AI: The Boost Needed for Better HC Revenue Cycle Management
Analytics Insight examines the emerging and crucial role of Artificial Intelligence in healthcare revenue cycle. They note that RCM has gotten more challenging due to ever-growing claims and healthcare consumer issues, but the three primary factors are:
- Increased patient financial responsibility
- Convoluted payer contracts
- The shift to value-based payments
The article goes on to note that AI is now a tool that needs to be in every "toolbox":
AI is no longer just a buzzword in the revenue cycle; it is a strategy leveraged to enhance the efficiency of RCM and the associated outcomes. By simplifying archaic processes and providing new intelligence to the claims lifecycle, Artificial Intelligence (AI) is revolutionizing the healthcare industry.
From spiraling claim volumes to more stringent payer requirements and increasing reporting obligations, today’s health practitioners face higher challenges than ever. As a result, diagnostics providers across the country are effectively looking for new revenue streams, improved payer relations, cost-cutting opportunities, and more predictable reimbursement rates. For example, high-quality and carefully designed data sets facilitate improved analytics, and the use of Artificial Intelligence (AI) can expedite the Revenue Cycle Management (RCM) process while also enhancing financial and operational performance.
The American Medical Association (AMA) polled 1,000 practicing physicians and found that:
- 86% of doctors rate the burden of prior authorizations as high or extremely high
- 88% indicated the strain has increased in the last five years
- Physicians and their staff spend over two full business days per week processing prior authorizations
- More than one-third of physicians have personnel dedicated only to this job
The article also mentions that it is evident that automation and AI can revolutionize the execution of the RCM process, with more healthcare organizations setting AI as a top priority.
- Recent surveys cite that 75% of medical institutions are implementing or planning to implement an AI strategy
- 43% indicating that automating business activities such as revenue cycle management could be their first move
AI in Healthcare RCM is Still Developing...Or AI Needs to be Deployed?
A common perception in the HC industry as a whole is that AI still needs time to develop. In certain sections of HC, this is whole-heartedly true. In RCM however, we need to pivot from the idea that AI is in development to AI needs to be deployed. Many vendors have spent years developing their AI technologies, and healthcare providers, RCM companies, clearinghouses, and billers are actively using AI to improve RCM, as deployments have been accelerated by the pandemic. Analytics Insights offers this final piece of advice:
Although the market for AI in healthcare revenue cycle management is still developing, providers can already reap the benefits of the cutting-edge technology. Identifying use cases is an excellent place to start with for AI investments. With AI, providers can discover plenty of avenues to automate processes that will help realize benefits in the long run and not just stop-gap solutions.
The measures being taken by these organizations are also supporting the goal of achieving true healthcare data interoperability. On top of this, the pending No Surprise Act we've been reporting on, which will introduce new, more detailed compliance rules, makes it vital for RCM to focus on electronification of paper-based remits and EOBs/EOPs. AI and machine learning technologies have been trained specifically to extract data from remits and EOBs/EOPs, electronifying these documents to create postable EDI 835 files that streamline the processing of healthcare payments -- creating a more efficient, pandemic resilient process.