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
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
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
Key takeaways: As healthcare costs increase, the demand for patient financial assistance also rises as more patients find themselves without insurance coverage or facing economic hardship. Early identification of charity care eligibility reduces patient financial stress, makes the financial experience more compassionate, and protects providers from bad debt. Automated screening tools like Patient Financial Clearance, built on accurate, real-time data, are essential for flagging eligible patients before accounts go to collections and ensuring that no one misses out on vital support. Too often, patients who qualify for financial assistance aren't identified until after their accounts have been sent to collections. As healthcare costs increase and coverage becomes less certain, more patients will likely face financial challenges, making timely support even more critical. With estimated income data and financial behavior indicators, healthcare organizations can identify patient eligibility for charity care earlier, before the bills pile up. This article looks at how automated charity screening tools like Patient Financial Clearance can help providers support patients, protect revenue and remove the financial barriers that get in the way of care. The rising demand for patient financial assistance Demand for financial support is climbing quickly as economic pressures and policy changes make it harder for patients to keep up with medical costs. Nearly one in four adults are uninsured, often delaying or forgoing care because of high deductibles and out-of-pocket costs. Medicaid redeterminations have already resulted in more than 19 million disenrollments. At the same time, the Congressional Budget Office estimates that new federal spending provisions could push an additional 10.9 million people out of health coverage by 2034. As a result, revenue cycle teams will increasingly find themselves trying to collect payments from patients who are more likely to need financial help. "We're also seeing more states pass legislation that effectively mandates early screening for financial assistance before billing, such as Oregon's HB 3320," says Alex Liao, Senior Product Manager for Patient Financial Clearance at Experian Health. "These policies are becoming major drivers of financial clearance efforts. Identifying financial need early in the process helps patients avoid unexpected medical debt, and gives providers the insight they need to manage accounts appropriately and protect revenue." For providers, growing administrative costs, claim denials and underpayments mean less flexibility to absorb uncompensated care. Early screening protects against the burden of medical debt and facilitates the transparency and clarity patients need to manage their bills. Why does early identification of patient charity care eligibility matter? When charity care eligibility is missed or delayed, patients can quickly accumulate medical debt they can't afford. In an interview about the latest State of Patient Access survey, Clarissa Riggins, Chief Product Officer at Experian Health, explains why this is so important: "Cost is a major pain point," she says. "The report shows that 34% of patients struggle to pay for healthcare. That number is up from 23% last year. And nearly all patients, 95%, say they at least sometimes have trouble paying. It's clear that affordability is still one of the top reasons people delay care." Identifying charity care eligibility early on ensures these patients don't fall through the cracks. This reduces financial stress for patients and protects providers from avoidable write-offs and bad debt. When staff know which patients are likely to need support, they can have more compassionate and helpful financial conversations and connect patients with appropriate resources. Unlock patient charity care eligibility with automated screening Manual charity care screening processes are often time-consuming and prone to delays, especially when staff have huge volumes of information to handle. Automated financial assistance screening tools use real-time data to identify patients who may qualify for charity care with greater speed and accuracy. For example, Patient Financial Clearance (PFC) helps providers screen patients earlier in the financial journey by automatically checking for eligibility at or before the point of service. It uses a range of estimated data points, including household income, household size and Federal Poverty Level (FPL) percentage, to assess whether a patient qualifies for charity care, Medicaid or other financial assistance. After calculating a risk score to evaluate the patient's propensity to pay, PFC can pre-fill application forms, reducing the need for staff input and accelerating enrollment. For those who may not qualify for charity care, PFC can recommend payment plan options that align with the provider's financial policies. This proactive, behind-the-scenes screening enables providers to flag eligible patients at multiple points in the care journey, ensuring more patients get the support they qualify for while minimizing manual work for staff. Case study: How UCHealth wrote off $26 million in charity care with Patient Financial Clearance See how UCHealth partnered with Experian Health to create a more streamlined approach to providing charity care to patients who needed it. Take a smarter approach to patient financial assistance with Experian Health Automated charity screening tools like Patient Financial Clearance are faster, more consistent and easier for staff to act on. But they'll fall short without reliable data. "Strong data practices are key," says Riggins. "That means better systems to catch errors before they become problems, regular staff training, and giving patients the chance to double-check their records… By automating tasks traditionally performed by human staff, healthcare organizations can save time associated with administrative intake and coverage verification. This also means solving for bad data in real-time, which can prevent billing and claim errors in the long run. Clean data makes everything easier, from billing to insurance verification to patient trust." She gives the specific example of Patient Access Curator, which uses artificial intelligence to run multiple data checks at once, covering eligibility verification, coordination of benefits, Medicare Beneficiary Identifiers, demographics, and coverage discovery. When thinking about how to use data to find charity care eligible patients, tools like this lay the foundation for more proactive financial engagement. By cleaning up data and automating repetitive tasks, Experian Health's revenue cycle solutions enable providers to streamline their financial operations and give financial counsellors the details they need to engage patients at the right time and help them understand their options. The bottom line Automation and accurate data aren't just backend upgrades. They're essential to building a smarter, more compassionate financial experience, with fewer accounts going to collections. By embracing the best practices for identifying patients needing financial assistance, early action, better data quality, and automation, providers will be better placed to make sure no one misses out on the help they need. Find out more about how Patient Financial Clearance can help healthcare organizations automate financial assistance and identify patients eligible for charity care. Learn more Contact us
Managing claims efficiently—and reducing denials—remains one of the biggest challenges for healthcare providers. Statistics reveal that 46% of denials are caused by missing or inaccurate data, as highlighted by Experian Health's 2024 State of Claims Survey. For providers, these denials translate into endless follow-ups with patients, staff burnout, rising bad debt (which has increased by 7% year-over-year), and slim revenue margins. Reworking a denied claim costs providers an average of $25 and hospitals $181—an expense that is difficult to justify. Introducing Patient Access Curator: Automated claims accuracy from day 1 Fortunately, there is now a way to ensure claims are processed accurately from the start, without excessive effort: Patient Access Curator (PAC), Experian Health's groundbreaking new tool that uses artificial intelligence (AI) to revolutionize the claims process. As a central component of Experian Health's Patient Access portfolio, this innovative solution automates front-end processes, identifies incorrect data upfront, and resolves inaccuracies in real time, preventing costly claim denials before they occur. Introduced in early 2024, the curation tool is getting the attention of revenue cycle leaders at health systems and laboratories, with good reason. This article gives a run-down of Patient Access Curator and how it helps providers prevent claim denials in seconds. On-demand webinar: Reimagining patient access — AI at the epicenter of coordinated benefits management Explore how automation and AI are eliminating manual errors, reducing denials and unlocking millions in recoverable revenue. Built-in AI for more accurate data and seamless claims denial prevention Most issues that lead to denials crop up early in the revenue cycle, when information is missed or captured incorrectly during patient registration. For this reason, it makes sense to focus on denial prevention strategies on the front end. With so much data to capture, manual strategies are bound to stumble. Unfortunately, many digital tools still require staff to check multiple payer websites and data repositories to verify insurance eligibility and check for any billable coverage that might have been missed. Patient Access Curator takes on these tasks seamlessly, and right within Epic workflows. From patient demographics and eligibility checks to coordination of benefits (COB) primacy, Medicare Beneficiary Identifiers (MBI), and insurance discovery, the system automates these essential processes, providing precise data within moments. This solution ensures data integrity from the moment of registration by replacing manual guesswork with advanced AI-driven technology. This reduces the frequency of denials, minimizes A/R write-offs, and curtails vendor fees. Beyond enhancing efficiency, the tool safeguards the financial health of healthcare providers. Jason Considine, President of Experian Health, says, "Our mission is to simplify healthcare. Patient Access Curator's advanced AI technology equips providers to address claim denials more effectively and efficiently than ever before." Say goodbye to manual work with instant eligibility and insurance verification Patient Access Curator simplifies operations for billing teams, healthcare staff and patients. By removing administrative hurdles, staff can focus on patient engagement, rather than spending time on paperwork, phone calls and browsing websites for data. The outcome is improved satisfaction for both healthcare providers and their patients. "We know this technology is revolutionizing the healthcare industry," shares Jordan Levitt, Senior Vice President at Experian Health. Levitt, who developed the AI-powered data capture technology, explains, "By delivering faster, more accurate results, providers can improve financial solvency while giving staff and patients a better experience." Gone are the days of asking patients for insurance cards or verifying numbers and dates that might be inaccurate. With this solution, registrars and billing teams can be confident in the data they collect, right from the start. PAC was created to replace the manual guesswork that often bogs down eligibility and insurance verification processes. From patient demographics and eligibility checks to COB primacy, MBI, and insurance discovery, this solution automates these critical touchpoints, delivering accurate data in seconds. Fewer denials, faster reimbursements The impact on denial prevention is unparalleled. Patient Access Curator ensures fewer claim rejections and faster payer reimbursements by identifying and correcting bad data across eligibility, COB, and discovery at the start of the revenue cycle. Providers are left with more retained revenue, which can be reinvested into what truly matters: patient care. Patient Access Curator: Key features that set it apart Patient Access Curator differentiates itself as a comprehensive, all-in-one product that simplifies the most complex aspects of claims management. Key features include: Real-time data correction: Fixes inaccurate data instantly without staff intervention. Comprehensive coverage: Finds and corrects bad data across eligibility, COB primacy, MBI, demographics, and insurance discovery. Eligibility verification: PAC automatically interrogates 271 responses, flagging up active secondary and tertiary coverage information to eliminate coverage gaps Coordination of Benefits: Integrating with eligibility verification workflow, PAC automatically analyzes payer responses to find hidden signs of additional insurances that may be missed by a human eye, and triggers additional inquiries to those third parties to determine primacy, for faster COB processing Medicare Beneficiary Identifiers: PAC uses AI and robotic process automation to find and fix patient identifiers so no one misses out on essential support Insurance discovery: For patient accounts marked as self-pay or unbillable, PAC automates additional coverage searches Demographics: The platform can quickly check and correct patient contact information. Seamless integration: Automatically updates host systems (Epic) with verified and corrected coverage data in seconds. The results? Fewer clicks, faster workflows, and more accurate billing processes. PAC doesn't just prevent claim denials; it transforms how healthcare teams approach patient access and revenue cycle management. Proven ROI: How Patient Access Curator delivers $100 million boost to Exact Sciences Explore how Patient Access Curator powered a $100M improvement at Exact Sciences by automating insurance discovery and reducing claim denials. Improve financial health by focusing on patient health By eliminating redundant administrative questions, Patient Access Curator allows patients to focus on their health rather than the complexities of billing and coverage. Meanwhile, healthcare staff enjoy a boost in morale, thanks to fewer manual tasks and more efficient workflows—a benefit that can lead to higher staff retention over time. Patient Access Curator is more than a tool; it's a game-changer for healthcare organizations looking to protect their revenue while delivering a better, more seamless experience for both staff and patients. Say goodbye to manual guesswork and hello to a smarter, faster, and more reliable way to manage claims. With PAC, healthcare organizations can finally get claims right from the start, without the hassle. Patient Access Curator is available now - learn how your healthcare organization can get started and prevent claim denials in seconds. Learn more Contact us
Prompt patient payment after service is a key factor in keeping revenue cycles on track. However, patients don't always pay right away or in full. Despite around 90% of Americans having health insurance coverage, many patients still face medical debt. Unpaid patient bills often leave providers on the hook chasing patient collections and footing the cost for uncompensated care. This article covers some of the key patient collections metrics to help revenue cycle leaders get insights on how to measure and improve revenue cycle collections. Why measuring patient collections is critical in revenue cycle management When protecting profits in today's increasingly challenging healthcare landscape, revenue cycle management (RCM) leaders know that “what gets measured, gets managed.” The first step to improve patient collections rates is reviewing current data for issues. To do this, healthcare organizations must identify key performance indicators (KPIs) for measuring patient collections in the revenue cycle. Patient collections metrics are quantifiable measures that illustrate if a healthcare organization is effectively optimizing its collections process. They provide RCMs visibility and insights that help indicate if the organization is achieving its goals and effectively managing inflows and outflows. Key revenue cycle patient collection metrics Streamlining revenue cycle collections often hinges on collecting patient payments — and quickly. Here are a few common ways healthcare organizations can measure patient collections in revenue cycles. Days In Accounts Receivable (A/R) Rate - The days in Accounts Receivable rate is a metric that measures the average number of days it takes healthcare providers to collect payment for services — from both payers and patients. Lower days in A/R typically indicate an efficient billing and collections process. Days in A/R over 30 could lead to an increase in collections efforts, unloading to collections agencies, and even write offs to bad debt – all potentially resulting in cash flow issues and revenue loss. Gross Collection Rate - The Gross Collection Rate, or GCR, shows the percentage of total patient balances collected and indicates the health of the overall effectiveness of an organization's billing and collections process. Healthcare providers generally strive to keep GCRs as high as possible to prevent cash flow issues. The industry benchmark is typically around 95%, but this can vary by provider. Adjusted Collection Rate - Also known as the Net Adjustment Rate (NCR), this metric is shown as a percentage of the reimbursement healthcare providers collect in comparison to what they could have collected. It represents the amount of revenue healthcare organizations are losing, and a high NCR is typically an indicator of issues in the revenue cycle like uncollectible bad debt. Patient Balance After Insurance Ratio - The Patient Balance After Insurance Ratio, or PBAI Ratio, is the percentage of financial responsibility that falls on the patient after insurance pays. Tracking PBAI Ratios closely helps providers identify trends early on to stay ahead of issues that could potentially impact cash flow. As today's patients shoulder more self-pay costs, keeping tabs on this metric can help providers prioritize billing and collections that are compassionate and simple to access. Patient Contact Rate - The Patient Contact Rate measures how often a provider contacts patients with outstanding balances. Higher Patient Contacts Rates typically indicate high levels of engagement with patients about their unpaid bills that often leads to an easier collections process and improved cash flow. When Patient Contact Rates are low, providers may have an opportunity to increase patient communication efforts. Bad Debt Rate - The Bad Debt Rate shows providers how much patient debt goes uncollected and is written off as “bad debt” over a period of time. A high Bad Debt Rate often indicates a need to tighten up process improvements, like collecting more patient patients upfront. A good rule of thumb is to aim for a Bad Debt Rate of less than 5%. The lower the rate, the more efficiently the billing team collects patient balances. Cost to Collect - The cost to collect is a percentage-based metric that refers to the expenses healthcare organizations spend to recover payments from patients and payers. Many times, hospitals spend more to collect than what the patient owes, whether it's from time and resources calling unresponsive patients, paper statements sent to wrong addresses, etc., which makes this an important metric to track. Contingency Fees - When healthcare organizations turn to third-party agencies for their collections, a contingency fee is often paid for their services. This fee is usually a percentage of what the third-party agency is able to recover, and is often around 20-50% of the total amount. Some healthcare organizations work with multiple collections agencies, which can strain hospital cash flow even further. Hospitals must weigh the cost of outsourcing collections against maintaining in-house billing departments. Strengthening the revenue cycle with effective patient collection metrics Optimizing patient collections metrics helps strengthen the revenue cycle. Here are some strategies revenue cycle leaders can consider to help boost patient collections rates overall, improve patient engagement and lower bad debt rates: Improve patient communication: Sometimes patients need additional reminders to pay their bills. Providers looking to raise their Patient Contact Rate might benefit from engaging more with patients. Strategies can include making additional phone calls or sending monthly billing statements. Healthcare organizations that want to scale patient contact without adding to headcount may also benefit from tools like Patient Outreach Solutions, which increases collections through automated solutions like touchless text messaging, queue callback and bill reminders. Make it easier for patients to pay: Providers can shorten the amount of time it takes to collect payment from patients by implementing billing and collections processes that make it simple for patients to know costs up front and pay their bills. With a solution like PatientSimple, patients get access to self-service account management tools, like secure self-pay and patient estimates. Tools that automate the payment process, like Experian Health's PaymentSafe®, further enhance the payment experience by helping providers collect more revenue earlier and creating a seamless payment experience. Utilize data and analytics solutions to optimize patient collections: Experian Health's Patient Access Curator solution uses artificial intelligence (AI) to quickly verify patient insurance eligibility and coverage data in real-time. This can help ensure patient estimates and bills are accurate before the patient collections process even begins. Segment and screen patients by propensity to pay: During the patient collections process, Collections Optimization Manager helps identify high-value patient accounts and screen out bankruptcies, deceased accounts, Medicaid and other charity eligibility in advance. This solution segments patients by propensity of pay scores, and reduces the cost to collect. The Screening component of Collections Optimization Manager alerts staff to accounts that are not worth collecting from – whether it's a deceased or bankrupt, or charity care account. This saves valuable staff time and resources. Discover how Weill Cornell increased collections by $15M with Collections Optimization Manager. Gaining clear visibility in patient collections metrics Patient collections metrics data must be current and easily accessible in order to provide healthcare organizations with the most valuable insights into billing and collections challenges and opportunities. However, RCM analysts are often tasked with compiling data from numerous legacy processes and disjointed systems. Bringing together critical patient collections information into a revenue cycle dashboard can help revenue cycle leaders track the KPIs that matter most and show changes over time. This visibility into trends can help RCM understand how what areas of patient billing and collections need the most attention to improve patient communication, create workflow efficiencies and reduce revenue leaks. Learn more about how Experian Health's collections optimizations solutions can help healthcare organizations improve collections and increase their bottom lines. Learn more Contact us
Key takeaways: Error-prone manual processes are a top reason for delayed reimbursements. Automation across the revenue cycle can help providers see quicker reimbursements. Many processes can be automated: patient estimates, eligibility verification checks, collections, claims management, and more. Prompt reimbursements are crucial for today's healthcare organizations. Delayed reimbursements can lead to a domino effect that impacts the entire revenue cycle. Provider productivity goes down along with quality of care, patients have poor experiences and the bottom line takes a hit. Reimbursement delays often stem from error-prone, outdated manual processes, overburdened staff and excessive administrative work. However, incorporating revenue cycle management automation can help providers overcome numerous reimbursement challenges and improve processes overall. With revenue cycle automation, providers can eliminate many persistent pain points in traditional revenue cycle management (RCM). Staff no longer lose time to tedious manual tasks, patients get their queries answered faster, and managers get the meaningful data they need to drive improvements. And the biggest win? It's easier for providers to get reimbursed for their services, faster and in full. What is revenue cycle automation and how does it work? Healthcare revenue cycle management knits together the financial and clinical components of care to ensure providers are properly reimbursed. As staff and patients know all too well, this can be a complex and time-consuming process, involving repetitive tasks and lengthy forms to ensure the right parties get the right information at the right time. This requires data pulled from multiple databases and systems for accurate claims and billing, and is a perfect use case for automation. In practice, revenue cycle automation involves using technology to complete tasks and processes that may have previously been manually completed. These tasks might include: Automatically generating and issuing invoices, bills and financial statements Streamlining patient data management and exchanging information quickly and reliably Processing digital payments Collating and analyzing performance data to draw out valuable insights. Understanding the challenges in traditional revenue cycle management When it comes to delayed reimbursements, providers lacking revenue cycle management automation typically face the following challenges: Inefficiencies in patient access According to The State of Patient Access 2025, front-end operations are still a source of friction for patients and providers. Four out of the five top patient access challenges reported by providers relate to front-end data collection. Top concerns include insurance searches, reducing errors, and speeding up authorization. Nearly 48% say data collected at registration is “somewhere” or “not” accurate, while 85% report an urgent need for faster, more comprehensive insurance verification. Rising claim denials due to manual errors The State of Patient Access also showed that manual, error-prone processes often lead to delays, claim denials and patient frustration. In fact, more than half (56%) of providers say patient information errors are a primary cause of denied claims. When claims are denied, reworks are often time-consuming, costly and place additional burdens on already overworked staff. Difficulty in managing patient collections Due to rising costs, confusion over estimates and a lack of patient payment options, providers are often left to deal with unpaid medical bills. According to Experian Health data, 29% of patients say paying for healthcare is getting worse. Affordability is a key factor, but patients are also struggling to understand how much their insurance covers and looking for convenient payment options, like payment plans. Download The State of Patient Access 2025 report for a full run-down of patient and provider views about access to care. Six ways revenue cycle automation accelerates reimbursements Revenue cycle improvement through automation can help speed up reimbursements for healthcare providers by: 1. Capturing accurate information quickly during patient access Gathering patient data manually is time-consuming. Errors in the process can lead to denied claims and roadblocks in patient care. Tools like Experian Health's Patient Access Curator use artificial intelligence (AI) to streamline patient access and billing, improve data quality and address claim denials from the outset. This solution also ensures that all data is correct on the front end by checking eligibility, coordination of benefits (COB), Medicare Beneficiary Identifier (MBI), demographics and insurance discovery. 2. Simplifying collections and focusing on the right accounts Healthcare collections are a drag on resources. Automating the repetitive elements in the collections process helps reduce the burden on staff. Collections Optimization Manager leverages automation to analyze patients' payment histories and other financial information to route their accounts to the right collections pathway. Scoring and segmenting accounts means no time is wasted chasing the wrong accounts. Patients who can pay promptly can do so without unnecessary friction. As a result, providers get paid faster. 3. Reducing manual work and staff burnout Chronic staffing shortages continue to plague healthcare providers. In Experian Health's recent staffing survey, 96% of respondents said this affected payer reimbursements and patient collections. While automation cannot replace much-needed expert staff, it can ease pressure on busy teams by relieving them of repetitive tasks, reducing error rates and speeding up workflows. 4. Maintaining regulatory compliance with minimal effort While regulatory compliance may not directly influence how quickly providers get paid, it does play a crucial role in preventing the delays, denials and financial penalties that impede the overall revenue cycle. Constant changes in regulations and payer reimbursement policies can be difficult to track. Automation helps teams continuously monitor and adapt to these changes for a smoother revenue cycle, often with parallel benefits such as improving the patient experience. One example is Experian Health's price transparency solutions, which help providers demonstrate compliance with new legislation and provide extra clarity for patients. 5. Improving the end-to-end claims process Perhaps the most apparent way RCM automation leads to faster reimbursement is in ensuring faster and more accurate claims submissions. Automated claims management solutions, like Experian Health's award-winning ClaimSource®, reduce the need for error-prone manual processes, while improving accuracy and efficiencies in the claims editing and submission process. Additional claims management tools, like Claim Scrubber, also help providers submit more complete and accurate claims. Other tools, like Denial Workflow Manager, can be used if claims are denied. With automation and its extensive data analysis capabilities, work lists are generated based on the client's specifications, like denial category and dollar amount, to identify the root cause of denials and improve upstream processes to prevent them. And as artificial intelligence (AI) gains traction, providers are discovering new ways to use technology to improve claims management. AI Advantage™ uses AI and machine learning to find patterns in payer behavior and identify undocumented rules that could lead to a claim being denied, alerting staff so they can act quickly and avert issues. Then, it uses algorithmic logic to help staff segment and rework denials most efficiently. Providers get paid sooner while minimizing downstream revenue loss. 6. Providing better visibility into improvement opportunities Finally, automation helps providers analyze and act on revenue cycle data by identifying bottlenecks, trends and improvement opportunities. Automated analyses bring together relevant data from multiple sources in an instant to validate decisions. Machine learning draws on historical information to predict future outcomes, so providers can understand the root cause of delays and take steps to resolve issues. A healthcare revenue cycle dashboard is not just a presentation tool; it facilitates real-time monitoring of the organization's financial health, so staff can optimize workflows and speed up reimbursement. Embracing automation for a more efficient revenue cycle Like any business, healthcare organizations must maintain a positive cash flow to remain viable and continue serving their communities. Revenue cycle automation strategies can cut through many of the common obstacles that get in the way of financial stability and growth and speed up reimbursements. Learn more about Experian Health's revenue cycle management technology and see where automation could have the biggest impact on your organization's financial health. 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