By Ritesh Ramesh, CEO, MDaudit.
Healthcare organizations are in a precarious financial position. With operating margins still hovering near zero, revenues are at heightened risk because of a surge in third-party audits following the expiration of the public health emergency as well as increased scrutiny by federal and commercial payers alike to identify – and recover – billions in improper payments and penalties.
This sharp uptick in audit activity has many healthcare organizations – even those that have already adopted revenue cycle management (RCM) technologies to streamline workflows – struggling to comply with both the volume of incoming documentation requests (ADRs) and the timeframes within which they must reply.
The appearance of artificial intelligence (AI), specifically conversational AI, is promising to change that, making it possible to convert the highly unstructured data populating the audit process into information that can be both analyzed and automated.
The Audit Environment
Ferreting out fraud and abuse remains high on the federal government’s priority list. In fiscal year 2022, the U.S. Department of Justice (DOJ) collected more than $1.7 billion in improper payments, while the Office of the Inspector General (OIG) reported identifying more than $200 million in expected audit recoveries and over $277 million in questioned costs in its 2023 Semi-Annual Report to Congress.
Meanwhile, the Centers for Medicare & Medicaid Services (CMS) is expected to claw back $4.7 billion from Medicare Advantage plans over the next decade thanks to recent adjustments to its risk adjustment data validation (RADV) program. Add to all that the influx of demand letters in the wake of the expiration of the federal PHE – along with many of the waivers that kept external audits in check – as well as claim changes and heightened regulatory and billing practice scrutiny by federal contractors and commercial payers.
All this comes at a time when hospital margins remain “well below historical norms,” per Kaufman Hall, and revenue cycle leaders are facing severe labor shortages, with more than 41% reporting that up between 51% and 75% of RCM and billing department roles are currently vacant.
That’s more, many of those departments are ill-equipped to manage the influx of audit requests pouring in from all sides. Pre-pandemic, nearly one-quarter of hospitals reported responding to 500 to more than 2,000 external audit-related requests every month – a figure that pales in comparison to today’s volume.
The length of the ADR is getting longer, with some exceeding 100 pages. Further, nearly 40% of organizations rely on spreadsheets to track audits and denials versus more advanced technological denial management solutions.
The Power of AI
Even those healthcare organizations that have adopted RCM automation technology are quickly discovering that, without the added power of AI, it’s simply not enough to keep pace with the growing audit demands. The reality is that much of the data that comes into the audit workflows is unstructured, typically in the form of multi-page paper or PDF documents dealing with multiple claims files.
Thus, regardless of how advanced the organization’s RCM tools may be, that avalanche of unstructured data must be processed manually before any automation tools can be applied to help streamline the process. It is a time-consuming, error-prone process that is further complicated tenfold by the rapid increase in ADRs and shrinking staffing levels.
Conversational AI, when coupled with advanced Natural Language Processing (NLP) to digitize ADRs, can elevate RCM workflow tools and the overall audit process by accelerating response times, eliminating human error, and ensuring deadlines are not missed.
This powerful combination can be leveraged to deliver intelligent functionality to automate and accelerate management of external payer audits. As shown here, NLP allows users to upload ADRs from multiple payers regardless of format, which are then available for automated workflow tools to process. This eliminates the tedious and error-prone manual work of keying in data and reviewing hundreds of letters from payers every week and expedites the overall resolution of audits in a shorter timeframe, resulting in faster revenue retention with fewer resources.
Conversational AI also simplifies access to the insights found within ADRs and claims history (e.g., information about at-risk facilities, providers, or coders, or which DRG had the highest number of denials for medical necessity in a specific timeframe) that can help drive strategic decision making to reduce the likelihood of future audits and resolve systemic issues impacting audit rates and outcomes.
It democratizes these insights across all levels of a healthcare organization – from billing compliance auditors, revenue cycle analysts, operational leadership and to the C-suite – by responding to questions posed in natural language with precisely the insights being sought. These insights can then be tightly integrated with actionable workflows to drive outcomes.
Speed, Efficiency, Accuracy
The evolving audit environment poses numerous resource challenges at a time when many simply cannot afford any delays to the revenue cycle. Enhancing RCM workflow tools with conversational AI solutions specifically designed to address the complex audit process can eliminate the challenges presented by unstructured data, accelerate workflows to allow limited staffs to keep pace with higher audit volumes, and drive high performing revenue cycles.