AI in RCM: Bridging the Gap Between Enthusiasts and Doubters

As the healthcare industry faces increasing demands and complexities, artificial intelligence (AI) emerges as a transformative force, promising to unlock benefits for both providers and patients. But how is AI used in healthcare with respect to revenue cycle management (RCM)? A recent survey of providers reveals an environment filled with both optimism and caution, varying significantly across different market types, organization sizes, and job titles. Understanding these perspectives can help tailor AI solutions to meet the diverse needs of healthcare providers.

A survey of more than 400 healthcare leaders and professionals, conducted by Inovalon in April 2024, targeted a broad spectrum of respondents, including hospitals, skilled nursing facilities (SNFs), home health and hospice (HHH), and ambulatory practices. It included managerial roles and above, with a significant portion involved in selecting RCM vendors. The data provides a comprehensive look at how different segments perceive the potential of AI in healthcare as it relates to RCM.

Optimism and caution: a delicate balance

Across the board, there’s a notable blend of optimism and caution regarding artificial intelligence in healthcare RCM. While 40% of respondents are cautiously optimistic about AI’s role in RCM, 25% are concerned/skeptical, particularly about accuracy and reliability. Lack of familiarity/understanding of AI is a common reaction, with some respondents concerned that the professional expertise of revenue cycle professionals could possibly be overshadowed by AI automation. Among the anticipated benefits highlighted in the survey are improved efficiency, task automation, and workload reduction. Specific workflows identified include denials management, prior authorization, and eligibility verification.

Hospital executives and managers: AI perspectives from each group

C-suite and directors

Higher-level executives, including C-suite, VPs, and directors at hospitals and health systems, are generally more optimistic about AI in RCM, with 61% being cautiously optimistic, 23% being very optimistic, and just 12% being concerned/skeptical. They emphasize the potential for AI to enhance operational efficiency, reduce redundant work, and empower staff. These leaders are driving the push for AI adoption, seeing it as a strategic advantage.

Managers and supervisors

In contrast, managers and supervisors exhibit more caution, with 33% expressing concern/skepticism and 18% being unsure/unfamiliar. Of the hospital managers and supervisors surveyed, 48% were optimistic in total, but with a significant level of caution and unfamiliarity with AI. They are closer to the operational challenges and express concerns about AI’s accuracy and the potential for errors. Their perspective underscores the need for AI solutions that are reliable and transparent.

Potential workflow improvements

The survey highlights several RCM workflows where AI could make a significant impact:

• Denials management: AI can help flag errors and potential denials before claims submission and speed up claims processing. This capability is crucial for driving staff satisfaction, reducing burnout, and streamlining workflows to allow staff to focus on high priority tasks.
  • Survey says: “If AI could flag potential denials ahead of submission, that would be tremendously helpful.”
• Verification of eligibility: Automating the verification of patient benefits and insurance information can flag potential denials prior to submission and improve front-end processes.
  • Survey says: “Automatically checking eligibility and submitting prior authorization requests would streamline our workflow.”

Concerns and barriers

Despite the optimism, many respondents voiced concerns about AI:

• Accuracy and reliability: The most significant concern is AI’s accuracy in handling complex healthcare claims, with skepticism that AI can match the nuanced understanding of experienced human operators.
  • Survey says:  “I would require in-depth testing of the functionality of any AI program before I’d be willing to entrust our claims to the process.”
• Preference for human interaction: Some respondents prefer human oversight for critical tasks, fearing that AI might overlook specific details that a trained professional would catch.
  • Survey says: “I prefer to have a live person with experience looking at our claims.”

Moving from mystery to mastery

The 2024 survey paints a dynamic but hopeful picture about the RCM benefits of AI in healthcare. While many providers see potential for positive outcomes from AI, concerns about accuracy, reliability, and the need for human oversight remain significant barriers. It’s clear that the need for greater education is significant, with large percentages of healthcare professionals unfamiliar or unsure about AI, including its role in assisting humans rather than taking over all processes. Tailoring AI solutions to address these concerns and demonstrating tangible benefits will be key to increasing adoption.

Rigorous testing to increase user confidence and reduce unintended assumptions is also essential, as is education on how the technology can empower staff to streamline RCM processes and improve workflows. For example, in the battle to reduce claims denials, AI can flag potential denials prior to submission, thereby boosting efficiency, productivity, and accuracy of each claim. Identifying the correct coverage for patients and residents the first time not only reduces the risk of claims denials, but it improves overall satisfaction and accelerates access to care.

Get additional insights in our white paper

For a deeper dive into the detailed results and comprehensive insights from the survey, check out the white paper. Explore the nuanced perspectives across different healthcare settings and understand the strategic recommendations for integrating AI effectively into your operations.

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