A recent report from Kaufman Hall underscores the urgent need for strategic intervention related to healthcare’s tightening margins and escalating expenses. Significant increases in labor expenses, bad debt, charity care, and days in Accounts Receivable (A/R) since 2021 are called out in the report. These challenges lay a compelling groundwork for leaders to turn to automation, especially in administrative domains like revenue cycle management (RCM).
The resulting chatter around automation in RCM has often manifested in immense promises, but technology leaders are confronting a more nuanced reality of automation technology. Here are three myths surrounding automation in healthcare RCM.
1. Automation Will Replace Humans In RCM
The integration of AI into RCM has sparked both excitement and apprehension. At the heart of this discussion is our fundamental belief: AI is not here to replace humans; its purpose is to enhance our productivity and capabilities. This perspective is critical for understanding the true potential of AI in healthcare RCM.
One key insight is the distinction between tasks that AI can automate and those that require human cognitive capabilities. While AI can handle objective-driven, low-level reasoning tasks, the complexity and nuances of many healthcare tasks necessitate human intervention, particularly in broad reasoning and complex decision-making.
Effective automation in healthcare involves a "happy orchestration" between human and AI tasks, ensuring each task is handled by the best-suited entity. Digital agents excel in repetitive tasks and can improve over time, but tasks requiring high-level cognitive skills and nuanced decision making are best suited for humans. A hybrid approach, where AI and humans collaborate, is crucial for optimal outcomes, as AI alone cannot address the inherent complexities and needs of healthcare RCM.
2. Automation Requires In-house Development
Privy to a distinct lack of automation in most healthcare platforms—particularly EHRs—many healthcare organizations are seeking programmers to develop custom automation routines.
However, the lack of RCM-specific expertise among these programmers often leads to suboptimal solutions. Developers either need to rely on subject matter experts or build less-complete automations. As mentioned earlier, adding high-touch automations into RCM workflows can lead to inefficiency and further burden staff.
So, what does effective automation look like? How can Robotic Process Automation (RPA) be added to EHRs and other healthcare platforms?
It is possible to combine deep RCM knowledge with automation expertise and to integrate standalone automations with EHRs and other platforms in an exclusively embedded fashion. Combining industry, technological, and platform expertise enables more comprehensive automation, leading to more effective and efficient outcomes. It also enables teams to avoid futile attempts at automating too-complex processes.
3. All Automation Improves Efficiency
With rising labor costs, there is great need for automation in healthcare. Yet, progress in RCM has been slower than that of many other industries. Why?
Automation loses significant value unless it is unattended, or fully automating a process from end-to-end, without requiring human intervention. This end-to-end aspect is particularly difficult to implement in the revenue cycle, which involves huge amounts of unstructured data and reasoning-based tasks.
Easily implemented automations are typically process-oriented and can only automate tasks that follow a clear, linear progression from start to finish. This is why early efforts have fallen flat—many require significant human intervention. These attended automations can be difficult to use and even tend to backfire, causing more burdens in training, clean-up, and execution—especially when wielded by inexperienced teams.
So, what does it take for automation to add significant value in healthcare RCM?
Consider a Paradigm Shift to Cognitive Automation
As opposed to simple rule-based automation, cognitive automation can execute tasks that require both reasoning and synthesis of unstructured data. Cognitive automation offers new opportunities to streamline processes that were previously dependent on human intervention.
Here are some practical applications of cognitive automation:
- Document Interpretation: Generative AI can read and understand complex documents, such as procurement policies or clinical guidelines, and identify relevant information or exceptions. When provided with specific documents like CMS medical necessity guidelines, cognitive automation reasons whether guidelines are being met. Consider the process of submitting clinical documents for prior authorization. Traditionally, a human would review the documents to ensure all necessary details are included. With cognitive automation, an AI system could reason over the clinical data to determine if it meets the required criteria. This system could then use APIs to submit the documents directly, bypassing the need for manual review and speeding up the authorization process.
- Eligibility Verification: By processing explanation of benefits s and other insurance verification documents, AI can determine eligibility and benefits, reducing the need for human review. Prior authorization statusing is also accomplished, where cognitive automation goes out to payer websites to status the claim or prior authorization request and bring that information back into the EHR.
- Denial Management: AI can analyze denial reasons and their root causes, generate appeal letters, and predict the likelihood of claim approvals. These insights inform conversations with payers and directly impacts time to payment.
Conclusion
While we do not see it ever fully replacing humans, the integration of cognitive automation in healthcare RCM will enhance productivity, reduce manual workloads, and improve accuracy. Automation can drive significant improvements in operational efficiency and revenue recovery.
Infinx provides scalable AI-driven solutions to optimize the financial lifecycle of healthcare providers across all functions of patient access and revenue cycle management. To stay ahead of ever-changing government regulations and payer guidelines, request a demo here.