All posts by Kelly Nguyen

Key takeaways: Artificial intelligence (AI) is changing how healthcare organizations operate, but while most providers believe in its potential, adoption is uneven. As payers use AI to control costs, providers must apply the same technology to address rising claim denials and data quality challenges. Experian Health’s AI Advantage™ and Patient Access Curator™ help providers prevent denials, improve efficiency and strengthen financial performance. AI is transforming every part of healthcare. In the doctor’s office, it supports faster diagnoses and treatment decisions. At the front desk, it helps verify coverage and schedule appointments. And in the business of healthcare, AI’s ability to interpret vast amounts of data is changing how claims are reviewed, processed and paid. But transformation is not without challenges. As providers adopt AI and machine learning (ML) to improve care and operations, payers are using the same technology to control costs and make faster coverage decisions. According to the American Medical Association, 61% of physicians believe AI is increasing prior authorization denials. Strategic use of AI is the only way to keep pace and remain competitive. This article outlines what providers need to know about using AI in healthcare, including how Experian Health’s AI Advantage and Patient Access Curator use AI to prevent denials, improve efficiency and strengthen financial performance. Understanding AI technology and machine learning in healthcare AI refers to technology that performs tasks that require human-like reasoning, such as recognizing patterns, interpreting data and solving problems. It learns from experience, spots trends a human eye might miss and generates recommendations based on what users want to achieve. Machine learning is a subset of AI that improves performance over time, helping healthcare organizations turn their own complex information into practical insights. Because these models are trained on each organization’s unique data, they can adapt to local patterns and workflow differences, making their predictions far more accurate. Clinical and operational applications AI and ML are now used in many areas of clinical care, such as: Improving diagnosis by analyzing medical images with greater accuracy. Accelerating drug discovery by tracking side effects and treatment outcomes. Improving surgical safety and precision through robotics. Supporting patients in managing their own health through wearables and remote monitoring. On the operational side, AI helps staff work smarter and faster. Patient access teams use AI to verify insurance, forecast demand and manage scheduling, while revenue cycle leaders use it to reduce manual work and improve claim accuracy. Experian Health’s State of Claims 2025 report found that 69% of organizations using AI solutions have seen fewer denials or higher resubmission success rates, reflecting measurable gains in both efficiency and financial performance. Read the Q&A: How AI innovation is transforming healthcare revenue cycle management Experian Health executive David Figueredo gives a closer look at how we’re helping healthcare organizations use AI to tackle claim denials head-on. How AI technology in healthcare can prevent and reduce claim denials and boost financial performance Despite these gains, denials are still rising, revealing persistent problems with data quality. More than half of providers (54%) in the State of Claims report say claim errors are increasing, and 68% find it harder to submit clean claims than they did a year ago. On top of this, keeping up with payers’ use of AI is challenging. American Medical Association President Bruce A. Scott notes, “emerging evidence shows that insurers use automated decision-making systems to create systematic batch denials with little or no human review.” In contrast, on the provider side, around 90% of denials require manual rework, contributing to a widening technology gap that slows reimbursement and puts pressure on already stretched teams. Experian Health’s AI-based solutions can help close this gap. Capture accurate data from the start with Patient Access Curator. Patient Access Curator uses AI and machine learning to automate front-end eligibility and authorization workflows. It verifies eligibility, insurance coverage and reduces the data errors that often lead to downstream denials. Improving data quality before a claim is created helps organizations submit cleaner claims, reduce delays and deliver a better patient experience. Case study: Experian Health and Ohio Health See how Ohio Health cut denials by 42% with Patient Access Curator and solved claim errors at the source. Predict and prevent denials with AI Advantage In a recent webinar, Eric Eckhart of Community Regional Medical (Fresno) and Skylar Earley of Schneck Medical Center discuss how AI Advantage helped them take control of their denials management strategy and maximize reimbursement. “What really sold [AI Advantage] for me was that it’s looking at my data. It’s not looking at Skylar’s data in the Midwest. It’s looking at my data in central California. We have lots of little payers that do their own thing, and it’s learning from my information, my actual denials that are happening. If the payer shifts, the model’s going to follow that and let me know about it.”— Eric Eckhart, Director of Patient Financial Services at Community Medical Centers AI Advantage takes a two-pronged approach to reduce the risk of denials and expedite rework: AI Advantage – Predictive Denials examines claims before submission and calculates the probability of denial based on historical payment data and undocumented payer behavior in real-time. High-risk claims can be edited before submission to reduce the risk of denial. AI Advantage – Denial Triage evaluates and segments denials based on the likelihood of reimbursement and prioritizes the work queue accordingly. It learns from past decisions to formulate recommendations with increasing accuracy, so staff can focus on denials that will be most likely to yield results. Eric Eckhart of Community Regional Medical (Fresno) and Skylar Earley of Schneck Medical Center discuss how AI tools have helped them reduce denials. Watch now > Key challenges of implementing AI technology in healthcare Interestingly, the State of Claims survey suggests confidence in AI outweighs adoption. While 67% of providers believe AI can improve the claims process, only 14% use it to reduce denials. This suggests some caution around the practicalities of AI implementation. For smooth implementation of AI technology, providers should consider three essentials: Data quality: AI tools are only as good as the data they analyze. Partnering with a reliable third-party vendor can help providers ensure that data is error-free and usable. Integration: New tools must fit easily with existing workflows and systems. A single-vendor solution can mitigate interoperability issues. For example, AI Advantage fits seamlessly with ClaimSource®, reducing disruption. Compliance and security: Solutions must comply with data privacy and security regulations, like HIPAA, to avoid financial and reputational risk and maintain patient trust. FAQs What is AI technology in healthcare? AI in healthcare uses algorithms and machine learning to analyze data, support clinical decisions and automate administrative tasks. How does AI technology improve the healthcare revenue cycle? AI technology automates claim reviews, predicts denials and prioritizes claims to maximize reimbursement efficiency. How can healthcare providers start using AI for claim denial management? Tools like Experian Health’s AI Advantage and Patient Access Curator integrate with existing claims management workflows to predict and prevent denials, automate reviews and improve front-end accuracy for faster reimbursement. What’s next for AI technology in healthcare? As predictive analytics, natural language processing and automation advance, providers that use AI strategically will see greater efficiency and faster reimbursements. With payers and competitors accelerating their AI adoption, understanding where and how to apply these tools will be essential to staying adaptable and financially resilient. What’s next for AI technology in healthcare? As predictive analytics, natural language processing and automation advance, providers that use AI strategically will see greater efficiency and faster reimbursements. With payers and competitors accelerating their AI adoption, understanding where and how to apply these tools will be essential to staying adaptable and financially resilient. See how AI Advantage and Patient Access Curator are helping Experian Health’s clients transform healthcare operations. Learn more Contact us

Key takeaways: As claims denial rates continue to climb, pressure is mounting on healthcare organizations to find new ways to reduce denials. Leveraging artificial intelligence (AI) and automation-based tools, like Experian Health's AI Advantage™ and Patient Access Curator™ solutions, is proven to lower denial rates. More than half of survey respondents say they’d replace existing claims management platforms if presented with compelling ROI to make the change. Claim denials are a well-documented challenge for healthcare organizations. Denied claims take much longer to pay out than first-time claims, if they get paid at all. Each one means additional hours of rework and follow-up, pulling in extra resources as staff review payer policies and figure out what went wrong. It’s time-consuming and costly. Beyond dollars and paperwork, denials affect patient care as uncertainty about payments leads to delays in treatment or unexpected out-of-pocket costs. But how do healthcare leaders feel about the state of claims management today? How are they tackling the administrative burden? Is there any light at the end of the denials tunnel? Experian Health surveyed 250 healthcare revenue cycle leaders to find out. The 2025 State of Claims report breaks down the survey findings, including insights into how automation and AI technology are being used (or not!) to optimize the claims process for denial prevention and increase revenue. The State of Claims: 2025 Download the full report to uncover actionable strategies and see if AI is what can break the denial cycle for your organization. What is the current denial rate for healthcare claims? Health claims are still stuck in a cycle of denials, delays and data errors. 41% of survey respondents said that at least one in ten claims is denied. That’s a lot of rework and lost revenue that providers were counting on. In 2009, claims processing accounted for around $210 billion in “wasted” healthcare dollars in the US. A decade later, the bill had climbed to $265 billion. Industry reports – including Experian Health’s State of Claims series – repeatedly observed a rise in denial rates. Today, 54% of providers agree that claim denials are increasing. And with this increase, providers constantly worry about who will pay – and when. What are the most common reasons for healthcare claim denials? According to the State of Claim survey respondents, the top three reasons for denials are missing or inaccurate data, authorizations and inaccurate or incomplete patient info. In short? The problem is bad data. 26% say that 10% of denials result from inaccurate or incomplete data collected at patient intake. Given how much information has to be processed and organized to fill out a single claim, this isn’t surprising. From patient information to changing payer rules, the sheer volume of data points to be collected and collated creates too many opportunities for errors and omissions. Other challenges, such as coding errors, uncovered services, eligibility checks, and staff shortages still play a role, but it’s clear that solving the data problem could make a meaningful dent in the denials problem. Blog: How data and analytics in healthcare can help maximize revenue Find out how the right data and analytics can help providers better understand their patients, streamline operations and improve revenue. Could automation improve claim denial statistics? To help break the denial spiral, more healthcare providers are turning to claims management software. Leveraging technology helps organizations resolve or prevent the snags that interfere with claims processing and billing workflows – boost claim success rates. That said, around half of providers still review claims manually. Yet, despite the proven benefits of integrated workflows and automation, the drive to implement new technology seems to have lost momentum. In 2025, 41% of survey respondents say they upgraded or replaced their claims management technology in the last year. However, 56% say that their current claims technology is sufficient to address revenue cycle demands – far below the 77% in 2022. While some tasks still genuinely require a human touch, staff time is often wasted on repetitive, process-driven activities that would be better handled through automation. Here are a few ways claims automation can help improve claim denial statistics: Connect the entire claims process end-to-end: Using an automated, scalable claims management system – like ClaimSource® – helps providers manage the entire claims cycle in a single application. From importing claims files for faster processing to automatically formatting and submitting claims to payers, it simplifies the claims editing and submission process to boost productivity. Submit more accurate claims: 68% of survey respondents say submitting clean claims is more challenging than a year ago. There’s a strong case, then, for using an automated claim scrubbing tool to reduce errors. Claim Scrubber reviews pre-billed claims line by line so errors are caught and corrected before being submitted to the payer, resulting in fewer undercharges and denials and better use of staff time. Improve cash flow: Automating claim status monitoring is one way to accelerate claims processing and time to payment. Enhanced Claim Status eliminates manual follow-up so staff can process pended, returned-to-provider, denied, or zero-pay transactions as quickly as possible. Reduce denials: Denials Workflow Manager automates the denial process to eliminate the need for manual reviews. It helps staff identify denied claims that can be resubmitted and tracks the root causes of denials to identify trends and improve performance. It also integrates with ClaimSource, Enhanced Claim Status and Contract Manager, so staff can view claim and denial information on a single screen. Improving claim denial statistics with AI While automation speeds up the denials workflow by taking care of data entry, AI can examine that data and recommend next steps. Of the 14% of survey respondents who said their organization is currently using AI, 69% say that AI solutions have boosted claims success rates, reducing denials and/or increasing the success of resubmissions. Current ClaimSource users can now level up their entire claims management system with AI Advantage, which interprets historical claims data and payer behavior to predict and prevent denials. The video below gives a handy walk-through of how AI Advantage’s two offerings, Predict Denials and Denial Triage, can help providers respond to the growing challenge of denials. Additionally, turnkey AI solutions, like Patient Access Curator (PAC), allow organizations to ensure claims are processed accurately from the start. Introduced in 2025, PAC is a groundbreaking tool that consolidates important functions like eligibility checks, MBI, demographics and discovery into one seamless solution – maximizing clean claims and minimizing denials, appeals and resubmissions. Explore how Experian Health is reshaping the way health systems manage Coordination of Benefits. Learn how automation and AI are eliminating manual errors, reducing denials and unlocking millions in recoverable revenue. Watch now > Can AI break the claims denial spiral? Technology is critical to improving claims management processes, and 59% of survey respondents say they plan to invest in claims management technology in the next six months. Leveraging AI for claims management could break the cycle of denials, but is healthcare ready to trust it? Despite a solid understanding of AI’s potential, survey findings suggest many healthcare organizations still have concerns. According to the data, top worries include its accuracy, HIPAA compliance, the need for staff training on new technology, and AI’s understanding of payer-specific rules. However, as claim denials continue to rise, organizations that make the leap to adopt technology-based solutions that leverage automation and AI could prevent more denials and level the playing field with payers. Download Experian Health’s 2025 State of Claims report for an inside look at the latest claim denial statistics and industry perspectives on claims and denials management. Get the report Contact us

"We knew we needed to transform our authorization workflow processes. We were experiencing a high rate of denials due to a lack of authorizations."- Amy Grissett, Senior Director of Ambulatory Revenue Cycle at USA Health Challenge: Manual processes that couldn't keep up Serving more than 250,000 patients each year across hospitals, specialty centers and outpatient clinics means USA Health processes hundreds of thousands of authorizations. Speed is critical. Unfortunately, small inefficiencies were taking a major toll. Frustrating manual authorization processes resulted in work queue errors, forcing staff to print schedules multiple times a day to keep track of changes. Inevitably, cases were missed, resulting in claim denials and delays. It was hard to see where to make improvements without a reliable way to monitor staff performance. As new service lines were added and authorization requests grew, USA Health needed to find a more efficient way of handling authorizations, or overworked teams would be under even more pressure. Amy Grissett, Senior Director of Ambulatory Revenue Cycle at USA Health, says, "We knew we needed to transform our authorization workflow processes. We were experiencing a high rate of denials due to a lack of authorizations." Since hiring extra staff had been ruled out, automated prior authorizations were the obvious solution. Solution: Automating authorizations for faster, more efficient workflows Having already worked with Experian Health for eligibility, USA Health decided to implement Authorizations to optimize their workflows and automation. Alicia Pickett, Senior Product Manager at Experian Health, explains how this partnership worked: "First, the team needed to determine if authorization was necessary. If so, they would complete the authorization on the payer's website. Experian Health's Authorizations would then track the status of the authorization, saving time on phone calls and web portals for pending cases. Once the authorization was obtained, our product would automatically post the status update into the EHR." Automating status inquiries this way meant staff no longer needed to chase information through phone calls and payer portals. Dynamic work queues and alerts would guide them to priority tasks, allowing them to work more efficiently and accurately. Most importantly, authorized services could be cleared without delay. The tool also compares authorized procedures to those actually performed and flags any variance, so staff can amend claims submissions and prevent denials. "The implementation process took approximately 6-8 months, and we did it in phases," Grissett explains. "We started with one service line. As the team became more comfortable, we added additional service lines. Overall, the implementation met our expectations. And the solution has greatly improved our authorizations process and workflows." Outcome: Authorizations up, denials down Since implementing Authorizations, USA Health has seen measurable improvements, including: Increased daily authorizations by 100% Cut manual work by 50% and reduced errors and denials Expanded to six service lines without increasing staff Provided accurate tracking of staff productivity Instead of relying on slow, manual processes, staff now have thirty dynamic work queues at their fingertips, helping them process 130,000 authorization requests each year. Thirty dynamic work queues organize tasks by date and service line in real time. With automated payer website checks now delivering instant updates for more than half of all accounts, they can focus on the smaller number of complex cases that need hands-on management. The impact on productivity is clear. With the new workflow in place, the average number of accounts completed per employee each day has more than doubled, from around 20 accounts to between 40 and 50. In addition to monitoring accuracy and denial rates, Authorizations' monthly scorecards make it easier to measure staff performance. Grissett says, "We were trying to do more with less. We also wanted to be able to monitor what our employees were doing and ensure they were accountable. The tools that Experian provides allow us to capture that data." All of this benefits patients, too: With automated prior authorizations, fewer appointments are canceled or rescheduled because of authorization delays, so patients don't have to wait for care. "The Experian team was instrumental in helping us pivot and develop specific workflows tailored to our needs. Together, we addressed missing payer connections and created knowledge-based rule sets to drive efficiencies. As we add new facilities or services, the process is fairly seamless. We already have the intel on the number of staff required to manage a specific number of accounts, the productivity measures needed and how to streamline processes. This allows us to replicate workflow processes and optimize operations effectively. In fact, we've added six more departments with our staff of 28." - Amy Grissett, Senior Director of Ambulatory Revenue Cycle at USA Health Looking ahead, the team plans to introduce more service lines and facilities while continuing to refine workflows and streamline processes. Find out more about how Experian Health's automated prior authorizations can help your healthcare organization boost productivity, reduce errors and prevent costly denials. Learn more Contact us

Healthcare organizations are facing a perfect storm: rising claim denials, evolving payer rules, and patients expecting providers to reduce error rates that impact patient billing accuracy. Artificial intelligence (AI) has raised the stakes, causing revenue cycle leaders to feel the pressure to modernize quickly. According to Experian Health's State of Claims 2025 survey, 73% of providers agree that claim denials are increasing, which is a clear signal that outdated processes cost providers millions. The top-ranked reasons for denials included coding errors, missing or inaccurate data, authorizations, and incomplete information, to name a few. And with only 14% of providers using some form of AI technology in their processes, the message is clear:  the opportunity is high to get more providers to embrace the technology and reap the benefits of smarter automation. To stay competitive and financially viable, healthcare organizations must embrace AI-driven innovation that improves data accuracy, streamlines workflows and proactively prevents revenue leakage. To explore how leading RCM companies are responding, we interviewed David Figueredo, Experian Health's VP of Innovation, to get a closer look at how we're helping healthcare organizations use AI to tackle these challenges head-on. Meet the Executive David Figueredo, VP of Innovation at Experian Health, has spent over 20 years driving transformation in healthcare finance. Known for blending tech-forward thinking with operational expertise, David is passionate about using AI to solve persistent challenges in revenue cycle management, especially around claim denials and data accuracy. He believes that healthcare innovation must be both purposeful and scalable. "We're not just chasing trends, and buzzwords do not functionally solve problems," he says. "By focusing on building systems that adapt to payer behaviors and addressing the labor costs and manual inefficiencies providers face today, we can deliver measurable improvements in financial performance." David is passionate about building tools that empower revenue cycle teams to work smarter, not harder. "We're not just layering tech on top of broken processes," he says. "We're redesigning the workflows themselves to intuitively account for these emerging AI capabilities and by doing so, we are finding ways to fundamentally change those processes." Q1: "David, let's start with the big picture. How are you and your team thinking about innovation in revenue cycle management right now?" David: "At Experian Health, innovation is a strategic imperative, and the core to everything we do. We're focused on solving revenue cycle pain points, especially around claims management and patient access by blending AI, automation, and data intelligence to streamline workflows. We're not just trying to overlay new tech on yesterday's processes; we're reimagining how revenue cycle teams will operate, to reduce manual touch points and increase automated decisioning. That means leveraging AI to automate repetitive tasks, enable earlier and continuous monitoring with timely corrections, and equipping teams with actionable workflows backed by trustworthy, transparent insights. We're also seeing a shift in mindset and attitudes around automation and applied AI. Innovation used to be a long-term goal that took years to see measurable outcomes. Now, it's a short-term mandate where the pace of progress needs to deliver value today and increased value tomorrow. Our clients expect to see and feel the progress now, not just the promise of value in years to come. That's why we've designed a modular solution that allows clients to deploy AI tools where they deliver the most immediate value, while also supporting more complex workflows and integrations for the future. This includes integrating intelligence to improve eligibility checks, coordination of benefits (COB) and identity functions, enhancing claim scrubbing processes with accurate denial prediction and prioritization, and strengthening financial decisions with better data modeling that builds trust. Innovation should be cross-functional. This means aligning product design with IT build processes to reduce deployment times and mitigate risks, incorporating operations teams to ensure the right problems are being addressed, and enabling finance teams to better understand how technology impacts primary and secondary revenue streams." Watch our on-demand webinar to learn how healthcare organizations are using AI to eliminate manual payer chaining, detect and correct coverage issues in real-time, and reduce claim denials. Watch now Q2: "AI is everywhere these days, but how are you actually using it to reduce claim denials and improve data accuracy?" David: "AI can be a game-changer, but there is more to solving problems than just applying new technology. According to Experian Health's State of Claims 2025 report, 41% of respondents say their claims are denied more than 10% of the time. And 54% agree that errors in claims are increasing. We have to be thoughtful in how and where we apply AI to improve learning on the fly, promote integrated decision support in real time and automate actioning so that highly skilled and limited staff can focus on higher-value functions. AI is not just about automation; it's about intelligent intervention applied to real problems, removing guesswork, early issue identification and eliminating missed steps to improve the overall yield of the revenue cycle. Consider the denial space, where billions in revenue are lost each year. While the causes of denials are very diverse, many of them are excellent opportunities for applied AI to improve denial rates. Our flagship product, Patient Access Curator™, uses AI to address key drivers, such as eligibility and COB errors that account for 15-30% of all denials. AI can surveil system and user activity to detect missed coverage or primacy issues, then pursue those leads and update the HIS in real-time — both at registration and at every other touchpoint in the patient journey. Another great example of applied AI is our AI Advantage™ denial prediction and triage solution. While claim denial screening and prioritization are not new concepts, AI takes this to a new level by integrating behavioral analytics, machine learning processes and big data analytics into a simplified process. This solution doesn't just detect denials; it prioritizes them based on financial impact and likelihood of denial recovery, driven by a larger decision support framework that improves accuracy and reduces noise. Revenue cycle teams can then focus on high-value, revenue-protecting activities, rather than low-yield procedural work. Our models continuously learn from evolving payer behaviors as they emerge, to predict denial risk and recommend corrections in real time. And because they're continuously learning, they get smarter and vastly more adaptive than legacy ways of prioritizing pre-denial and denial workflows. It's a dynamic system that evolves with the payer landscape that maximizes limited resources, which I think is the hope and expectation of modern, AI-driven revenue cycle processes." Q3: "Can you give us a sense of the impact? What kind of results are clients seeing with AI tools?" David: "Absolutely. We are seeing some amazing early data that clearly point to very differentiated outcomes over traditional technology approaches. Since deploying our AI-driven denial prevention engine, we've seen a 15-60% reduction in initial eligibility and COB claim denials, with an average performance of ~30% reduction across our client base. However, the impact is not just on claim denials; we have to understand there are populations of patients, such as self-pay patients, that benefit from improved automation and intelligence that AI applied correctly can bring. We are also seeing significant reductions in self-pay at registration rates when AI is driving the automation. Here, we see ~25% reductions in self-pay at the time of registration. This is relevant and striking on so many levels, as correct estimates can now be provided pre-service, and authorization processes can now work more effectively, which leads to better patient experiences. What's most impactful is how these results compound over time. As AI tools mature, they start identifying systemic issues—like recurring documentation gaps or payer-specific quirks—that manual reviews often miss. That insight enables clients to fix individual claims while optimizing workflows and upstream processes, leading to long-term gains in efficiency and revenue integrity." Learn how Patient Access Curator streamlines patient access and billing, prevents claim denials, improves data quality, and makes real-time corrections to boost your healthcare organization's bottom line. Q4: "Let's talk about the patient side. A lot of innovation is happening behind the scenes, so how does that translate into a better patient experience?" David: "That's a great point. A lot of what we do in revenue cycle innovation isn't visible to patients, but it absolutely impacts their experience. In many cases, our patients are the victims of broken processes and fragmented data that AI and related technology improvements will help to resolve. Take claim denials, for example. When a claim is denied because of a missing authorization or incorrect insurance information, it doesn't just delay payment; it creates confusion and stress for the patient who may suddenly receive a surprise bill for something outside of their control. Resolving this issue requires multiple calls to the provider or payer, which adds frustration. This creates a stressful experience and negatively impacts the provider's brand perception. That's where AI makes the difference. We use Experian Health's AI-powered registration optimization and claims management tools, like AI Advantage, to catch these issues early, before the incorrect estimate is generated, before the authorization is missed or before the claim is submitted. This drives more consistency and automation into the revenue cycle. By improving data accuracy at the front end—with things like insurance verification, COB issue detection, automated coverage surveillance and predictive analytics — we're helping providers get it right the first time. The result: fewer billing surprises, faster resolutions and a smoother patient journey. While the patient may not see the AI working in the background, they feel the difference when their estimates are more accurate, duplicate or conflicting statements are reduced, and they no longer have to chase down answers. This builds trust and improves patient satisfaction – allowing them to focus on their health, rather than revenue cycle issues they should never have to deal with." Q5: "For healthcare organizations that are just starting to modernize their revenue cycle, where should they begin?" David: "Start by understanding your internal views, change threshold and restrictions. Many healthcare providers don't ask hard questions about their goals, the data they're willing to share or how to prioritize their needs. AI is only as good as the data it has access to, so ensure your data is clean, structured, and compliant with legal and clinical requirements. Next, find partners with the right technical tools and healthcare experience. Focus on measurable outcomes —not just technology—and prioritize areas with the greatest revenue leakage, high FTE investments or elevated patient risk. Don't underestimate the importance of change management. Involve your operations, training and strategy teams early, and make them part of the innovation process. Overemphasize the human element of change control to improve outcomes. Finally, always keep the patient in mind. Every improvement in the revenue cycle affects their experience and access to care. Design technology solutions that simplify the patient journey, reduce their burden, and help lower the cost of care." The future of RCM lies in AI innovation  As healthcare organizations navigate mounting financial pressures and the increasing complexity of payer requirements, the need for smarter, AI-powered solutions has never been greater. By embracing intelligent automation, providers can reduce costly errors and denials, strengthen their financial stability and enhance patient experiences. Learn how Experian Health's AI-driven solutions, like Patient Access Curator and AI Advantage, can help your healthcare organization minimize claim denials, streamline workflows and unlock new opportunities for financial success. Learn more Contact us

Key takeaways: Manual work and disconnected claims management systems are often error-prone, resulting in delayed and denied claims. Technology, like automation and AI, can help healthcare organizations predict and prevent potential claims issues before submission. Implementing AI-powered claims management solutions should be a top priority for revenue cycle leaders. Healthcare claims denials are on the rise — but so is a new era of technology that can predict and prevent denials before they occur. Leveraging artificial intelligence (AI) for claims management can help organizations break the denial cycle and keep revenue cycles churning. In this article, we’ll explore how solutions like Experian Health’s innovative Patient Access Curator and AI Advantage™ are designed to help providers reduce claim denials with ​AI. Explore how Experian Health is reshaping the way health systems manage Coordination of Benefits. Learn how automation and AI are eliminating manual errors, reducing denials and unlocking millions in recoverable revenue. Watch now > Updating healthcare claims management tools  Claims management is one of the most pressing challenges in healthcare billing. In Experian Health’s 2024 State of Claims survey, 77% of providers said they were moderately to extremely concerned that payers won’t reimburse them, largely due to changing payer policies and prior authorization requirements. Revenue cycle leaders know that good claims management is the key to healthy cash flow and a strong financial foundation. However, with patient volumes growing and complex payer rules increasing, traditional claims management solutions can no longer keep up. As a result, today’s healthcare organizations are feeling the squeeze to update their claims management processes and adopt solutions that rely on automation and AI-powered analytics to better predict, prevent and process denials. Predicting and preventing denials with artificial intelligence​ Healthcare providers can stop the denial spiral before it begins by capturing accurate and complete patient data at registration. According to Experian Health data, 46% of denials are caused by missing or incorrect information. Now, many healthcare organizations are accelerating their digital transformations by implementing automation and AI tools designed to predict and prevent denials. Automation creates consistent workflows, standardizes routine tasks and reduces human errors. At the same time, AI takes claims management to the next level by predicting denials, flagging claims errors before submission and prioritizing claims that need attention. Leveraging AI solutions that form a closed-loop system can ensure clean data at registration while predicting and preventing denials. Front-end solutions Tools like Patient Access Curator automatically find and correct patient data within seconds — across eligibility, Coordination of Benefits (COB) primacy, Medicare Beneficiary Identifiers (MBI), demographics and insurance discovery. Machine learning and predictive analytics allow providers to identify and correct bad data in real time, without the need for guesswork. Ken Kubisty, VP of Revenue Cycle at Exact Sciences, shares how Patient Access Curator improved eligibility processes, reduced errors and more. Back-end solutions Experian Health’s AI Advantage uses AI and machine learning to predict and prevent denials. AI Advantage not only predicts claim outcomes mid-cycle, but pushes urgent tasks to the front of the queue — allowing staff to prioritize the claims that matter most financially. Extending the automation advantage To minimize denials and delays, providers can look to implement automation and artificial intelligence across the entire claims ecosystem. For instance, Patient Access Curator and AI Advantage integrate seamlessly with solutions that manage the entire claims cycle, like Experian Health’s ClaimSource® — using real-time insights generated by ClaimSource to detect patterns and predict future payer behavior. Additionally, tools like Claim Scrubber can automate the claim scrubbing process — reducing potential errors, administrative burden and the need for costly reworks. Organizations can also add a denials workflow manager to automate and optimize the denial management portion of the claims cycle, improve staff productivity and speed up reimbursement. Artificial intelligence for claims management ​FAQs Want to learn more about how Experian Health’s AI tools can help reduce and prevent claim denials? Consider these commonly asked questions. What is AI Advantage, and how does it help with healthcare claims management? AI Advantage works in two stages of claims management, with two offerings: Predictive Denials and Denial Triage. In stage one, Predictive Denials uses AI and machine learning to look for patterns in payer adjudications and identify undocumented rules that could result in new denials. This solution also flags claims with a high potential of denial, so the right specialist can intervene before claims go to payers. After a claim has been denied, AI Advantage’s stage two component uses advanced algorithms to identify and segment denials based on their potential value. What is Patient Access Curator, and how does it help reduce claim denials? Experian Health’s Patient Access Curator is a robust patient intake and verification solution designed to eliminate errors that often result in denials, such as missing or incorrect information. Through AI and robotic process automation, Patient Access Curator automatically checks and verifies patient demographic information, insurance details, eligibility and more — reducing claim denial rates and administrative burden. How can AI Advantage and Patient Access Curator work together? Patient Access Curator and AI Advantage form a closed-loop system that offers healthcare organizations a smarter, faster and more scalable way to reduce denials and increase reimbursements while reducing administrative burden on staff. What are real-world results from using these ​solutions? Case study: Experian Health and Exact Sciences See how Exact Sciences used Patient Access Curator to reduce denials by 50% and add $100 million to their bottom line in six months. Case study: Experian Health and Schneck Medical Center See how Schneck Medical Center used AI Advantage to achieve a 4.6% average monthly decrease in denials. The bottom line: Providers can reduce claim denials with AI Leveraging artificial intelligence for claims management can improve the overall efficiency and accuracy of healthcare claims processing — leading to fewer denials and a more seamless patient experience. Instead of waiting for denials to occur before taking remedial action, healthcare organizations can stay a step ahead with claims management solutions that utilize AI and automation. These tools can help proactively detect errors and diagnose claims process weaknesses for a healthier revenue cycle. As Jason Considine, President at Experian Health, recently shared: “With the power of AI and predictive intelligence, we’re no longer waiting for denials to happen; we’re helping providers proactively prevent them. Tools like Experian Health’s Patient Access Curator and AI Advantage allow healthcare organizations to identify issues at the point of registration and throughout the revenue cycle, so teams can focus on care, not corrections. It’s about working smarter, reducing risk and protecting ​​revenue.” Find out more about how Experian Health’s AI-powered claims management solutions help healthcare providers improve reimbursement rates and reduce denials. Learn more Contact us

Over the past two decades, U.S. hospitals have absorbed nearly $745 billion in uncompensated care, according to the American Hospital Association. This burden continues to grow as hospitals struggle to verify active insurance. The task is made harder by patients frequently changing jobs, relocating and moving through a fragmented payer system that providers must track and interpret. The result? Missed billing opportunities, delayed payments and unnecessary write-offs threaten not only the hospital's financial stability, but also their ability to provide care to their communities.  Now, the newly enacted "One Big Beautiful Bill Act" adds even more pressure. With sweeping Medicaid cuts and stricter eligibility rules, millions of Americans could lose coverage — and hospitals may face a sharp rise in uncompensated care. Key provisions include:  More frequent eligibility reviews (every six months instead of annually) Higher out-of-pocket costs (up to $35 per doctor visit) New limits on state Medicaid funding (including bans on provider taxes) According to the Congressional Budget Office, an estimated 11.8 million people could lose Medicaid coverage by 2034.  These changes shift more financial responsibility to hospitals and patients.   But the impact isn't just financial. For patients, undetected coverage can lead to surprise bills, postponed treatment, or even collections, all of which erode trust in the healthcare system. Vulnerable populations, particularly those affected by the latest Medicaid changes, are at the greatest risk of falling through the cracks.   Hospitals are committed to serving their communities, including those who may not be able to afford to pay. To do this, they must recover every dollar they're entitled to. That means identifying coverage wherever it exists, even when it’s hidden, forgotten or misclassified.   That’s where Coverage Discovery comes in. Experian Health's solution uses proprietary data and advanced machine learning to identify unknown or forgotten insurance coverage across the entire revenue cycle — before, during, and after care. Unlike traditional eligibility checks, Coverage Discovery goes deeper. It scans commercial, government and third-party payers in real time; it uncovers primary, secondary and even tertiary coverage that might otherwise go unnoticed. This proactive approach helps providers bill the right payer the first time, which reduces denials, accelerates reimbursements, and minimizes bad debt.  Coverage Discovery identified over $60 billion in insurance coverage across 45+ million unique patient cases in 2024 alone, turning missed opportunities into paid claims. In a time of uncertainty, clarity is essential. Coverage Discovery empowers providers to take control of the coverage gap — not just react to it. By surfacing hidden coverage early and often, hospitals can protect their financial health while improving the patient experience.  Here's how it all comes together:  Learn more Contact us

For patient access leaders at large healthcare organizations, the pressure is mounting and has been building for some time. Healthcare claim denials are climbing. Staffing is stretched, and the tools healthcare organizations have relied on for years are no longer enough. But what if providers could stop denials before they start? Welcome to the new era of denial prevention in healthcare, powered by predictive intelligence. Experian Health's innovative artificial intelligence (AI) solutions, Patient Access Curator and AI Advantage™, were designed to help organizations prevent denials before they occur. Explore how Experian Health is reshaping the way health systems manage Coordination of Benefits. Learn how automation and AI are eliminating manual errors, reducing denials and unlocking millions in recoverable revenue. Watch now > The denial spiral explained: A systemic challenge in revenue cycle management  Claim denials aren't just a back-end billing issue. They're a symptom of upstream breakdowns—often rooted in inaccurate or incomplete patient data at registration. According to Experian Health's 2024 State of Claims Survey, 46% of denials are caused by missing or incorrect information. And the cost of reworking a denied claim? $25 for providers and $181 for hospitals. The result? A denial spiral that drains resources, delays reimbursements, and frustrates patients and staff alike.  Why Epic users are especially vulnerable While Epic is a powerful EHR platform, many Epic-based organizations still rely on staff to make complex decisions at registration. Questions like: Is this coverage primary? Should discovery be run? Is this data accurate? ...are often left to frontline staff. This guesswork leads to inconsistent outcomes—and denials. What's needed is a layer of predictive intelligence that works within Epic to automate and correct data before it becomes a problem.  How Patient Access Curator fixes registration errors Patient Access Curator is that layer. Patient Access Curator is an all-in-one solution that automatically finds and corrects patient data across eligibility, Coordination of Benefits (COB) primacy, Medicare Beneficiary Identifiers (MBI), demographics and insurance discovery—within seconds. It integrates directly into Epic workflows, eliminating the need for staff to toggle between systems or make judgment calls on the fly. Instead of relying on registrars to catch every error, Patient Access Curator uses machine learning and predictive analytics to: - Identify and correct bad data in real time - Return comprehensive coverage directly into Epic - Reduce denials, write-offs, and vendor fees - Improve staff morale by removing administrative burden As one early-adopting Patient Access Curator client puts it: "If your current workflow still depends on frontline decisions, you're not just risking denials—you're building them in."  Predictive intelligence in healthcare: AI Advantage at work While Patient Access Curator fixes the front end, AI Advantage tackles the middle of the revenue cycle, where claims are scrubbed, edited, and submitted. At Schneck Medical Center, AI Advantage helped reduce denials by 4.6% per month and cut denial resolution time by 4x. The tool flags high-risk claims before submission and routes them to the right biller for correction. It also triages denials based on the likelihood of reimbursement, so staff can focus on the claims that matter most. Together, Patient Access Curator and AI Advantage form a closed-loop system: - Patient Access Curator ensures clean data at registration - AI Advantage predicts and prevents denials mid-cycle - Both tools integrate seamlessly with Epic and ClaimSource®  Why predictive denial prevention matters for patient access leaders  By implementing denial management technology and predictive intelligence, healthcare teams aren't just managing workflows; they're managing risk. Every inaccurate field, every missed coverage, every manual decision is a potential denial. Patient Access Curator and AI Advantage remove that risk by replacing guesswork with certainty. And the benefits go beyond revenue: - Fewer denials mean fewer patient callbacks and less frustration - Cleaner data means faster reimbursements and fewer write-offs - Automation means staff can focus on patients, not paperwork As Jason Considine, President at Experian Health, recently shared: "Our mission is to simplify healthcare. That starts by getting it right the first time, before a claim is ever submitted. With the power of AI and predictive intelligence, we're no longer waiting for denials to happen; we're helping providers proactively prevent them. Tools like Patient Access Curator and AI Advantage allow healthcare organizations to identify issues at the point of registration and throughout the revenue cycle, so teams can focus on care, not corrections. It's about working smarter, reducing risk and protecting revenue."  Denial prevention checklist: Preparing patient access teams for predictive denial prevention  Denial prevention is here, but what if billing teams aren't quite ready? To move toward a predictive denial prevention strategy, healthcare organizations can invest in the following five areas:   Audit front-end workflowsMap out every step from patient registration to claim submission. Identify where manual decisions are being made—especially around eligibility, COB, and insurance discovery. Ask: "Where are we relying on staff judgment instead of system intelligence?" Train staff on data quality awarenessReinforce the impact of inaccurate or incomplete data on downstream denials. Use real examples to show how a single missed field can lead to rework, write-offs, or patient frustration. Introduce the concept of "first-touch accuracy" as a team-wide goal. Evaluate Epic integration readinessAssess whether current Epic environments are configured to support automation tools like Patient Access Curator. Work with IT to assess whether the current setup allows for real-time data correction and coverage updates. Confirm that teams understand how new tools will integrate into their existing workflows, not replace them. Establish a denial prevention task forceBring together leaders from patient access, billing, IT and revenue cycle to align on goals. Assign ownership for key metrics like clean claim rate, denial rate, and registration accuracy. Use this group to pilot new tools like Patient Access Curator and AI Advantage and gather feedback from frontline users. Communicate the "Why" behind the changeFrame automation as a way to reduce burnout, not replace jobs. Highlight how tools like Patient Access Curator eliminate guesswork and free up staff to focus on patient care. Share success stories from peers (like Schneck Medical Center) to build confidence and momentum. The bottom line: Strategic denial prevention is the future Denial management is reactive. Denial prevention is strategic. For healthcare organizations using Epic, Patient Access Curator and AI Advantage offer a smarter, faster and more scalable way to increase reimbursements and improve the patient experience. Learn more about how Experian Health can help protect revenue, reduce staff burdens and reduce claim denials—starting at the first touchpoint. Learn more Contact us

Key takeaways: Changes to Medicaid, Medicare and the Affordable Care Act provisions in H.R. 1 are expected to increase financial pressure across the healthcare system. Hospitals could face higher uncompensated care costs and a growing administrative burden as millions lose coverage and payer rules grow more complex. Revenue cycle leaders should focus on strengthening eligibility checks, improving claims accuracy, and automating operations to remain financially resilient. On July 4, the budget reconciliation bill known as the “One Big Beautiful Bill Act” was signed into law, introducing sweeping changes to Medicaid, Medicare and Affordable Care Act (ACA) marketplace plans. At almost 900 pages, H.R. 1 sets out new eligibility, coverage and funding rules that will reshape how hospitals are reimbursed. This article explains what revenue cycle leaders need to know about the reforms and offers practical strategies for maintaining financial stability. Understanding the healthcare implications of H.R. 1 The healthcare provisions in H.R. 1 reflect a broader push by lawmakers to contain federal spending and return more control to states. While the reforms are framed as efforts to improve fiscal sustainability, they also introduce new financial risks for hospitals, particularly those serving low-income and high-utilization populations. How does the Act affect Medicaid? Enrollment H.R. 1 makes major changes to Medicaid enrollment, with direct implications for hospital revenue and patient coverage. Starting in 2027, states will be required to run automated eligibility checks every six months for Medicaid expansion adults, and cross-check against federal databases to remove ineligible or deceased enrollees. The Act pauses implementation of a federal rule related to streamlining enrollment in Medicaid and the Children’s Health Insurance Program. Eligibility Eligibility rules are also changing. A new community engagement requirement will require some enrollees to demonstrate that they work, volunteer, or are in education for at least 80 hours a month, unless exempted. While aimed at reducing fraud, waste and misuse, changes to eligibility and enrollment could result in more patients losing coverage and increase churn and care gaps – particularly among vulnerable populations. Uncertainty around citizenship status could deter patients from seeking care, and even affect staffing in hospitals that serve immigrant communities. Cost-sharing and funding To ensure beneficiaries have a financial stake in their care, the law introduces cost-sharing requirements for some enrollees. Providers will need to be ready to help patients understand their costs and adjust collections workflows accordingly. There are also new financial penalties for states that fail to recover overpayments, and limits on how provider taxes and supplemental payments can be used to boost federal matching funds. Over time, these provisions could constrain how hospitals are reimbursed for Medicaid services, especially in non-expansion states. How does the Act affect Medicare? For Medicare, the Act offers some short-term financial relief along with longer-term reductions. Outpatient providers will see a 2.5% increase to the Medicare Physician Fee Schedule in 2026, partially offsetting inflation and COVID-related losses. However, spending cuts of 4% per year are projected to reduce Medicare funding by more than $500 billion over eight years, beginning in 2026. In addition, the law brings Medicare eligibility in closer alignment to Medicaid, by restricting access for individuals without verified lawful status or sufficient residency history. It also delays until 2035 a rule that would have made it easier for low-income beneficiaries to enroll in Medicare Savings Programs. The Congressional Budget Office (CBO) estimates that this means 1.38 million fewer beneficiaries  will be covered by MSPs. How does the Act affect the ACA? One of the most immediate concerns for hospitals involves the end of enhanced premium subsidies for low-income ACA marketplace plan enrollees. Unless Congress steps in, these will expire at the end of 2025, making coverage less affordable for many. This comes as insurers prepare to increase premiums by an average of 15% in 2026, the most significant rise since 2018. H.R. 1 also modifies eligibility and repayment rules around subsidies. Subsidies will no longer be available to individuals disenrolled from Medicaid due to immigration status. Starting in 2027, most enrollees in marketplace plans will need to verify their eligibility for premium tax credits each year, effectively ending automatic re-enrollment. Without these subsidies, over 4 million people are likely to be uninsured in 2034. For hospitals, this means more self-pay patients, delayed collections and higher uncompensated care, especially in areas with large working-age populations. Financial risks: Medicaid cuts and rising uncompensated care The CBO projects that over 10 million people could lose health coverage by 2034 due to combined Medicaid and ACA reforms. This is a major financial risk for hospitals, particularly safety-net and rural providers. The Center for American Progress suggests that uncompensated care costs could increase by at least $36 billion by 2034 – a figure that will be especially painful in the context of reduced federal funding. Some newly uninsured patients may not seek alternative coverage, potentially leading to higher emergency department use. Those with ongoing health needs are more likely to find new coverage, but hospitals could still see a smaller insured population overall, and it could well be one that is older, sicker and more expensive to treat. Revenue cycle teams should prepare for an increase in self-pay volumes and greater demand for charity care and financial assistance. Organizations in high-Medicaid regions may need to reassess cost estimation tools, financial assistance screening and collections workflows to manage the effects. Strengthening front-end access and eligibility workflows Jason Considine, President at Experian Health, says that providers can be proactive in ensuring their revenue cycle operations are ready to adapt and scale, if and when the time comes: “It’s an uncertain time. However, as we wait to see how the changes to coverage and reimbursement play out in practice, providers aren’t just looking for predictions. They need actionable strategies. Strengthening front-end eligibility and financial clearance processes is one of the most immediate ways to reduce risk and support patients through coverage transitions. Experian Health helps organizations do that by offering automated tools that uncover hidden coverage, verify eligibility in real time, and provide clear, accurate patient estimates.” Here are a few examples: Getting eligibility right. Patient Access Curator uses artificial intelligence to run multiple data checks at once, covering eligibility verification, coordination of benefits, Medicare Beneficiary Identifiers, demographics and coverage discovery. Minimizing the risk of uncompensated care. Patient Financial Clearance uses real-time data to identify patients who may qualify for charity care and recommends suitable payment plan options, while minimizing manual work for staff. Helping patients figure out their financial obligations. Patient Payment Estimates draws on real-time data, including insurance coverage, payer contract terms and provider pricing, to give patients an accurate breakdown of their treatment costs. This improves transparency and reduces the risk of missed payments. Case study: Experian Health and Exact Sciences See how Exact Sciences added $100 million to their bottom line in just two quarters with Patient Access Curator. Optimizing claims and collections in a tighter reimbursement environment In addition to strengthening front-end processes, providers need to ensure their back-end operations are ready to handle the ups and downs. Denied claims are already a major challenge for providers: in Experian Health’s 2024 State of Claims survey, 73% said denials are increasing and 77% report more frequent payer policy changes. More than half have seen a rise in claims errors, highlighting an opportunity for improvement. As automation and AI continue to advance, healthcare providers have a chance to improve claims management and reduce denials. Embracing these solutions can reduce the costly burden of reworking claim denials and improve cash flow. If claims workflows are already struggling, providers can’t afford any extra friction. However, the H.R. 1 reforms will likely increase the administrative burden and make timely reimbursement even harder to secure. This makes digital transformation increasingly urgent. Some priorities to tackle with automation and analytics include: Improving first-pass claim accuracy.  AI Advantage™– Predictive Denials  uses artificial intelligence, machine learning and predictive analytics to scan claims before they are submitted to root out errors and flag high-risk submissions so they can be corrected. It analyzes historical payment data and real-time payer behavior to determine whether a claim is likely to be rejected, so staff can work faster and more efficiently to increase clean claim rates. Streamlining claims management. ClaimSource® helps providers manage the entire claim cycle from a single application. Voted Best in KLAS for Claims Management and Clearinghouse for the last two years, the platform automates claim submission to reduce manual work and support cleaner submissions. It performs customizable edits, formats and submits claims, and allows staff to create custom work queues for greater efficiency. Using data to optimize collections. Collections Optimization Manager uses data-driven insights to help revenue cycle management (RCM) teams focus on the right accounts and collect more, faster. By segmenting patients based on their propensity to pay and screening out accounts unlikely to yield returns (such as deceased, bankrupt or charity accounts) the tool helps reduce the cost to collect and saves valuable staff time. Case study: Experian Health and Weill Cornell See how Weill Cornell increased collections by $15 million with Collections Optimization Manager. Preparing for volatility with scalable technology Revenue cycle teams can’t control policy changes or budget decisions, but they can control the systems that keep their operations running. Experian Health’s end-to-end revenue cycle solutions are designed to support this kind of operational resilience. From coverage discovery to claims analytics, scalable platforms give providers the flexibility to respond quickly to financial disruptions using consistent and familiar technology. “When so much is out of your hands, the smartest move is to focus on what you can control. Scalable tech gives RCM leaders that control, so when payer rules shift or self-pay volumes spike, they’re ready to respond without slowing down,” says Considine. “It also helps them stay ready for compliance shifts and respond faster to regulatory changes without overhauling their workflows.” Blog: Revenue cycle management checklist - improve experience and profits Get a practical checklist to optimize patient access, collections and claims management, while building a resilient and patient-centered revenue cycle. Readiness today protects financial resilience tomorrow The H.R. 1 bill has introduced significant changes across Medicaid, Medicare and the Affordable Care Act. New eligibility requirements, adjustments to reimbursement formulas, reduced subsidies and greater administrative complexity are all expected to influence how patients access coverage and how care is financed moving forward. While the long-term impact will vary by market and patient population, disruption is coming. Hospitals and health systems that rely on outdated workflows or fragmented technology will face growing challenges in managing changing coverage patterns and rising uncompensated care. As the specific effects of the “One Big Beautiful Bill” become clearer, revenue cycle leaders will be tasked with making fast choices under pressure. How will coverage changes affect patient behavior? What happens to reimbursement if eligibility gaps widen? The focus won’t just be on protecting revenue, but also on supporting patients who may be confused or anxious about what the new rules mean for them. The ability to track changes and adapt accordingly will be a competitive advantage for providers looking to stay ahead. Find out how Experian Health can help hospitals prepare for reforms by modernizing revenue cycle operations and reducing exposure to revenue loss. Learn more Contact us

Manual prior authorization workflows represent one of the most tedious and expensive aspects of the healthcare revenue cycle. However, despite access to automated prior authorization software, only 31% of providers use electronic prior authorizations, according to the Council for Affordable Quality Healthcare (CAQH). The CAQH predicts that providers who switch to automated prior authorization software could not only gain back valuable staff time, but also see significant cost savings. What is prior authorization and why is it important? In healthcare, prior authorizations are when providers and payers decide in advance if a patient's insurance plan will pay for a specific treatment. Prior authorizations are crucial to reimbursements and keeping revenue cycles on track. Providers that offer services without prior authorization are unlikely to receive reimbursement from the patient's insurer. This can result in unpaid medical bills, leaving billing teams chasing patient collections or writing off bad debt. During the prior authorization process, providers submit a rationale for a proposed treatment to the payer. The request is approved or denied based on certain criteria, including payer policies and medical necessity. The payer may reject a prior authorization request if the treatment or service isn't covered under the patient's insurance plan, if it's not considered medically necessary or if a more affordable alternative is available. Simple paperwork errors, like missed deadlines or incomplete documentation when submitting a prior authorization, may also result in a denial. Challenges of manual prior authorization processes Despite the importance of prior authorizations in the revenue cycle, tedious manual prior authorization processes present challenges for many healthcare providers. Some of the key obstacles providers face using manual prior authorization include: Heavy administrative burden Healthcare providers spend a significant amount of time starting, completing and revising prior authorization paperwork. An AMA survey found that 86% of physicians say prior authorization has increased healthcare resource usage. At the same time, additional AMA data reports that providers spend around 13 hours working on 39 prior authorizations each week, and nearly one-third of providers report that these prior authorization requests usually end up being denied. Changing payer policies Keeping up with multiple payers and ever-evolving payer policies adds strain on staff and ultimately results in prior authorization denials. Changes are often unannounced, making it hard for providers to stay on top of updates. As a result, prior authorization submissions aren’t always accurate and may be based on outdated rules. This can lead to instant rejection and wasted time correcting and resubmitting requests. Inefficient workflows Prior authorization requirements can be complicated, especially when providers are juggling different payers, standards and service lines. Coping with these complexities often puts strain on manual systems, especially when multiple staff and notetaking methods are involved. Staff members may each get different pieces of information from payer websites (or over the phone) and not have the ability to benefit from their shared knowledge efficiently. Navigating communication hurdles and rapid payer information changes can result in workflow inefficiencies that snowball quickly. How prior authorization software can improve efficiency Replacing manual prior authorization processes with automated prior authorization software can help providers improve efficiency. Here are some key ways providers benefit from automated prior authorization solutions, like Experian Health's Authorizations. Reduces manual interventions: This solution limits guesswork, human errors, and misinterpretations by automating data originating from the EMRs. Automation saves staff time and energy and prevents frustration. Stays current with latest payer policies: The prior authorization system stays up-to-date with the latest regulations and payer requirements. Automatic updates provide staff with the most current information, eliminating the need for staff to visit multiple payer websites or cross-check data by hand. Provides real-time updates: Providers can promptly clear authorizations for service by proactively identifying authorization status as pending, denied or authorized. This allows physicians to make timely treatment plans and for patients to avoid disruptions in care. Reduces risk of denials: Through automation, electronic prior authorization software ensures the accuracy and completeness of submissions by automatically checking with payers and vendors to validate that the authorization is on file. Payers and providers also get a shared view of account information, reducing the need for prolonged discussions about the status of authorization and rework requests. Key features to look for in prior authorization software When implementing prior authorization software, look for a solution that offers a wide range of features to automate and streamline the prior authorization process. Experian Health's prior authorization solution, Authorizations, for instance, offers healthcare providers the following key features: Real-time knowledgebase: Access to up-to-date prior authorization requirements and criteria in the National Payer Rulesets Submissions support: Removes guesswork and directs users to the correct payer portal based on procedure Automated inquiries: Automates the prior authorization payer inquiry process Enhanced workflow: Dynamic work queues display status and guide users through next steps Postback: Allows users to easily send authorization status, number and validity dates to health information systems (HIS) and practice management systems (PMS) Image storage: Receives and securely stores payer responses in an integrated document imaging system Reconciliation: Provides insights into authorization variations and helps resolve them, so staff can take proactive steps to prevent denials and appeals Integration with electronic health records and billing systems: Why it matters Providers often choose a prior authorization platform that seamlessly integrates with existing Electronic Health Records (EHR) and billing systems for maximum efficiency. Solutions like Experian Health's automated prior authorization management tool, Authorizations, easily adapt to existing processes. This eliminates the need for a complete workflow overhaul and minimizes the learning curve for staff. Embracing prior authorization software for a more efficient revenue cycle Revenue cycle leaders who implement prior authorization automation strategies could see significant savings – $494 million annually as an industry, according to CAQH data.  Claims and revenue management processes are often complex and outdated, costing healthcare organizations time and money. High denial rates and slow reimbursements can hurt cash flow and get in the way of financial stability. Automating prior authorization can reduce claim denials, speed up reimbursements and improve the bottom line. Learn more about how Experian Health's electronic prior authorization software, Authorizations, uses automation to achieve greater consistency and efficiency for healthcare organizations. Learn more Contact us