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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: 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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Highlights: Healthcare claims processing is becoming more complex, putting financial stability at risk. Many organizations are turning to technology, particularly automation and artificial intelligence (AI), to improve the speed and accuracy of claims processing in healthcare Organizations that modernize their claims systems and track key performance indicators are better positioned to reduce denials and accelerate reimbursement. Healthcare claims processing is getting harder, according to Experian Health's 2024 State of Claims report. For 65% of healthcare leaders, claims management is more complex than before the pandemic. Slower reimbursements, rising denial rates and mounting administrative pressure are putting financial performance at risk. To improve speed and accuracy, many organizations are investing in technology: 45% of providers plan to invest in claims management technology in the next six months. As margins tighten, those that modernize their healthcare claims processing systems will be better equipped to stay financially strong. Understanding the current healthcare claims processing landscape Despite its central role in healthcare finance, claims processing continues to be one of the most resource-intensive and error-prone parts of the revenue cycle. Findings from the State of Claims report highlight three linked challenges that make it tough for providers to get paid promptly: rising denial rates, recurring errors that lead to even more denials, and the growing burden of rework. Denial rates are rising Claim denials are a persistent and growing issue. According to the report, 38% of healthcare leaders said that more than 10% of their claims are denied, and 11% reported denial rates over 15%. These numbers represent not just lost revenue, but significant time spent on rework and appeals. Common causes of denials The underlying reasons for denials are largely preventable. In the survey, 46% of respondents pointed to missing or inaccurate data and authorization problems as key contributors. These issues often stem from manual errors, inconsistent data entry, or gaps in communication between systems and teams. Incorrect insurance details, incomplete patient records and missing prior authorizations all lead to avoidable rejections. The cost of rework is growing As denial rates climb, so does the effort required to fix them. Almost half (48%) of respondents said they review denials manually, with three-quarters of denials handled by someone other than the person who processed the original claim. This puts extra strain on overextended revenue cycle teams on top of delayed payments. Leveraging technology for improved claims management Clearly, there's a need to reduce the manual burden. Comprehensive claims management platforms can help by automating workflows, tracking payer policies and improving claim accuracy at every stage. With claims processing tools designed to streamline decision points and flag potential issues early, revenue cycle teams can work more efficiently and sidestep disappointing financial results. For example, Denial Workflow Manager makes it easier to identify and prioritize denied claims by automating follow-up steps and assigning tasks to the right team members. Enhanced Claim Status submits automated status requests to payers, so staff can respond to pended, returned-to-provider, denied or zero-pay transactions before the Electronic Remittance Advice and Explanation of Benefits are processed. Along with ClaimSource®, organizations can centralize claim activity and apply customizable edits and consistent formatting to reduce errors before submission. Case study: How St. Luke's Health System cut denials by 76% with Enhanced Claim Status Enhancing data accuracy for cleaner claims While many denial management strategies focus on the submission process, achieving clean claims starts much earlier in the revenue cycle. Much of the inaccurate and incomplete patient data that causes so many denials originates at registration. Patient Access Curator addresses this issue by validating critical patient and insurance information at the front end. It pulls data from multiple sources to verify insurance eligibility, confirm coverage details and flag inconsistencies in real time. By resolving errors early on, it prevents incorrect data from flowing downstream into the claim process, resulting in millions of dollars saved. As Ken Kubisty, Vice President of Revenue Cycle at Exact Sciences notes, “You know when the Patient Access Curator went live because you can see it in our stock price. It helped us drive a $100 million bottom-line improvement within two quarters.” On the back end, a tool like Claim Scrubber bolsters clean claim strategies by reviewing pre-billed claims line by line, to catch any remaining errors. Together, this front-to-back accuracy boosts first-pass payment rates and reduces the risk of costly rework. Watch the webinar: Hear how Exact Sciences and Trinity Health used Patient Access Curator to tackle denials and make major savings. Implementing automation and AI to streamline claims processing Once claims are accurate and ready for submission, automation and artificial intelligence (AI) can help organizations work smarter and faster. Nearly half (47%) of providers already using AI consider it a competitive advantage, and it's easy to see why. Predictive tools allow teams to identify which claims are at risk of denial before they are sent, so they can intervene early and avoid costly delays. Tools like AI Advantage™ use AI and machine learning to analyze patterns in claims history and payer behavior. This solution flags claims that are likely to be denied and prioritizes them for review, helping staff focus their time where it has the greatest financial impact. By identifying potential issues in advance, organizations can reduce preventable denials and improve reimbursement rates. Analyzing key performance indicators to stay ahead Even with the right tools and processes in place, consistent results require teams to keep a close eye on performance. Regularly reviewing key performance indicators gives them the insight they need to adjust strategies and stay ahead of claim issues. Metrics like denial rates, clean claim rates and days in accounts receivable show where claims are most frequently getting stuck, where errors are recurring, and where improvements are actually working. While claims processing technology can do much of the heavy lifting, it isn't a set-it-and-forget-it solution. Long-term success depends on constant fine-tuning. Organizations that stay engaged and monitor key metrics closely are better positioned to reduce denials, accelerate payments and improve financial outcomes. Experian Health consultants are also available to help guide these efforts, offering expert support and strategic advice to help claims processing teams get the most out of their investment. Find out how Experian Health's claims management tools help organizations take control of claims processing in healthcare for cleaner claims, fewer denials and faster reimbursement. Learn more Contact us

Early diagnostics, remote patient monitoring and personalized care recommendations are just a few examples of how artificial intelligence (AI) is transforming the way healthcare is delivered. As technology advances, so do opportunities to optimize clinical and operational processes. With projected savings in the region of up to $360 billion annually, it's no surprise that 75% of healthcare executives believe AI has reached a turning point in their industry. Yet many providers are still just scratching the surface. Only a small percentage use AI for complex tasks like claim denial management, leaving the competitive advantage wide open. Understanding how these technologies work – and where to apply them for maximum impact – will be crucial to improve efficiency, remain competitive and above all, deliver excellent patient care.  The power of AI in healthcare As the name suggests, artificial intelligence refers to a machine's ability to perform cognitive tasks that would normally be associated with humans, such as problem-solving and decision-making. It can spot patterns, learn from experience and choose the right course of action to achieve a goal. Natural language processing, robotics and machine learning might all be in the mix. AI in the healthcare industry has been found to support applications like: Improving diagnosis through the analysis of medical images AI-powered wearables and virtual nursing assistants Patient data management Reducing and preventing insurance claim denials. Artificial intelligence in healthcare isn't a substitute for human contact, which underpins the best patient care. However, by increasing accuracy and reducing costs, it can help clinicians and healthcare administrators make better decisions that support a positive patient experience across virtually all healthcare settings. AI & automation in healthcare: key benefits  AI and automation deliver results in the three areas that matter most to healthcare organizations: improving the patient experience and care delivery, allowing staff to perform at their highest level, and increasing revenue. Boosting patient satisfaction through speed and accuracy Patient feedback has a few common themes: timely access to care, clearer communication and greater financial transparency. To meet these needs (and improve those feedback scores), healthcare providers should offer patients accurate, upfront information and reduce friction wherever possible. Tools like Patient Access Curator use AI to verify and update all necessary patient information at the front end, all at once, which drastically reduces the time and effort required to manage patient records. This streamlines patient intake and solves for bad data, which prevents claim denials and increases patient satisfaction. Bringing in more revenue by reducing claims errors The 2024 CAQH index estimates that 22% of current costs could be saved by shifting from manual revenue cycle processes to automated ones. Experian Health's State of Claims Survey 2024 suggests providers are eager to capitalize on this opportunity, with 51% seeking to reduce manual work. AI-driven solutions like Patient Access Curator and AI Advantage are designed specifically to meet these needs. Patient Access Curator automates insurance eligibility and coverage, scanning patient documentation for inaccurate information, and uses AI and robotic process automation to reduce manual errors. AI Advantage™ works to prevent denials before they happen, using predictive analytics to flag claims errors and alert staff to claims that fail to meet payer requirements. Improving staff performance by easing burnout The strain of manual processes doesn't just slow down operations. It's also a major cause of staff stress and burnout. Around half of healthcare staff report feeling burned out, costing the industry an estimated $4.6 billion each year. By taking repetitive tasks off busy employees' plates, AI can alleviate overwork and allow staff to focus on higher-value work, improving job satisfaction and productivity. In claims management, for example, AI Advantage, works in conjunction with ClaimSource®, to proactively identify claims with a high likelihood of denial prior to claim submission without staff intervention. This reduces the burden on staff while improving clean claim rates. How AI Advantage and Patient Access Curator improve patient care Experian Health's two flagship AI-based products go even further, offering new ways to use technology to improve patient care: Patient Access Curator uses AI and robotic process automation to streamline one of the most tedious parts of patient intake – verifying insurance eligibility and coverage. By automatically scanning patient records for errors and pulling up-to-date information from payer sources, it eliminates the guesswork and manual labor that bog down revenue cycle teams. The result is faster, more accurate eligibility verification and a smoother experience for both staff and patients. As Ken Kubisty, VP of Revenue Cycle at Exact Sciences, put it: “Within the first six months of implementing the Patient Access Curator, we added almost 15% in revenue per test because we were now getting eligibility correct and being able to do it very rapidly.”  On the back end, AI Advantage – Predictive Denials acts as an early warning system for denials, scanning claims before they go out the door to catch errors and flag risky submissions so they can be corrected in time. Built on advanced AI and machine learning, the platform evaluates claims using historical payment data and real-time payer behavior. Its counterpart, AI Advantage – Denial Triage, picks up where Predictive Denials leaves off, sorting rejected claims according to their potential for reimbursement and prioritizing them based on financial impact. Together, they help providers minimize denials, resulting in faster reimbursement and freeing up resources that can be redirected to patient care. Case study: See how AI Advantage helped Schneck Medical Center achieve a 4.6% average monthly decrease in denials in the first six months. The future of AI in healthcare: what's next? As a quick glance at any newsfeed will confirm, AI's role in healthcare is only going to expand. Predictive analytics will give staff increasingly powerful insights and recommendations to maximize reimbursements, while minimizing the burden on the workforce. AI's ability to continually learn and improve means providers that embrace AI will be better placed to make full use of their data and adapt to the trends and challenges that affect patient care. As expectations grow and resources shrink, AI is likely to be the only way to deliver the scalable, responsive, high-quality care patients deserve. Discover how solutions like AI Advantage and Patient Access Curator use artificial intelligence in healthcare to help reduce claim denials, improve patient access and more. AI Advantage Patient Access Curator

Experian Health's State of Claims survey finds that for many providers, it's getting harder to submit clean claims and taking longer to get paid. More than half say their current technology can't keep up. With revenue at risk, choosing the right denial management software is increasingly important. What features should healthcare organizations look out for to prevent denials and improve financial performance? Why denial management software is essential 11% of respondents in the State of Claims survey said that claims are denied more than 15% of the time, while the administrative cost of submitting and reworking claims continues to rise. Revenue cycle leaders are all too familiar with the challenges driving the denials trend: Frequent updates to payer policies, which make it harder for staff to be sure their submissions comply with the latest rules Incomplete or inaccurate data, such as missing codes or demographic errors, Staffing shortages put pressure on overworked teams, leading to higher error rates and slower response times Reimbursement delays, which tie up revenue and increase the cost of follow-up. Managing these issues is time-consuming and expensive. Speaking to the AAPC, Clarissa Riggins, Chief Product Officer at Experian Health, says that without a robust denial management strategy, providers risk falling further behind. “This growing crisis is a sign that traditional approaches are no longer enough, and providers should adopt more proactive strategies and the latest technology,” she says. Denial management software can help. By automating error detection, tracking payer requirements and helping staff prioritize high-risk claims, it can reduce denials and strengthen overall revenue cycle performance. According to the CAQH, just switching from manual to digital claim submission could save the industry up to $2.5 billion annually. Artificial intelligence (AI) and machine learning, used in solutions like AI Advantage™, can take those savings even further. Key features to look for in denial management software To make a real impact, healthcare denial management software must do more than just track denials. The best solutions offer faster responses, deeper insights and greater efficiency across the revenue cycle. Here are a few core features to seek out: Real-time claim monitoring Does the software alert users the instant a claim is denied? Real-time claim status updates are critical for minimizing delays and missed follow-ups. Automated alerts allow teams to act immediately when a claim is denied, preventing lost revenue and streamlining appeals before a backlog builds up. Tools like AI Advantage can also automatically detect payment pattern changes made by payers, so billers don't have to. Automated workflow  Can it reduce time spent on repetitive manual tasks? Ideally, the software will streamline submissions by auto-populating forms, attaching documentation and routing tasks to the right team members. This minimizes errors, shortens appeal cycles and frees up staff for higher-value tasks. Artificial intelligence Can the platform use AI to prevent denials before they happen (and prioritize the ones worth pursuing)? Experian Health's AI Advantage does this in two ways. First, it uses AI to analyze historical trends to flag high-risk claims before they're submitted, helping teams correct issues early and prevent denials altogether. Second, it identifies denials with the highest chance of a successful appeal, so staff can prioritize their time and improve overall recovery rates. Watch the webinar: Eric Eckhart of Community Regional Medical (Fresno) and Skylar Earley of Schneck Medical Center share how AI Advantage has helped them reduce denial volume, accelerate reimbursement and reduce time spent working low-value denials. Analytics and reporting Does it provide clear insights into why claims are denied? Advanced analytics identify denial patterns across payers, procedures and departments. A tool that offers denial-specific performance indicators, like denial rate, overturn rate and days to resolution will support smarter, faster decisions and long-term process improvements. Keri Whitehead, System Director of Patient Financial Services at UC San Diego Health, explains how AI Advantage gives her team actionable insights to get ahead of denials: Integration capabilities Can it connect seamlessly with current systems? A strong denial management platform should integrate smoothly with electronic health records, practice management systems and billing software. This eliminates data silos, reduces manual data entry and allows staff to work within familiar workflows. Experian Health's “Best in KLAS” claims management solutions can be used to build a single, connected system for greater visibility, fewer duplication errors and faster processing, to prevent denials without adding administrative overhead. Steps to evaluate denial management software Choosing the right claim denial management solution starts with a clear understanding of the organization's unique challenges and goals. Healthcare leaders should consider the following steps during the selection process: Define organizational needs. Identify the most pressing denial challenges, such as high denial rates, slow appeals or limited visibility, and prioritize software that directly addresses those issues. Evaluate integration compatibility. Confirm that the software integrates smoothly with existing systems to avoid data silos or workflow disruptions. Assess scalability. Ask potential vendors about how the solution will grow with the organization and adapt to changing claim volumes, payer mixes and regulatory demands. Review vendor support and training. Look for a partner that offers responsive support, user training and ongoing product updates. Request a demo or trial. The best way to figure out if a new platform will be a good fit for the organization is to see it in practice and let key team members try out its automation, interface and analytics for themselves. Book a demo of AI Advantage to see how it can help providers predict and prevent denials. Best practices for implementing denial management software Once the denial management software has been chosen, the final step is to make sure it's implemented successfully. This calls for good planning, team buy-in and ongoing evaluation. A few best practices to steer the process are to: Engage core teams early to ensure the software fits with their existing workflows and organizational goals. Make sure there's a shared understanding of what success looks like, using KPIs like denial rate reduction or faster appeals to measure performance and ROI. Provide thorough training to equip staff with the skills needed to use the system effectively. Regularly review software performance, denial trends and user feedback to refine processes and settings. By following these steps, organizations can maximize the impact of their new healthcare denial management software and turn a reactive process into a strategic advantage. Find out more about how Experian Health's denial management software, like AI Advantage, helps providers predict, prevent and process denials for faster revenue recovery. Learn more Contact us

Medical billing errors are common problems that can lead to significant financial losses for healthcare organizations. While most medical billing errors are preventable, outdated systems, complex processes and human errors often result in delayed or denied claims. Faced with ever-increasing overhead costs, workforce challenges and growing volumes of data, healthcare leaders will need to implement modern medical billing software solutions to improve revenue cycle management (RCM) medical billing efficiencies, without adding costly headcount or overhead. This article reviews the role modern medical billing software plays in revenue cycle management and how RCM leaders can use it as a top defense to prevent costly claim delays and denials. What is medical billing software in revenue cycle management? Medical billing software is a critical tool healthcare organizations use to streamline patient billing and collections in revenue cycle management. Revenue cycle leaders know that outdated and complex billing processes can wreak havoc on the entire revenue cycle and waste valuable staff time. However, medical billing in revenue cycle management allows providers to optimize the entire revenue cycle — from pre-visit insurance verification and cost estimates through patient billing and collections. Automated medical billing processes in the revenue cycle can help improve efficiencies, reduce errors, and create more reliable collections processes. This allows healthcare organizations to deliver better patient care while protecting their bottom line. How software powered by artificial intelligence (AI) improves medical billing efficiency AI-powered software helps providers manage many types of complex revenue cycle billing processes — from claims management to collections. Providers that embrace AI often benefit from streamlined medical billing processes, fewer claim denials, real-time eligibility verification, better data insights and productivity boosts. For example, AI-powered software can streamline medical billing by automating repetitive tasks, like insurance verification checks, so providers can prevent and catch errors, speed up reimbursements and stretch strained resources. On the front end, with single-click AI-driven data capture technology, running multiple manual eligibility queries is no longer necessary. Now, with solutions like Patient Access Curator, patient details can be verified quickly and accurately. Patient Access Curator leverages AI and machine learning to automatically handle eligibility verification, coordination of benefits, Medicare Beneficiary Identifiers, insurance discovery and more, with just one click. This saves staff hours and reduces human errors that can lead to claims denials and costly delays later on. Ken Kubisty, VP of Revenue Cycle at Exact Sciences, shares how Patient Access Curator helped their organization reduce claim denial errors and added $75 million in insurance company collections. AI-driven predictive analytics solutions, like AI Advantage™, can also help staff identify claims that may be at risk of denial, so potential issues can be handled before submission — saving even more staff time. When admin overhead is minimized, there's less burnout and less stress. Staff can focus on higher-priority tasks, and healthcare organizations can see productivity increase overall. Preventing claims denials with better billing solutions Claims denials are on the rise with healthcare organizations being left on the hook for delayed or unpaid claims. In the State of Claims 2024 report, 38% of survey respondents said that at least one in ten claims is denied. Some organizations see claims denied more than 15% of the time. That's a lot of cost in reworks and lost revenue. Nearly half of providers say patient information errors are a primary cause of denied claims. Errors are common during pre-visit insurance verification due to error-prone manual processes, but can happen at any point during the collection process. Medical billing software helps providers reduce errors and submit cleaner claims right from the start and catch errors before they become costly problems. Here are some of the key ways medical billing software like Experian Health's Patient Access Curator solution helps providers head off claims denials before they happen.   Eligibility checks: Automatically verifies patient eligibility and updates records in real-time to ensure patient information is accurate before claims submission. Coordination of Benefits (COB) verification: Discovers and verifies secondary and tertiary insurance coverage to reduce the risk of COB-related denials while using AI-powered technology to seamlessly integrate with a provider's eligibility verification process. Medicare Beneficiary Identifiers (MBIs): Updates MBIs to confirm patient records are correct and compliant with Medicare requirements while using AI-driven technology and automation to find and correct patient identifiers automatically. Demographics: Patient demographic information is corrected and updated using in-memory analytics and Experian Health's proprietary algorithm to accurately find and fix contact information. Insurance Discovery: Identifies and corrects missing or incorrect insurance information to ensure claims are submitted with the most accurate information available. Discover how Experian Health's revolutionary AI-powered revenue cycle solution is turning denial management into denial prevention. Patient Access Curator solves for missing or correct data in real-time at registration and scheduling, creating a smooth, clean claim process and lowering denials by double digits. Optimize efficiencies in claims management through AI Experian Health customers currently using ClaimSource® can now improve their claim management strategy — before claim submission and after denial. With AI Advantage™ Predictive Denials and Denial Triage, providers can leverage historical claims data and Experian's deep knowledge of payer rules to continuously adapt to an ever-changing payer rules landscape.AI Advantage's - Predictive Denials component reduces denial rates, detects payer changes and empowers staff to focus on highest-priority claims, while AI Advantage's - Denial Triage identifies denials with the highest reimbursement potential and uses AI to segment denials, eliminating guesswork for billers. Watch the video to learn more about the two components that make up AI Advantage, and how healthcare organizations can transform the reimbursement process and decrease claim denials for good. Medical billing software is only getting smarter and faster Upgrading outdated manual medical billing processes results in cleaner claims, improved staff efficiencies, better care and improved patient satisfaction. Today's AI-driven technology brings medical billing in RCM to the next level, enabling time-strapped providers to do even more with less. Now busy providers can streamline manual processes that used to take hours into just seconds. With this new technology, patient information is accurate when claims are submitted, eliminating the need for costly reworks and hits to the bottom line. As more providers adopt AI technology for RCM in medical billing and software solutions get more sophisticated, providers will see new success stories in its power to help healthcare organizations optimize the entire revenue cycle. Learn how tools like Patient Access Curator and AI Advantage can help healthcare organizations prevent claim denials and improve medical billing in RCM. Learn more Contact us

Ask any healthcare revenue cycle manager how they feel about using artificial intelligence (AI), and the response is likely to be “hopeful, but wary.” The potential is clear — fewer denials, faster reimbursements and more efficient workflows. However, with adoption slowing, it seems many have lingering concerns about implementation. According to Experian Health's State of Claims survey, the number of providers using automation and AI in revenue cycle management has halved from 62% in 2022 to 31% in 2024. Despite these reservations, there are bright spots. From preventing claim denials to automating patient billing, AI and automation are already helping many healthcare organizations improve operations, boost financial performance and deliver a better patient experience. This article examines what providers need to know about bringing AI technology into their revenue cycle. Understanding the role of AI in revenue cycle management AI regularly hits the headlines for its clinical applications, like medical imaging analysis, drug discovery and surgical robotics. But behind the scenes, it's also quietly transforming revenue cycle management (RCM). Non-clinical processes like medical billing, claims management and patient payments are complex. Trying to manage these manually results in slow reimbursement and strained resources. AI offers efficient solutions to reshape how providers manage these pressing issues, giving them a head start in coping with increasing costs, workforce challenges and ever-increasing volumes of data. Benefits of AI in healthcare RCM  For most providers, AI's main draw is its ability to deliver significant financial savings. The most recent CAQH index report suggests that switching from manual to electronic administrative transactions could save the industry at least $18 billion. That's a compelling prospect for revenue cycle leaders looking to do more, and faster, with fewer resources. These financial savings aren't just the result of direct cost-cutting – they stem from the broader operational benefits AI brings to the table. These include: Streamlined billing processes: Automating repetitive tasks and minimizing human error reduces costly mistakes that lead to payment delays Fewer claim denials: Predictive analytics help staff identify claims that may be at risk of denial so that issues can be tackled upfront Real-time eligibility verification: AI tools can check a patient's insurance details in an instant, to catch outdated information and prevent billing mistakes and denials Better data insights: AI has the power to analyze vast datasets and find patterns and bottlenecks to help teams improve decision-making Productivity boost: With reduced admin overhead, staff can focus on higher-priority tasks and improve overall performance, with less stress and burnout. The benefits extend to patients, too. Behind every denied claim or billing error is a patient caught in administrative confusion. By automating processes, eliminating errors and increasing transparency, AI and automation help providers give patients financial clarity throughout their healthcare journey. How AI is revolutionizing healthcare RCM  Here are some examples of what this looks like in practice: Using AI to manage complex billing procedures Medical billing errors cost healthcare organizations millions of dollars each week, and the problem is only getting worse. Experian Health's State of Patient Access survey 2024 found that 49% of providers say patient information errors are a primary cause of claim denials, while in the State of Claims survey, 55% of providers said claim errors were increasing. Manual processes make managing the complexity of insurance plans, billing codes and patient payments near impossible. AI simplifies the task. For example, Patient Access Curator uses AI-powered data capture technology, robotic process automation, and machine learning to verify coverage and eligibility accurately with one click. This ensures accuracy throughout the billing cycle, reducing denials and accelerating collections. On-demand webinar: Watch our recorded session to hear how revenue cycle leaders from Exact Sciences and Trinity Health share their strategies and success stories with the Patient Access Curator. Using AI to prevent claim denials Claims can be denied for many reasons, but poor data consistently tops the list. Even so, around half of providers are still using manual systems to manage claims. AI helps providers buck the trend by improving data quality and using that data to improve claims management. Experian Health's AI AdvantageTM, available to those using the ClaimSource® automated claims management system, analyzes patterns and flags issues before claims are submitted, using providers' historical payment data together with Experian Health's payer datasets. It continuously learns and adapts, so results continue to improve over time. Read the case study: AI Advantage helped Schneck achieve a 4.6% average monthly decrease in denials in the first six months. Using AI to reduce patient payment delays The rise in high-deductible health plans is associated with a greater risk of missed patient payments. According to SOPA, 81% of patients said accurate estimates help them prepare for the cost of care, and 96% are looking for their provider to help them make sense of their insurance coverage. AI is vital for providers looking to help patients understand their financial responsibility early and avoid payment delays. With solutions like Patient Access Curator, staff no longer need to sift through piles of patient data and payer websites to verify eligibility and get a clear picture of a patient's insurance coverage. Instead, they can quickly gather the information they need to give the patient a prompt and accurate breakdown of how the cost of care will be split. "Within the first six months of implementing the Patient Access Curator, we added almost 15% in revenue per test because we were now getting eligibility correct and being able to do it very rapidly." Ken Kubisty, VP of Revenue Cycle, Exact Sciences Key AI technologies driving RCM transformation Healthcare revenue cycle managers have long trusted automation to handle repetitive tasks. Hesitancy around AI may stem from a lack of familiarity with its more advanced capabilities. Findings from the State of Claims survey reveal a widening comfort gap, with the number of respondents feeling confident in their understanding of AI dropping from 68% in 2022 to 28% in 2024. So, what are some of the key technologies providers should understand to help bridge the gap? While automation relies on straightforward, rule-based processes to handle repetitive tasks, AI tools are capable of learning, adapting and making decisions. A few examples to be aware of include: Machine learning: Analyses historical data to predict trends like claim denials and payment delays, and use this knowledge to prevent future issues Natural language processing: Extracts actionable insights from unstructured data, such as clinical notes and patient communications, giving staff consistently formatted data to use in RCM activities AI-powered robotic process automation: Goes beyond basic automation to handle decision-based workflows with precision, for example, in evaluating claims information to make predictions about the likelihood of reimbursement. Challenges and considerations in implementing AI in RCM Getting to grips with what AI technologies offer is an important first step for healthcare revenue cycle managers. However, successful implementation also calls for consideration of the practical challenges. Can AI solutions be successfully integrated with existing legacy systems? Will the data available be of high enough quality to drive meaningful insights? Are the costs of implementation within budget, especially for smaller providers? Is the workforce ready to buy into AI, or will extensive training be needed? With careful planning and a trusted vendor, these challenges are manageable. Embracing AI for a smarter, more efficient RCM The benefits of AI in revenue cycle management are clear: more innovative, faster processes that free up staff time and reduce errors, resulting in much-needed financial gains. To maximize AI, providers should begin by reviewing their organization's key performance indicators and identifying areas where AI can add the most value. This should focus on points in the revenue cycle where large volumes of data are being processed, such as claims submissions or patient billing, which are common areas for inefficiencies and errors. By taking a strategic, targeted approach, providers can find the right AI solutions to make the biggest impact – whether it's through curating patient insurance information, improving claim accuracy or predicting denials. A trusted vendor like Experian Health can guide teams through the AI setup and make sure it meets their needs. Find out more about how Experian Health helps healthcare providers use AI to solve the most pressing issues in revenue cycle management. Learn more Contact us