Key takeaways: Healthcare organizations are facing growing levels of bad debt and a sharp decline in collections. Propensity-to-pay models that utilize machine learning and robust data offer insight into a patient's likelihood to pay and allow staff to focus their collections efforts where they matter most. In 2024, Experian Health clients that implemented Collections Optimization Manager saw a 10:1 ROI. Some clients, like Weill Cornell Medicine, have seen up to $15 million in recoveries. Healthcare organizations are facing a sharp decline in collections and an increase in bad ​​debt. Rising self-pay costs and more patients struggling to afford their medical bills are contributing factors. Inefficient collections practices, reliance on third-party agencies that don't utilize propensity to-pay scores and manual processes are also key contributors to this growing market problem. Providers who adopt propensity-to-pay models that use data and automation to forecast the likelihood of payment often see both improved revenue recovery and patient satisfaction. Here's what to know about propensity-to-pay collections strategies in healthcare. Why propensity to pay matters in healthcare collections "Propensity to pay" is a data-driven model that identifies patient populations with the greatest likelihood of paying, to enhance existing collection strategies. When billing teams better understand a patient's propensity to pay, they can easily prioritize outreach and allocate collections resources effectively. This eases their workload, as they can focus their efforts where they'll have the greatest impact, and on accounts with the highest probability of payment. Keeping more collections in-house also reduces the reliance on expensive third-party agencies, while eliminating wasted effort on low-yield tasks – like repeated phone calls or mailed statements to accounts unlikely to pay. The need to adopt propensity-to-pay models has grown in recent years as patient volumes and the cost of care continue to grow. In the last 20 years, U.S. hospitals have absorbed nearly $745 billion in uncompensated care, according to American Hospital Association data.American Hospital Association Rising healthcare costs and the newly enacted "One Big Beautiful Bill Act" are expected to shift even more financial responsibility to both hospitals and ​​patients. Unfortunately, many organizations still rely on inefficient collections processes, third-party agencies and medical billing practices that lack propensity-to-pay insights. The result? Disruptions to the entire revenue cycle, including lost patient revenue, wasted resource hours, increased costs to collect, and high vendor costs. Using outdated collections strategies also contributes to patient dissatisfaction and churn, causing even more revenue leaks. Why healthcare providers need propensity-to-pay analytics Limited staff capacity and high volumes of self-pay accounts further compound collections challenges for organizations that have yet to adopt propensity-to-pay analytics. As collections timelines drag out, providers can be left with cash flow issues, revenue losses and bad debt. This ultimately disrupts the revenue cycle and affects the quality of patient care – and the entire patient experience. By leveraging propensity-to-pay analytics, revenue cycle leaders can boost revenue cycle predictability and streamline collections efforts. Listen in as Weill Cornell Medicine and Experian Health discuss how a smarter collections strategy delivered $15M in recoveries – and how you can do the same. This on-demand webinar shows how to move faster, work smarter and collect more, without adding headcount. Watch now > How propensity-to-pay models work in practice Propensity-to-pay models screen and segment patient accounts based on the likelihood of payment. Segmented accounts receive a propensity-to-pay score – from 1 to 5, with 1 being the highest likelihood to pay — and are then transferred to appropriate reconciliation channels. Experian Health's solution, Collections Optimization Manager, leverages machine learning, predictive analytics and data sources – like credit, behaviour and demographics – to identify which patient accounts have the highest likelihood to pay. It also automatically screens patient data for deceased, bankruptcy, Medicaid and ​​charity. Patient accounts are then sorted into pay groups through data-driven segmentation. This allows busy collections staff to quickly clean up accounts receivable and put their focus where it matters most – patient accounts with the strongest chance of paying their bill. With a clear picture of a patient's financial situation, healthcare organizations can improve patient communication and further boost collections efforts to maximize revenue. High-propensity accounts may receive light-touch reminders, like less frequent bill reminders. At the same time, alternative financial assistance, such as charity care or payment plans, can be made available automatically to low-propensity patients. Benefits of using propensity-to-pay models Propensity-to-pay models, like Experian Health's Collections Optimization Manager solution, offer numerous benefits to organizations that strengthen the revenue cycle. Higher collections rates: Using a propensity-to-pay model makes AR more manageable, especially for high-patient-volume organizations. Complimentary tools, like Experian Health's PatientDial and PatientText, easily send self-pay options via voice or text message, boosting patient engagement and building trust. Reduced bad debt: Propensity-to-pay models help identify patients with a low likelihood of paying their medical bills. Lower collections costs: Chasing payments on accounts that are deceased, bankrupt, or eligible for Medicaid or charity wastes valuable resources. With propensity-to-pay models, busy staff can efficiently work on high-yield accounts in-house, reducing the number of accounts that need to go to third-party vendors. Faster cash flow: Prioritize likely-to-pay patients early and shorten payment cycles, which can improve revenue cycle predictability.  On-demand webinar: Boost self-pay collections – Novant Health & Cone Health’s 7:1 ROI & $14M patient collections success Hear how Novant Health and Cone Health achieved 7:1 ROI and $14 million in patient collections with Collections Optimization Manager.  Case study: How Wooster Community Hospital collected $3.8M in patient balances with Collections Optimization Manager Read more about how automated collections strategies helped Wooster Community Hospital achieve a $3.8 million increase in patient payments. Implementing propensity-to-pay analytics: Best practices Healthcare organizations that implement propensity-to-pay analytics should consider the following best practices:  Choose the right partner. Look for a technology partner, like Experian Health, with extensive data assets and healthcare expertise. Automate patient communication. Reduce overhead and increase collections efforts with automated patient communication strategies. Ensure alignment with legacy technology. For real-time accuracy, choose a solution that integrates seamlessly with existing EHR and billing systems. Train billing staff. Provide comprehensive training to billing and collections teams on propensity-to-pay scores and how to communicate payment options with empathy. Automate the agency management. Reduce the manual workload of auditing agency remittances by automating the reconciliation process. Monitoring patient accounts. Look for a solution that regularly scans for changes or updates in a patient's ability to pay or contact information. Track performance. Monitor key performance indicators to fine-tune the collections process over time and improve forecasting. How Experian Health's solutions support better collections Changing longstanding collections practices is often a significant investment. Yet, the cost of inaction is often greater. Experian Health's Collections Optimization Manager uses propensity-to-pay models, driven by machine learning, and data-driven workflows to help healthcare providers improve patient collections. Our comprehensive industry-leading solution offers a smarter and faster way to collect patient payments, and Experian Health's experienced consultants are there every step of the way, as collections needs shift. Learn more about how Experian Health's data-driven patient collections optimization solution helps revenue cycle management staff collect more patient balances. 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: Experian Health’s State of Claims 2025 report is out now, detailing providers’ views on claims management and how these have changed since the survey began in 2022. Claim denials are still on the rise, causing providers to find faster and more efficient ways to submit clean claims the first time. When it comes to solutions, optimism about artificial intelligence (AI) is high, but uptake remains surprisingly low. AI-powered tools like Patient Access Curator™ and AI Advantage™ can help healthcare providers reduce claim denials while optimizing the claims management process. According to Experian Health’s State of Claims 2025 report, claim denials continue to negatively impact America’s healthcare providers. This quantitative survey of 250 healthcare professionals, carried out in June and July 2025, reveals providers’ concerns about rising denial rates, staffing shortages and uncertainty over whether payers or patients will ultimately pay. The findings show that providers are open to new claims processing and denial reduction solutions. However, while providers are enthusiastic about artificial intelligence's ability to ease the squeeze, only a small fraction are actually using it. This article highlights a few key takeaways from healthcare providers' statements about the current challenges in claims management and the factors that contribute to their responses. NEW: State of Claims 2025 Report Download the State of Claims 2025 report to see the full findings. Takeaway 1: Claim denials are on the rise again This year’s survey confirms what providers have been seeing for several years: claim denials are not letting up. In 2022, 30% reported that at least 10% of their claims were denied. By 2024, the figure had grown to 38%. Now, in 2025, 41% of providers say their claims are denied over 10% of the time. If this trend continues, how much further could denial rates climb? Claim denials are becoming a growing part of everyday operations, demanding more time, staff and resources. Margins that are already under pressure are strained further by missed reimbursements. And when insurers don’t pay, more of the bill falls to patients, many of whom are already struggling to manage medical costs. Half of respondents said they are “very or extremely concerned” about patients’ ability to pay, up six percentage points from last year. For many organizations, the question is not whether denials will continue, but how best to prevent them before the financial burden worsens. Blog: Denial prevention - Why manage denials when you can prevent them? Read more about how our claims management solutions help providers build effective denial prevention strategies and reduce lost revenue. Takeaway 2: How bad data leads to more healthcare claim denials The report lists several of the top triggers for denials, but inaccurate and incomplete data continue to stand out. More than half of providers (54%) say claim errors are increasing, and nearly seven in ten (68%) report that submitting clean claims is more challenging than it was a year ago. Many of these errors originate at registration. Incomplete or inaccurate information collected during check-in is now the third most common cause of denials, with 26% of respondents saying that at least one in ten denials at their organization can be traced back to intake errors. Every mistake sends ripples downstream, leading to costly rework, avoidable payment delays and unnecessary patient stress. Tightening up patient access processes and accurate data collection is one of the best things providers can do to curb denials. With that in mind, Experian Health’s Patient Access Curator is designed to help providers capture accurate data the first time. Using AI and machine learning, it consolidates eligibility checks, coordination of benefits, Medicare Beneficiary Identifier (MBI) verification, demographics, insurance coverage and financial status into a single workflow. This allows providers to: Quickly collect accurate patient information upfront Eliminate the need to re-run eligibility checks, which now take more than 10 minutes for over half of providers Reduce manual data entry errors that lead to downstream denials Free up staff time for higher-value tasks Case study: Experian Health & OhioHealth See how OhioHealth cut denials by 42% with Patient Access Curator and solved claim errors at the source. Takeaway 3: An AI paradox in healthcare claims: High optimism, low adoption Patient Access Curator is a great example of how AI can help address the data problems behind denials. But clean data alone isn’t enough. Errors and risks still emerge mid-cycle. Here, AI Advantage offers another application for AI, using predictive analytics to identify high-risk claims before submission and routing them for correction. It also triages denials based on the likelihood of reimbursement, so staff don’t lose time on unproductive rework. 69% of healthcare providers who use AI say that AI solutions have reduced denials and/or increased the success of resubmissions.State of Claims 2025 report | Experian Health The survey shows many providers are enthusiastic about AI's potential: 67% believe AI can improve the claims process, and 62% are very confident in their understanding of how AI differs from automation and machine learning, up sharply from just 28% in 2024. Despite this optimism, adoption is surprisingly low. Only 14% of providers are currently using AI to reduce denials. The survey suggests that even though the majority of AI adopters report fewer denials and more successful resubmissions, fear of the unknown seems to be slowing progress. Blog: Leveraging artificial intelligence for claims management Read more about how our AI-powered claims management solutions help healthcare providers improve reimbursement rates and reduce denials. Takeaway 4: Tech upgrades aren’t enough without integration Even if they remain on the fence about AI, providers are still moving to modernize claims management. Only 56% believe their current technology is sufficient to handle revenue cycle demands, a major drop from 77% in 2022. This explains why 55% are willing to completely replace their existing claims management platform if presented with a compelling return on investment. Much of the frustration comes from fragmentation. Nearly eight in ten providers say their organizations still rely on multiple solutions to collect the information needed for a claim submission. Switching between systems slows down intake, creates duplication and increases the risk of errors that feed directly into denials. An integrated solution like Patient Access Curator solves this problem by replacing a patchwork of tools with a single platform that manages intake and eligibility in one workflow. Information is captured in one place, reducing the duplication and errors that are inevitable when data is entered into multiple databases. Extending this with AI Advantage links front-end accuracy with back-office intelligence, giving providers a connected denial-prevention system rather than stitching together isolated fixes. With fewer tools to log into, staff can work more efficiently and focus on submitting cleaner claims. 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 > Closing the technology gaps in claims management to prevent denials The 2025 State of Claims report clearly shows that denials remain a persistent and costly problem for healthcare organizations. An overwhelming majority say that reducing them is a top organizational priority. Beyond the financial concerns, the survey reveals a system still held back by data errors, fragmented technology and delays. At the same time, there are hints of cautious optimism. Last year, many providers felt in the dark about AI and machine learning. This year’s survey shows that awareness of these technologies has grown considerably, even if adoption is still early. As the report sheds light on how leaders are weighing investments in new technology, the question now is whether providers can turn growing confidence in AI into action that delivers the results they need. To see the full picture of where claims management stands today, and where it could go next, download the State of Claims 2025 report. Download now 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

“Registrars used to wonder, ‘Do I run Coordination of Benefits? Which insurance is primary?’ Now Patient Access Curator does all that work and removes the guess work, and it does it in under 20 seconds.”Randy Gabel, Senior Director of Revenue Cycle at OhioHealth Challenge OhioHealth faced rising denial rates and inconsistent insurance discovery. Registrars relied heavily on what patients told them at check-in, without knowing if that information was complete or current. Forced to make judgment calls about whether to run Coordination of Benefits (COB) or check for Medicare Beneficiary Identifiers (MBI), staff could do little to avoid errors and denials. Randy Gabel, Senior Director of Revenue Cycle at OhioHealth, says, "We were sending claims with the wrong insurance simply because staff didn't know what to do next." They needed a reliable solution to identify coverage upfront – without asking patients to dig out old insurance cards or involving costly contingency vendors. OhioHealth's search became more urgent when a nationwide cyberattack hit the industry in early 2024. They needed a trusted revenue cycle partner to close the gaps in claims and eligibility workflows and prevent denials from the start. Solution To strengthen front-end revenue cycle operations, OhioHealth selected Experian Health's Patient Access Curator® (PAC). This all-in-one solution uses artificial intelligence (AI) and machine learning to check eligibility, COB, MBI, demographics and insurance discovery through a single process. This solution gave staff more accurate data in real-time. Although they had not worked with Experian Health before, the OhioHealth team was immediately convinced that Patient Access Curator fit the bill. Gabel says that during the evaluation, "Patient Access Curator discovered a whopping 18% more insurance on self-pay accounts than our current vendor. No other company or product found that much." PAC fits directly into existing workflows, so OhioHealth's 800+ staff members did not have to learn a new tool or change their daily processes. And with real-time insurance discovery and auto-population of coverage data into Epic, staff no longer needed to rely on guesswork and manual data entry. The tool's ability to automatically determine primacy and remove expired coverage meant staff could submit claims with confidence. "One of the primary reasons we chose Experian and Patient Access Curator was because it makes the manual work of revenue cycle much easier on the registration teams, which in turn improves productivity, empowerment and morale," said Gabel. Outcome When Patient Access Curator went live, the effects were felt almost immediately. Registrars who once spent valuable time debating which checks to run found that PAC handled those decisions automatically, and much faster. Manual searches were no longer necessary, and the system's accuracy drastically reduced the number of errors. These front-end improvements have boosted performance throughout the revenue cycle. Clean registrations meant fewer denied claims, less manual cleanup and faster reimbursements. PAC even uncovered insurance for accounts that had already been sent to collections, helping OhioHealth reduce reliance on contingency vendors and cut avoidable bad debt. PAC continued to prove its value long after it went live. Within the first year, OhioHealth achieved: 42% reduction in overall registration/eligibility-related denials 36% decrease in COB-related denials 69% drop in termed insurance-related denials 63% fewer incorrect payer-related denials $188 million in claims unlocked by reassigning staff and improving productivity What's next? Building on this success, OhioHealth's next steps are to expand their use of PAC by launching a patient financial experience initiative. This will allow patients to complete registration themselves and find their own coverage without waiting for a staff member to become available to help. Resolving more insurance issues upfront will deliver a faster, easier and more transparent registration experience from the start. With Patient Access Curator, OhioHealth has gone from losing time and money dealing with the downstream effects of claims errors to ensuring coverage accuracy at the source – while cutting denials by almost half. Along with a better experience for staff and patients, these gains have created a more resilient revenue cycle, ready to withstand whatever unexpected changes may be in store. Find out more about how Patient Access Curator prevents claim errors before they begin, helping teams submit clean claims and reduce denials. Learn more Contact us

Key takeaways: Billing mistakes and claims delays are common when providers rely on manual patient insurance verification processes. Automated patient insurance verification can speed up eligibility checks and ensure patient insurance and billing information is accurate. Claims denial rates go down and reimbursement rates go up when providers adopt real-time insurance eligibility technology. Patient insurance verification is critical to managing healthy revenue cycles. Without a complete picture of a patient's insurance policy details—like payable benefits, deductibles and co-pay thresholds for out-of-pocket maximums—providers run the risk of non-reimbursement. Yet, many providers still rely on manual insurance verification processes that are often error-prone, resulting in high claims denial rates. Implementing patient insurance verification software helps boost both accuracy and speed, ultimately helping health organizations reduce claims denial and keep revenue cycles on track.  What is insurance verification? In healthcare, insurance verification is the process of confirming if a patient has active medical insurance coverage and finding missing health insurance. Also called an eligibility check, insurance verification typically takes place before a patient receives care, even if they are a long-time patient. During insurance verification, providers check insurance status, coverage details, benefits for medical services and billing details. To keep revenue cycles on track, providers must have the most up-to-date patient insurance information on file to maintain more accurate billing and reduce costly and time-consuming claim denials. Insurance verification also benefits patients by helping them better understand their financial responsibility so they can plan for out-of-pocket costs. Challenges of manual insurance verification processes Many healthcare organizations still rely on manual insurance verification processes to check patient insurance information. Unfortunately, running eligibility checks by hand can result in increased mistakes, a heavy administrative burden on busy staff and higher claim denial rates. Here's a closer look at some of the common challenges of manual insurance verification. Prone to errors Patients typically provide their insurance information when they register or check in for an appointment with a provider. However, this information can be outdated, incorrect or incomplete. According to Experian Health data, nearly half of providers (48%) say data collected at registration or check-in is somewhat or not accurate, and 20% of patients report encountering errors in their medical records and/or billing information. Patients may make mistakes when entering information, switch insurance coverage after filling out their paperwork or forget about secondary coverage they may have. Staff can also incorrectly input patient information from a paper form into a billing system or forget to update a patient’s file with new insurance information. Workflow bottlenecks and reduced efficiencies Staff often get bogged down correcting errors or may waste valuable time contacting patients by phone to update insurance information. Billing errors that result from mistakes made during patient insurance verification also create extra work for staff. Inaccurate insurance information may also result in patient confusion about out-of-pocket costs and disrupt care, further jamming up collections and patient scheduling for busy practices. The 2025 State of Patient Access Survey shows that one in five patients face challenges before they even get to see a provider due to data and information discrepancies, while 22% of patients reported experiencing delays in care due to insurance verification. Increased claim denials When providers submit claims with inaccurate or outdated information, it can result in delayed claims processing or denials. More than half (56%) of providers say patient information errors are a primary cause of denied claims. Claims may require rework and resubmission due to outdated billing information, which adds even more delays and burdens staff. Providers may also bill the wrong payer if a patient has unknown secondary insurance coverage and needs to resubmit to the correct provider. Bottlenecks in claims management that result from manual insurance verification create headaches for staff and patients. They also directly impact cash flow, potentially disrupting a provider’s entire revenue cycle. How insurance verification software can improve efficiency When providers leverage insurance verification software, like Experian Health’s Insurance Eligibility Verification solution, there are fewer medical billing errors, cleaner claims submissions and staff are no longer burdened by time-consuming, tedious manual tasks. Automation of eligibility checks: Automating insurance verification throughout the entire patient financial journey ensures cleaner claim submissions, speeds up reimbursement and reduces medical billing errors. Other tools like Experian’s Health’s Coverage Discovery automatically work across the entire revenue cycle, searching both commercial and government payers to find previously unknown coverage, identifying accounts as primary, secondary or tertiary coverage. Real-time coverage and benefits updates: Insurance verification software ensures patient information is always up-to-date. Experian Health’s solution, for example, lets providers access real-time patient reliability data by connecting with over 900 payers. Additionally, its optional Medicare beneficiary identifier (MBI) lookup service can automatically find and validate Medicare coverage—a process that’s commonly done manually. Integration with existing systems and interfaces: Automated insurance eligibility solutions that integrate seamlessly with the tools providers are already using—like claims management and health record systems—accelerate insurance verification, keep patient insurance information up-to-date and allow staff to leverage data analytics to further streamline operations. For instance, Experian Health clients have access to insurance verification tools through eCare NEXT®, which offers a single interface for staff to manage several patient functions. Key features to look for in insurance verification software Healthcare organizations adopting patient insurance verification software should prioritize solutions offering features such as multi-payer support, real-time eligibility checks and analytics tools. As healthcare regulations continue to evolve, especially around price transparency, providers adopting insurance verification software will also benefit from partnering with a solution provider that offers compliance support. Embracing patient insurance verification technology helps providers get paid faster The entire revenue cycle hinges on timely and accurate payer reimbursements. Although often underestimated, the right patient insurance verification solution can be the key to minimizing reimbursement roadblocks and getting claims paid faster. Automating patient insurance checks as early as registration—and at every step along the patient journey—helps providers prevent cash flow issues and reduce long-term revenue losses. Learn more about how Experian Health’s Insurance Eligibility Verification solution can help healthcare organizations reduce eligibility verification errors and accelerate reimbursements. 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: Survey data shows that healthcare providers find it harder to secure reimbursement for their services. Automation, staff training and analytics are the keys to preventing denials, improving accuracy and streamlining every step of the claims process. Experian Health's integrated claims management solutions are designed to close the claims gap and accelerate reimbursement. Claims management has become 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. Billing teams are left to work through dense code lists and figure out each payer's distinct playbook, often without the tools or time to catch mistakes. Managing claims efficiently is essential to ensure accurate and timely reimbursement. What is claims management in healthcare? Claims management is the process of preparing, submitting and following up on healthcare claims to ensure providers are paid for the care they deliver. It spans the entire revenue cycle, from verifying coverage during patient intake through final settlement. For revenue cycle teams, good claims management is what keeps finances on track. But with the volume of patients, claims and complex payer rules continuing to increase, the pressure is on organizations to tighten up their processes. Three key findings from the State of Claims survey show what they are up against, when compared with metrics from 2022: 73% of providers say claim denials are increasing 67% report longer reimbursement timelines 55% have seen a rise in claim errors Each denied or delayed claim adds to the administrative burden. However, when claims are submitted correctly the first time, staff can focus on patients instead of paperwork. The claims management process step by step Clean claims start with getting the basics right. "Once you let bad data in the door, it's like a virus," says Jordan Levitt, Senior Vice President at Experian Health. "Every action you take once bad data enters your system is wasting resources." Each of the following steps is a chance to keep the claim moving: Patient intake and verification Staff collect and verify patient demographic information, insurance details and eligibility at patient intake. If any of the information is missing or incorrect, the risk of denial increases immediately. Experian Health's flagship Patient Access Curator addresses this problem directly, using artificial intelligence (AI) and robotic process automation to automatically check and verify these details.   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. Medical coding Coding is where clinical services become billable. Staff must select the correct codes from thousands of options covering diagnosis, procedure and supply. If the codes don't match the care provided or a modifier is left out, the claim will come back, leaving money on the table. Claim submission At this stage, all the key data is packaged together and sent to the payer, often through a clearinghouse. Claims should be reviewed line by line for errors before filing, but relying on manual processes is slow and highly risky. Automation offers a better chance at catching issues before the claim reaches the payer. Adjudication and payment posting Once the payer reviews the claim, they'll validate the services, apply negotiated rates and determine payment or denial. Payment posting closes the loop, allowing providers to reconcile accounts quickly and flag underpayments or errors needing further action. Denial management and appeals Not every claim gets paid the first time. When denials come in, teams need to know what went wrong to fix the issue and get the claim resubmitted quickly. Denial management software identifies the reasons for denials and organizes work queues for faster resolution. Patient billing and collections Anything insurance doesn't cover is billed to the patient. If the bill is confusing or shows up late, it's less likely to be paid. Upfront conversations, flexible payment options and convenient point-of-service collections can improve collection rates and patient satisfaction. Best practices for effective claims management Getting ahead of the claims challenge isn't just about fixing denials after the fact, but about preventing them in the first place. Automation, staff training and visibility into what's working (or not) all play a role. Implementing automation and technology Manual work and disconnected systems are a drag on reimbursement. Automation helps standardize routine tasks, reduce errors tied to human input and create consistent workflows that can handle sudden surges in patient volumes. AI takes this to the next level, by predicting denials, flagging coding errors or coverage issues before submission and prioritizing claims that need attention. For example: ClaimSource® is an automated claims management system that organizes claims activity from a single hub. This system makes claims editing and submissions more efficient, by performing customizable edits and checking for errors before submission. On the back end, AI Advantage™ uses AI and machine learning to predict claim outcomes and push urgent tasks to the front of the queue, so staff can spend time on the claims that matter most financially.   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. Training and education for staff Successful claims management depends on a confident team. Staff should undergo regular training to stay current on payer rules, policy changes, coding updates and get support to understand new technology. To that end, Experian Health offers live training and on-demand webinars for teams to hear about the latest industry best practices and to see how others are using different tools. Hands-on consultancy support is also available to help teams get up and running with claims management products. Monitoring and analyzing claims data To improve claims performance, staff also need to be able to see where claims might be getting stuck. Tracking key performance indicators like clean claim rate, denial rate and days in accounts receivable helps staff spot issues. Integrated revenue cycle management tools bring everything together in one place so management can see the full picture and make sense of their data.   Blog: How to choose the right key performance indicators for your revenue cycle Find opportunities to prevent revenue leakage by building a healthcare revenue cycle KPI dashboard populated with the right medical billing metrics. Common challenges in claims management and how to overcome them Even with best practices in place, there will always be challenges and uncertainty. Claims pass through multiple departments, which means multiple opportunities for miscommunications or mistakes. Aligning workflows and claims management systems can reduce friction and help keep data secure. Another hurdle is managing the growing number of tools in use. The 2024 State of Claims report shows that one in five providers uses at least three revenue cycle solutions to pull together each claim, creating more complexity than clarity. Again, choosing claims management software from a single supplier will ensure a neat and efficient process. Finally, there's the challenge of meeting changing patient expectations. For 65% of patients, managing healthcare is overwhelming, especially when it comes to understanding costs and coverage. Organizations must maintain fast, accurate and transparent claims processing for better patient experiences. Next steps for strengthening your claims management approach The impact of claims management goes beyond the balance sheet, directly affecting patient satisfaction and operational efficiency. To move forward, healthcare leaders should ask: Are denial trends being tracked and addressed? Do teams have the tools and training they need? Is automation being used where it can make the most significant difference? Answering "yes" to these questions is the first step toward efficient claims management. With the right support, organizations can shift from daily firefighting to more predictable reimbursement strategies. Find out more about how Experian Health's award-winning claims management solutions help healthcare providers improve reimbursement rates and reduce denials. Learn more Contact Us