In the ever-evolving landscape of healthcare, maintaining financial stability isn't just about managing patient care; it’s intrinsically tied to how effectively you handle your revenue. And when it comes to keeping your organization financially healthy, few things are as crucial as mastering revenue cycle management (RCM). While much attention often goes to managing denied claims, there's a significant, often-overlooked segment of accounts receivable (AR) that can silently drain your resources: claims with “no response”.
As we head into 2025, healthcare leaders are doing their due diligence to stay on top of the latest trends in RCM, not just to be trendy, but because these advancements are helping teams adapt strategies to maintain financial stability, accelerate revenue, and reduce denials. Understanding how to effectively tackle these "no response" claims, especially with the help of innovative advancements like AI, is key to unlocking profitability and ensuring no revenue is left on the table.
Let’s dive deep into understanding this challenge and explore how intelligent automation can transform your approach, streamline processes, and ultimately enhance your organization’s financial well-being.
The Hidden Drain: Understanding Your RCM Cost to Collect
In the competitive healthcare landscape, understanding and reducing your "cost to collect" is paramount for financial health. This term refers to the expenses incurred in obtaining payments for services rendered, and it’s a critical indicator of an organization's financial viability. Simply put, if it costs you more to collect money than the money you’re collecting, you have a serious problem.
Accounts receivable (AR) represents the money owed to healthcare providers, primarily by insurance payers for services delivered. Effectively managing this AR is crucial for maintaining an organization's financial health, as it is the "lifeblood" of any healthcare entity. Mismanagement of AR can lead to significant cash flow problems, which in turn can negatively affect patient care, expansion plans, and even the overall financial viability of your organization.
When we talk about managing AR, it’s a multifaceted process involving tracking, managing, resolving, and preventing issues within the revenue cycle. The primary goal is to keep the total unpaid AR as low as possible by prioritizing prevention. This means dedicating sufficient time and resources to stopping issues before they arise, which should always be the number one priority. Beyond prevention, efficient and effective resolution of outstanding AR is vital, along with meticulous tracking to ensure no revenue is lost. Without proper reconciliation from billing charges to claims submission and payer acceptance, it's easy to lose track of revenue.
Key Performance Indicators (KPIs) like “days in AR” and “aging” are essential tools for tracking and managing your AR performance. Your days in AR indicate how long it takes to collect on a claim, while aging refers to how long claims remain unpaid. If either of these numbers climbs too high, it signals underlying problems within your revenue cycle processes, highlighting the risk of losing revenue that is sitting unpaid in AR.
The Manual Burden: Why Traditional RCM is Expensive
Traditional revenue cycle management often grapples with a significant manual burden, inflating overall costs and creating "unnecessary backlogs". This stems from reliance on archaic billing systems, fragmented processes, and the sheer volume of time spent on low-value claims that could otherwise be automated. The healthcare industry is heavily regulated, with constantly changing rules and requirements that add to this complexity, forcing healthcare administrators and revenue cycle managers to scramble to stay up-to-date on everything from new coding guidelines to evolving privacy regulations.
A major challenge within the healthcare industry continues to be persistent staffing shortages and rising labor costs, which place a considerable strain on financial stability. Contract labor costs alone have surged by nearly 258% over the past four years, forcing many health systems to seek external assistance from revenue cycle management providers. While outsourcing can provide efficient ways to manage patient collections, claims processing, submission, and denials management, the internal processes often remain heavily manual.
Denials, in particular, are a constant headache for healthcare providers. An AKASA survey revealed that half of providers experienced increased denial rates in the past year, making this a significant challenge for future revenue cycles. Common causes include errors in patient information, insufficient documentation, or issues with prior authorizations. Dealing with these requires a proactive approach, including ongoing staff training and leveraging technology for automated prior authorizations and accurate claim submissions from the start.
However, claims with “no response” represent a unique and often overlooked operational challenge. While many robust denial management software and dashboards exist, they typically don't track claims that haven't received a denial. This means that claims with no response can easily be forgotten, even though they frequently represent substantial recoverable revenue. This oversight can significantly delay the revenue cycle and create unnecessary backlogs, underscoring the importance of having specific processes in place to identify and address these claims.
Why Do Insurance AR Claims Get No Response? Outline the Top Reasons
Insurance AR can be broadly divided into two categories: claims that have been denied or received some type of response from the payer, and claims that have received no response at all. The distinction is vital because they require different approaches.
A denial means the payer has reviewed and adjudicated the claim, deciding not to pay for a specific reason, communicated via a claim adjustment reason code (CARC) and a remittance advice remark code (RARC) on the explanation of benefits (EOB) or electronic remittance advice (ERA). This provides a clear path for action, whether it’s appealing, correcting, or re-submitting. Even if the reason isn't always perfectly clear, it at least signifies that the claim reached the payer and was processed, providing a starting point.
Claims with no response, on the other hand, are those that have been submitted but have yielded "absolutely no feedback, no denial, no payment, nothing". This presents a different challenge because there's no initial direction for what to do next. These claims demand proactive management; otherwise, they can linger for weeks or months, delaying the revenue cycle and creating backlogs.
As stated in the podcast:
"One of the key challenges with managing AR is ensuring that claims with no response don't fall through the cracks. And it's easy to get caught up in focusing on denials, especially if your denial management process is well supported by dashboards or technology. But here's the issue. Most denial software and dashboards don't track claims that haven't received a denial."
This often leaves organizations with a segment of AR that doesn't get addressed by existing solutions, posing an operational challenge. While some technology incorporates 276 (claim status request) and 277 (payer response) EDI transactions, providing status updates that can be integrated into practice management systems, limitations exist. Not all payers or clearinghouses support this connectivity, meaning a segment of AR will still require manual attention.
Here are the top four things you can check to resolve claims with no response, which in most cases will lead to a resolution:
Check the Claim Status: The first step is to verify the claim's status through the payer portal or status monitoring software. This helps determine if the claim is still being processed or if it's stuck somewhere. Sometimes, you might find it's already been paid, leading you to investigate payment posting issues. Or, it might be pending for medical records or a patient questionnaire, providing a clear follow-up action.
Check Payment Posting: This is crucial, especially if payments are received via paper checks or EOBs. A payment might have been processed but not yet posted in your system, indicating a delay with your payment posting team.
Verify Patient and Payer Information (Eligibility Check): This is often the most impactful step.
"In my experience, about 70% of claims with no response are caused by simple registration errors like incorrect subscriber IDs or outdated insurance details. Correcting this information and resubmitting the claim can often resolve the issue quickly." A simple eligibility check confirms that all patient demographics, subscriber information, and insurance details (including the electronic payer ID) are correct. Payers have been known to send fewer notifications for eligibility denials, meaning an uncorrected error in this area can lead directly to a “no response” situation.Check the Clearinghouse: Confirm that the claim was accepted by the correct payer. If a 277CA response indicates a rejection, it means the claim never even reached the payer and needs to be corrected and resubmitted. Even if accepted, ensure it was accepted by the intended payer.
If all these checks yield no response, the final step is to directly call the payer. Payers are typically required by contract or state law to respond within a certain timeframe (e.g., 30-45 days), even if it's just to acknowledge receipt and continued processing.
AI as the Efficiency Engine: From Data Lake to Smart Decisions
The sheer volume of data in healthcare is overwhelming, making traditional, manual approaches to RCM inefficient and costly. This is where Artificial Intelligence (AI) and automation step in as powerful efficiency engines, transforming vast amounts of raw data into actionable insights and guiding resource allocation. Healthcare executives are significantly increasing spending on IT and software due to the rise of AI technologies, including generative AI. These tools enhance efficiency, optimize workflows, and minimize errors in critical RCM areas such as patient registration, eligibility verification, claims processing, denials management, and payment posting.
Unlike traditional Robotic Process Automation (RPA) tools, which can be difficult to set up, expensive to maintain, and rigid in handling variations, AI is changing the game. Agentic AI, for instance, allows for quick setup of complex workflows in minutes instead of months. This advanced form of AI autonomously perceives, decides, and acts to achieve goals, adapting to new situations based on predefined instructions. By combining large language models (LLMs) with traditional AI methods, agentic AI agents can analyze data, make decisions, and perform actions with minimal human intervention, continuously improving their performance.
Agentic AI works by:
Automating complex processes effortlessly: It maximizes efficiency through full process automations, moving data between systems, navigating forms, and submitting information without human input.
Making decisions just like a human: Utilizing reasoning models, real-time data retrieval, and goal-based execution, AI agents make automations more reliable than traditional rule-based approaches.
Running entirely on virtual machines: This enables scalable automations and batch processing without limitations on automation volume.
Enabling smart data transformation: Data can be moved and transformed between applications automatically, handling date conversions, text extraction, and formatting without manual cleanup.
Intelligent PDF processing: Data can be extracted from any PDF (e.g., medical records, insurance forms) and populated into online forms instantly.
AI-powered resilience: Agentic AI agents adapt to changes and handle edge cases automatically, ensuring workflows continue reliably through self-healing workflows and error handling.
For revenue cycle management workflows specifically, agentic AI is ideally suited due to its ability to:
Understand and adapt to complex processes: RCM workflows involve interconnected steps, requiring analysis of unstructured data and nuanced decision-making. Agentic AI's ability to understand context and learn from experience is invaluable here.
Interact with multiple systems: It can integrate seamlessly with various RCM systems like EHRs, billing systems, and payment gateways, enabling smooth data flow and automation across departments.
Improve efficiency and accuracy: By automating tasks like claims processing, payment posting, and follow-up, it reduces manual effort, minimizes errors, and accelerates the revenue cycle.
This shift from rigid, rule-based automation (like manual driving with printed directions) to flexible, adaptable agentic AI (like self-driving cars) is transforming RCM. It means automations can course-correct, identify shortcuts, and get smarter over time.
Strategic Automation: Prioritizing Payments and Preventing Denials
With AI as the engine, strategic automation becomes possible, allowing healthcare providers to intelligently prioritize high-probability payments and proactively prevent denials. This involves using AI to automatically correct common errors, track payer behavior, and ensure staff focus on the most impactful claims, including resolving "claims with no response" proactively.
Agentic AI can significantly enhance claims management, eligibility verification, and prior authorizations, which are key areas that contribute to denials and no-response claims. For instance, by leveraging AI to observe team workflows, hidden inefficiencies can be identified, and automation opportunities flagged, even allowing for instant automation setup from existing Standard Operating Procedures (SOPs) or recorded workflows. This offers a "fast track to agentic AI automation," allowing teams to start automating within days and boosting efficiency by over 50%.
Once in autonomous mode, an AI workforce can operate fully independently, even while your human staff is offline, utilizing logic and making intelligent decisions within each automation. This level of autonomy is critical for scaling operations and ensures consistent reliability, with features like daily automated testing, detailed automation logs, and adaptive intelligence that adjusts when application changes occur. The platform is also built with security in mind, ensuring legal compliance and patient trust by avoiding the storage of keystrokes or patient data, thereby minimizing the risk of data breaches.
For the specific challenge of "no response" claims, which often stem from simple registration or eligibility errors, AI automation can provide immediate benefits:
Automated Eligibility Verification: AI can instantly perform eligibility checks, confirming subscriber IDs and insurance details, and automatically update systems, preventing common reasons for claims getting stuck or not receiving a response.
Streamlined Clearinghouse Management: AI can monitor clearinghouse acceptances and rejections in real-time, quickly identifying claims that never reached the payer or were rejected for correctable errors, ensuring they are addressed before timely filing limits are breached.
Proactive Payment Posting: If "no response" claims are due to unposted payments, automated payment posting, especially through the conversion of paper EOBs to 835s, can drastically increase productivity and reduce the time payments remain unposted, directly impacting AR KPIs.
By integrating AI throughout the RCM process, organizations can move from a reactive approach to a proactive one. This strategic application of technology helps to identify root causes of issues like unposted payments or unaddressed rejections, enabling systemic improvements that prevent future problems.
Ready to transform your revenue cycle management with intelligent automation? Book a demo with the Magical team to see how agentic AI can put your RCM workflows on autopilot, reducing errors and accelerating revenue.
Optimizing Your Workforce: Empowering Staff with Intelligent Delegation
One of the significant benefits of leveraging AI in RCM is the ability to optimize your workforce by empowering staff through intelligent delegation. This means that while AI handles routine follow-ups and corrections, your experienced team members can focus on complex appeals and strategic tasks.
When it comes to managing AR, assigning the right team members to the right tasks is a practical strategy for efficiency. For example, claims with "no response" can serve as an excellent entry point for less experienced staff members or those new to the revenue cycle field. These claims are often straightforward, primarily requiring correction of patient demographics or payer details and resubmission. This allows beginners to grasp the fundamentals of claim correction and submission without immediately diving into the complexities of denials. As they gain experience, they can progressively take on more challenging billing responsibilities.
In contrast, handling denials demands a higher level of expertise, involving a nuanced understanding of payer policies, coding regulations, and the appeals process. By utilizing AI to automate the more routine, high-volume tasks associated with "no response" claims and initial follow-ups, your seasoned staff are freed up to dedicate their specialized skills to these intricate denial challenges. This ensures that each team member is working on tasks best suited to their skill level, making your entire AR process more efficient.
AI employees, like those powered by agentic AI, can run fully autonomously, handling time-consuming workflows faster and more flawlessly, even working "while you sleep". This eliminates the constraint of budget cuts and headcount freezes by providing a scalable workforce that tackles the most mundane and soul-crushing tasks. This means your human team can be reallocated to focus on higher-value activities, complex problem-solving, and direct patient engagement, which require human empathy and critical thinking that AI cannot replicate.
Magical, for example, is highlighted as a top RCM company that helps healthcare companies put their RCM workflows on autopilot with AI employees. It is designed to automate entire processes end-to-end without human oversight, while still providing comprehensive monitoring tools for transparency. This allows healthcare organizations to increase revenue by decreasing billing errors and speeding up processes like patient charting by 25%. By automating repetitive tasks, Magical aims to "free the global workforce of mundane, soul-crushing tasks". This delegation of repetitive, rule-based (or intelligently adaptive, for agentic AI) work to AI empowers your human staff, boosts overall productivity, and allows them to focus on complex appeals and strategic tasks that truly move the needle for your organization.
Conclusion: A Leaner, More Profitable RCM with AI Automation
The journey to a leaner, more profitable revenue cycle management system begins with a proactive and holistic approach, especially when it comes to the often-overlooked segment of "no response" claims. By understanding the financial drain caused by these unresolved claims and the inefficiencies of manual RCM processes, healthcare organizations can strategically implement advanced solutions.
The integration of AI and automation, particularly agentic AI, is not just a trend for 2025; it's a fundamental shift in how healthcare teams can adapt their strategies to maintain financial stability, accelerate revenue, and reduce denials. Agentic AI transforms the RCM landscape by handling complex processes effortlessly, making human-like decisions, adapting to changes on the fly, and ensuring high reliability and security. This technology is perfectly suited for RCM workflows due to its ability to understand nuances, interact with multiple systems, and significantly improve efficiency and accuracy.
By embracing this innovation, revenue cycle leaders can steer their organizations through challenging times. Investing in technologies that automatically correct errors, monitor claim statuses, and streamline payment posting is key to preventing "no response" claims from occurring in the first place and quickly resolving those that do. Furthermore, strategically deploying AI allows for the intelligent delegation of tasks, empowering your workforce and optimizing human talent for higher-value activities like complex appeals.
The goal is not just to survive, but to thrive amidst a changing industry. By making smart, data-driven decisions and embracing a proactive approach, healthcare providers can support their financial well-being while enhancing the patient's financial experience. The ability to "put these RCM trends into action" through AI automation tools like Magical, which are designed to make automation simple and secure, is a testament to this transformative power.
Your next best hire isn't human—it's agentic AI that enables fully autonomous, scalable workflow automations. By transforming repetitive workflows into efficient, self-driving processes, healthcare organizations can ensure that no revenue is left on the table, ultimately providing more resources to dedicate to patient care.
Curious how Magical's Agentic AI can make tasks disappear and streamline your specific RCM workflows? Book a Free Demo today and discover how to automate your revenue cycle for greater profitability.
