriately. AI can help revenue cycle teams process enormous amounts of information, identify patterns and surface claims that deserve a closer look. But technology should support the decision-making process rather than eliminate the need for judgment. That requires experienced professionals and, maybe more importantly, experts who understand the healthcare industry and know how to manage, monitor and validate what the technology is producing. The strongest approach is one where AI helps find the opportunity and healthcare experts determine whether that opportunity is real, actionable and worth pursuing.

Key Takeaways for RCM Leaders

  • AI can dramatically improve the speed of identifying and prioritizing denied claims, but speed does not guarantee accuracy.

  • AI-generated inaccuracies can create additional work for already stretched hospital revenue cycle teams.

  • Denial management requires healthcare expertise, payer knowledge and human judgment that cannot always be captured by an algorithm.

  • AI should not be abandoned. It should be carefully monitored and supported by experts who understand the healthcare revenue cycle.

  • The most effective approach combines advanced technology with careful human oversight, validation and accountability.

Technology With Accountability

At ERISA Recovery, our company is built on advanced technology and experts who know how to identify and overturn denied claims for hospitals. Our technology helps identify claims that warrant attention, but we do not treat an algorithm's output as the final answer. Our experts carefully monitor and evaluate the results to help ensure hospitals are not left with another technology layer to manage or a new backlog of inaccurate opportunities to correct. The goal is simple: combine advanced technology with healthcare expertise to find more of the right claims, pursue them efficiently and accurately, and ultimately recover commercial revenue that hospitals may otherwise leave behind.