What if you could recover a good chunk of the estimated $5 million a year of lost revenue from denied claims? Today, an increasing number of providers are turning to revenue cycle management automation to streamline processes, reduce errors, and improve their bottom line.
But what exactly is RCM automation and how does it work? Also, which healthcare revenue cycle tasks see the biggest benefit from AI intervention? Read on as we break down all of these important considerations.
How Can Automation Benefit the Healthcare Revenue Cycle?
The term “revenue cycle management” refers to all the administrative and clinical tasks involved in capturing patient revenue. A standard revenue cycle includes everything from patient registration and eligibility verification to claims processing and payment collection. Given this lengthy paper trail, errors (and lost time) can easily occur.
Automating these often tedious, manual processes helps hospitals and health systems improve many financial aspects of patient care. Revenue cycle management automation helps your facility to:
- Reduce costs.
- Boost staff productivity by taking on time-consuming tasks. This allows employees to concentrate on specialized, complex tasks that machines struggle to handle.
- Improve compliance with regulations, such as the No Surprises Act.
- Accelerate the revenue cycle for healthier cash flow.
Let’s take a closer look at just how revenue cycle management automation works and some of the tools you can use. You probably have your own revenue cycle management automation case studies bolstering your decision to go this route, too.
As healthcare organizations grapple with rising costs, eroding financial margins, ongoing labor shortages, and increasing cybersecurity risks, the need for innovative solutions to help ensure fiscal fitness and reduce administrative burdens has never been more pressing. Among the most promising avenues for addressing these challenges is the application of artificial intelligence (AI) and automation in revenue cycle management (RCM).
-Arnab Sen, Chief Strategy Officer at Omega Healthcare
How Revenue Cycle Management Automation Works
Traditionally, administrative staff managed much of the healthcare revenue cycle manually. As you can imagine, this approach is prone to errors and inefficiencies.
With a system of intelligent automation, you not only complete more revenue cycle tasks each day but also reduce the amount of time staff devotes to each. Everyone prefers working smarter, not harder.
Let’s look at how a few common revenue cycle management automation solutions leverage technologies. Some of these include:
- Robotic process automation (RPA)
- Natural language processing (NLP)
- Machine learning (ML)
- And artificial intelligence (AI)
As AI swiftly infiltrates many of our workplaces and personal lives, healthcare revenue cycle departments need to understand how these technologies (including revenue cycle management software) improve operations and patient care.
Automating Patient Eligibility and Prior Authorizations
Imagine that it’s Monday morning at a busy internal medicine practice, and the schedule is completely booked, with many new patients on the docket. As patients check in and front office staff work to confirm their insurance coverage, they learn that an unusually high number carry coverage that requires prior authorizations.
These are needed to see specialists or even their primary care physician. With 25 patients arriving in the next hour, securing prior authorizations for even half creates a mountain of work for administrative staff. This potentially results in significant appointment delays, disgruntled patients, and burnt-out staff.
Where Automation Comes In
With intelligent automation, software algorithms carry out pre-programmed rules. These verify patient insurance eligibility using basic patient demographics. This eliminates the need for a human staff member to call the insurance company or log into a time-consuming patient portal.
Systems can return eligibility results in seconds and schedule the appointment within moments, minimizing errors and eliminating the risk of data entry errors.
Automation software can then initiate the prior authorization process using similar workflows. These adhere to a particular insurance plan's prior authorization requirements.
Rather than taking hours, an automated system completes the work in minutes. This frees staff up for tasks that require a human touch, or at the very least a much-needed break. These AI-powered automations, by completing a variety of revenue cycle tasks faster and with fewer errors, contribute to McKinsey’s belief that technology will create between $350 billion and $410 billion in annual value in healthcare by 2025.
Coding Claims and Avoiding Denials
Next, let's imagine that same busy practice a month later. The medical biller begins tackling accounts receivable, noticing an unusually high number of claim denials for recently submitted invoices. After contacting various payers, the biller learns that a new coding change, effective a month ago, requires submitting a new code that many physicians are forgetting to use during patient encounters.
Unfortunately, errors are present on 80% of medical bills submitted to U.S. payers. Because many healthcare providers bill for patient services long after the patient has departed (up to 30 days or even later is common), securing this new code information is difficult.
Additionally, it costs physician practices $25 per claim in rework when the wrong code is submitted. Worse, it costs hospitals $181 per claim.
This often requires contacting a physician by phone or secure messaging for clarification. In turn, it potentially delays claim submission for days, weeks, or even longer.
In addition, 70 percent of consumers say they prefer receiving digital medical bills. However, healthcare organizations continue to rely heavily on old-fashioned paper statements.
How can an automated revenue cycle solution prevent denials in this scenario? Intelligent software algorithms can examine claim data for common errors, such as incorrect coding or missing information, and correct them or flag the invoices for human review and intervention.
Machine learning (ML) algorithms can also learn to identify patterns in claims data that are likely to result in denials. By being proactive, providers can avoid denials in the first place and, when denials are unavoidable, speed the resolution process.
Streamlining Patient Collections
Because many hospitals and physician practices haven't embraced automated billing statements that their patients can pay online, many resort to paper invoices, costly stamps, and endlessly pursuing payment. According to a 2023 survey by the National Association of Healthcare Revenue Integrity, automating revenue cycle processes had a positive impact on the bottom line for 73 percent of respondents.
Those who participated in a similar 2023 Black Book survey stated that adopting revenue cycle management automation software helped them enjoy a 27 percent reduction in cost-to-collect, while their net patient revenue increased by six percent.
Intelligent revenue cycle automation, however, offers practices of all sizes significant cost and time savings with collections. Today's technology not only prints, stuffs envelopes, and mails patient statements automatically, but can also set up payment plans and accept payments securely online. This provides your patients with a streamlined experience that more closely aligns with consumer-driven industries like retail.
Top Use Cases for Intelligent Automation in the Healthcare Revenue Cycle
One use case for automation in the healthcare revenue cycle is with patient records. Magical is a free Chrome extension that automates repetitive tasks such as data entry and auto filling forms. Healthcare companies benefit from using Magical because they only have to enter patient info once - then you can securely move that data across systems without annoying copying and pasting.
Here are some of the other revenue cycle areas where AI-driven tools are most impactful:
- Prior authorizations.
- Patient registration.
- Insurance verification and eligibility confirmation.
- Claims processing.
- Medical billing.
- Denials management.
- Payment processing.
- Reporting and analytics.
Choosing the Right Revenue Cycle Management Automation Solution
Selecting the right automation software is one of the most important steps you will take to improve revenue cycle performance. When choosing the right one for your organization, consider factors like the size and scope of your organization.
Other important considerations are your budget allocated for implementing such solutions, your facility or practice’s technical resources and whether you require assistance with implementation or would rather install it on your own. Here are some things to keep in mind during this stage:
FAQs about revenue cycle management automation
What is revenue cycle automation?
It's the process of streamlining tedious revenue cycle tasks with software. This eliminates or reduces time-consuming manual work to reduce denials, improve compliance, and provide a better customer service experience to patients.
What is RPA in the revenue cycle?
RPA, which stands for Robotic Process Automation, refers to the software systems involved in revenue cycle automation work. An RPA system automates repetitive tasks within a workflow. This saves healthcare staff time and reduces errors by limiting human involvement in data entry or analysis.
How is AI used in revenue cycle management?
AI, or artificial intelligence, has become an invaluable tool in revenue cycle management (RCM), significantly enhancing the efficiency and accuracy of various processes. For instance, AI-powered automation can rapidly analyze vast amounts of data, identify patterns, and predict outcomes. This allows healthcare providers to proactively manage their revenue cycles with greater precision, thereby minimizing errors and reducing the likelihood of claim denials.
One of the most impactful applications of AI in RCM is in the realm of claims processing. AI algorithms can accurately code claims, ensuring that they meet payer requirements. This accuracy reduces the incidence of rejected claims and shortens the time to reimbursement. Furthermore, AI can flag discrepancies and potential issues before submission, providing an extra layer of scrutiny that human staff might overlook.
Another significant benefit of AI is its ability to perform predictive analytics. By examining patient demographics, payer trends, and reimbursement patterns, AI delivers actionable insights into future financial performance. These insights empower healthcare providers to make data-driven decisions about staffing, service offerings, and financial policies, ultimately optimizing revenue and resource allocation.
AI also enhances patient engagement and satisfaction by facilitating smoother billing and collections processes. With AI, patients receive timely and accurate information about their financial responsibilities, which helps prevent surprises and enhances the transparency of the billing process. Automated reminders and easy-to-navigate online payment platforms streamline collections, making the process convenient for patients and efficient for providers.
In the ever-evolving landscape
Healthcare facilities and organizations use artificial intelligence in their revenue cycle to identify and fix potential coding errors, improve data accuracy, optimize collections efforts, and streamline billing tasks. This results in a much more efficient and cost-effective approach of
What is the revenue cycle management method?
This phrase generally refers to all of the steps that a physician practice or hospital takes to ensure the facility is properly compensated for medical services rendered, from the time the patient schedules an appointment to when the final balance is paid.
By leveraging automation, healthcare providers can streamline each of these steps, ensuring accuracy and efficiency. For instance, automated systems can verify insurance eligibility in real-time, reducing the risk of claim denials due to ineligibility. This not only accelerates the pre-appointment verification process but also enhances patient experience by providing clear information upfront.
Furthermore, automation in scheduling can optimize appointment bookings by intelligently managing time slots and reducing no-shows with automated reminders. Patient registration can be expedited through electronic forms that integrate directly with the healthcare provider’s system, minimizing manual entry errors. As a result, staff can focus more on patient care rather than administrative burdens, leading to enhanced productivity and service quality.
Automated medical coding tools can process complex medical data swiftly and accurately, ensuring compliance with coding standards and thus reducing the likelihood of claim rejections. Claims submission systems leverage automation to check and correct errors before submission, increasing the chances of first-pass acceptance and faster reimbursements.
Remittance processing benefits significantly from automation by facilitating quick reconciliation of payments with expected amounts, identifying discrepancies immediately. This ensures that underpayments can be addressed promptly, reducing financial losses.
Finally, regarding patient collections, automation can provide personalized communication strategies and flexible payment options, helping patients clear their balances more effectively. Automated reminders and notifications about upcoming payments or outstanding balances can improve collection rates and reduce the administrative efforts required for follow-up.
Boost Your Productivity With Magical
Revenue cycle management automation has the potential to transform healthcare finances. Perhaps even more importantly, it can also improve the patient care experience. As new automation systems emerge, AI and other exciting technologies will no doubt power these complex workflows. Magical has superpowers when it comes to revenue cycle management: just put it into action and see how much time you can save!
Bring over information from another application right into your software to track it, like we've done here on Wave!
Although it has its own set of challenges, AI technology promises to only become more sophisticated in the months and years ahead. Especially when you choose a tool like Magical to make your healthcare staff more efficient. Magical is used at more than 50,000 companies like United Healthcare, Dignity Health, and Nuance to save 7 hours a week on average on their repetitive tasks.
