Tag: patient access curator

Key takeaways: Manual patient insurance eligibility checks often lead to billing errors, claims processing delays and denials. Automated insurance eligibility verification streamlines the process with real-time checks — ensuring patient insurance and billing information is always up-to-date. Accurate insurance information leads to cleaner claims submissions, reducing delays and denials while maximizing reimbursement rates and timelines. Insurance eligibility verification is one of the most crucial stages in the healthcare revenue cycle. Ever-evolving payer rules, new regulatory requirements and increased patient financial responsibility put organizations at risk for non-reimbursement when mistakes are made with patient insurance information. To ensure that patient insurance information is up-to-date, providers must run insurance eligibility verification checks to confirm active coverage and verify details like deductibles, payable benefits and payer billing details. To keep up with rising claim denials and patient volumes, organizations are shifting away from tedious, error-prone manual insurance verification processes. Instead, automated insurance eligibility verification tools offer providers access to faster, more accurate insurance verification checks — in real-time. The result? Fewer billing errors, quicker claims processing, reduced denial rates and a stronger bottom line. What is automated insurance eligibility verification? Insurance eligibility checks confirm if a patient has active coverage and search for missing health insurance. Sometimes referred to as insurance verification, the process can be either manual or automated and typically occurs before a patient receives care. During automated insurance eligibility verification, providers leverage technology to quickly and accurately confirm insurance coverage details. Instead of manually checking a patient’s insurance information, which may require logging into different platforms, making phone calls and other administrative tasks, tools like Experian Health’s Insurance Eligibility Verification automate the entire process. Automated insurance verification enables eligibility checks to happen in real-time, accross every stage of the revenue cycle — from registration to billing. This allows providers to easily—and quickly—confirm insurance status, coverage details, medical service benefits, billing details and other key information needed for accurate claim submissions and billing. Limitations of manual insurance eligibility verification While manual insurance eligibility verification is still commonly used to confirm a patient’s insurance eligibility, running the verification process manually presents numerous challenges for healthcare providers. It’s error prone. Insurance verification typically relies on insurance collected during patient intake. But when registration relies on manual methods, mistakes are common. Patients or staff may enter details incorrectly on forms and billing systems. A patient can switch insurers or forget about a secondary insurance coverage they may have. Experian Health data shows that nearly half of healthcare providers (48%) report that information collected during registration or check-in is either somewhat or not accurate. Patients agree, with 20% saying mistakes are common when they register or check in for an appointment. It’s inefficient. Manual insurance eligibility checks take time. Staff can become bogged down by heavy administrative tasks that take time away from other priorities. Phoning patients to confirm insurance details, correcting billing errors and resubmitting claims all create extra work for busy front desk staff and billing teams. The process also disrupts patient care, with 22% of patients reporting delays in care due to insurance verification issues and one in five patients saying they’ve faced challenges due to information discrepancies before seeing their provider. It increases denials. In the 2025 State of Patient Access Survey, 56% of providers report that patient information errors are a leading cause of denied claims. Manual eligibility checks aren’t always a reliable way to ensure patient insurance information is accurate and up-to-date. When outdated or incorrect insurance information is included on a final claims submission, it can result in delayed claims and denials—adding even more workload for staff and frustration for patients. 4 benefits of automated eligibility verification for healthcare providers Automated eligibility verification tools have numerous upsides for providers, including fewer medical billing errors, cleaner claims submissions and less administrative burden on staff. Here’s a closer look at some of the key benefits that can come with making the switch to an automated solution like Experian Health’s Insurance Eligibility Verification tool. 1. Creates efficiencies across the revenue cycle Automating insurance eligibility verification workflows allows providers to automatically (and quickly) verify patient insurance details at all stages of the patient financial journey—with little to no staff intervention. When coverage information is always up-to-date and accurate, staff spends less time clearing up information discrepancies, chasing down coverage and correctly billing errors or reworking claims. Tools like Experian’s Health’s Coverage Discovery help prevent even more bottlenecks — searching commercial and government payers to find previously unknown insurance coverage, identifying accounts as primary, secondary or tertiary coverage. Streamlined insurance verification through automation ultimately leads to faster reimbursements and improved cash flow, especially for healthcare providers managing high patient volumes. 2. Provides coverage and benefits updates in real time Having up-to-date patient insurance information at all stages of the revenue cycle is crucial for providers. When information is accurate, claims are cleaner, and reimbursement rates improve. However, verifying payer information and Medicare coverage is often a complicated and time-consuming process when handled manually. Solutions that use automation, like Experian Health’s Insurance Eligibility Verification tool, give providers access to real-time patient eligibility data by connecting with over 1,700 payers. Additionally, its optional Medicare beneficiary identifier (MBI) lookup service has the ability to find and validate Medicare coverage — automatically. Patient Access Curator™  takes this one step further by using artificial intelligence (AI) to verify and update patient records in real-time. 3. Offers seamless integration with other revenue cycle tools Many providers already use technology-based solutions across the revenue cycle—like claims management tools and health record systems. Layering in an automated insurance eligibility verification tool further streamlines operational efficiencies—especially with a solution designed to seamlessly integrate with an organization’s existing systems and interfaces. Experian Health’s Insurance Eligibility Verification solution “plugs in” to existing healthcare systems, automatically updating patient insurance information across the revenue cycle. Plus, organizations can leverage powerful data analytics to reduce even more potential bottlenecks. Experian Health clients also get access to insurance verification tools through eCare NEXT®, which offers a single interface for staff to manage several patient functions. 4. Reduces claim denials Accurate data collection is one of the best ways to prevent denials. The 2025 State of Claims report reveals that the top reasons for claim denials are patient insurance information issues and other data discrepancies. Half of providers say “missing or inaccurate claim data is the top cause for denials, while 30% blame incomplete or inaccurate patient registration data. Automated insurance eligibility checks help providers ensure information is accurate and up-to-date and keep up any changes in real-time across the revenue cycle. Case study: Experian Health & Providence Health See how Providence Health cut denials and found $30 million in coverage annually with automated eligibility checks. The future of automated insurance eligibility verification Automated insurance eligibility verification is a game-changer for healthcare organizations. It provides faster and more accurate patient insurance information, which can be used across the entire revenue cycle to ensure cleaner claims and maximize reimbursements. Solutions like Patient Access Curator utilize AI and machine learning to further refine data collection, eliminating the need for time-consuming and costly re-checks. Key patient information is consolidated across all patient access processes into one single workflow —including eligibility checks, coordinator of benefits, Medicare Beneficiary Identifier (MBI) verification, demographics, insurance coverage and financial status. Healthcare providers will need to start leveraging new technologies and move away from manual processes, or risk falling behind in the digital age. Learn more about how Experian Health’s Insurance Eligibility Verification solution can help healthcare organizations reduce eligibility verification errors and accelerate reimbursements. Learn more Contact us

Denial management is the process of addressing why healthcare claims are rejected or denied, instead of resolving them after they occur. This article explores denial management strategies, why outdated processes fail and how AI-driven solutions can help reduce denials and streamline workflows.

Top reasons for healthcare claim denials include missing or inaccurate data, lack of prior authorizations, and incomplete patient registration.

Experian Health’s 2025 High-Performance Summit was a catalyst for collaboration, innovation and a shared commitment to simplifying healthcare – for both providers and the patients that they serve.

As the healthcare industry prepares for the implementation of the One Big Beautiful Bill Act (OBBBA), it’s clear that readiness is not one-size-fits-all. Hospitals are leading the way, but most providers will need focused updates to their Medicaid/Medicare processes to ensure compliance and protect revenue. In October 2025, Experian Health surveyed 200 healthcare decision-makers to get a better understanding of their readiness levels, where they’ll be impacted and what they’re focusing on, following implementation of the OBBBA. Here are the results:  To prepare for incoming changes from the OBBBA, revenue cycle leaders will need to accelerate their adoption of artificial intelligence (AI) and automated solutions. AI-powered tools, like Patient Access Curator, can help providers streamline insurance eligibility checks and improve claims accuracy. Other tools, like  Patient Financial Clearance, can help providers support their patients, and minimize risks from uncompensated care. Find out how Experian Health's revenue cycle management solutions can help your healthcare organization navigate upcoming regulatory shifts and changes.  Learn more Contact us

When it comes to artificial intelligence (AI) usage in the healthcare industry, adoption is steadily gaining momentum as providers explore new ways to utilize this technology in their revenue cycle management (RCM) processes. While full trust in AI remains limited, especially for high-stakes decision-making, confidence is rising. Privacy, security, and implementation costs continue to pose significant challenges. However, providers broadly agree that AI will become a cornerstone of healthcare RCM in the next few years, especially in areas like eligibility verification and patient access. Many also acknowledge that human oversight will remain essential, to ensure accuracy and trust. In October 2025, Experian Health surveyed 200 healthcare leaders to better understand how much they trust AI for decision-making, their biggest barriers to adoption, and where the opportunities lie. Here are the results: AI in healthcare RCM isn’t the future; it’s happening now. Learn how healthcare organizations are using Experian Health’s AI technology to streamline patient access and reduce claim denials. Learn more Contact us

Key takeaways: Efficient revenue cycle management is crucial to ensuring efficient hospital operations and building financial stability.   RCM technology solutions allow healthcare organizations to increase cash flow and improve operational efficiency across the entire revenue cycle.   Revenue cycle management tools from Experian Health utilize data-driven insights, automation and AI to optimize revenue cycles, while supporting compliance and regulatory needs.  The revenue cycle management market is projected to grow to $238B by 2030. Revenue cycle management is a critical process that ensures healthcare organizations maintain healthy cash flow and keep operations running smoothly. However, keeping the financial scales tipped in the right direction can be a never-ending challenge for revenue cycle leaders. As hospital profit margins remain tight, technology-based RCM solutions can help revenue cycle leaders stay ahead and maximize reimbursements. In this guide to revenue cycle management, providers will learn how to optimize revenue cycle processes at every stage of the patient journey. What is revenue cycle management (RCM) in healthcare? Revenue management in healthcare connects the financial and clinical aspects of patient care. The primary purpose of RCM is to help healthcare organizations ensure proper reimbursement and accurate, efficient billing and claims management processes. Seamless revenue cycle management also allows providers to maintain a solid financial foundation, a critical factor in boosting resilience during uncertain economic times.    Over the last few decades, RCM in healthcare has undergone numerous evolutions. Largely paper-based, manual processes have been replaced by sophisticated software-based systems and data-driven technology. As more organizations embrace the ongoing digital transformation of RCM in healthcare, processes now commonly include solutions that utilize machine learning, automation and artificial intelligence (AI). Leveraging technology boosts efficiencies, streamlines operations and allows organizations to see quicker reimbursement rates. However, despite these upsides, switching to new modern revenue cycle management systems isn’t always a priority for providers. Many healthcare organizations still partially rely on outdated and disjointed systems that can result in reimbursement delays and other snags in the revenue cycle. How the healthcare revenue cycle works A typical healthcare revenue cycle follows the step-by-step lifecycle of a patient encounter, known as the patient journey. Every touchpoint is an opportunity for revenue cycle teams to ensure that patients, payers and back-office teams have the information needed to expedite payment. Along with revenue cycle leaders, a wide range of healthcare staff are commonly involved in various administrative functions across the RCM cycle. Depending on the organization and how revenue cycle processes are set up, this may include front desk staff, scheduling teams, medical coders, billing staff and collections teams. While individual healthcare organizations often customize their exact RCM process, most revenue cycles are generally broken down into several key​​ phases of the patient journey: pre-visit, visit and post-visit. Each phase of the healthcare revenue cycle also has its own specific components, such as registration, claim submission and collections. Key stages of the revenue cycle process commonly include: Pre-visit: This phase includes all of the steps of the patient journey that happen before treatment, such as preregistration, patient registration, insurance verification and prior authorization.  Patient visit: The next phase includes revenue cycle activities related to the patient visit for treatment or services, such as documentation, coding and charge capture.   Patient post-visit: This phase includes the steps of the patient journey after care has been received, such as claims submission, collections, payment posting, and any necessary follow-up.   Detailed breakdown of each revenue cycle stage Successful healthcare revenue cycles consist of a series of stages. Each component of the RCM cycle is carefully designed to prevent revenue leaks and create a frictionless patient journey. Here’s a detailed breakdown of what happens during each revenue cycle ​​stage across the pre-visit, visit and post-visit phases of the patient journey: Patient registration: Gathers key patient information before service, including demographics, insurance, medical history and other personal details.  Eligibility and benefits: Verifies patient insurance coverage status, checks for additional or unknown coverage and provides transparent, accurate estimates prior to service. Data entry: Maintains accuracy of patient information data, verifying and protecting patient identities to ensure the right information is linked with the right patient. Prior authorizations: Determines if prior authorizations are needed before service, submitting payer requests as needed. Patient encounter: Adds information about the services a patient receives to the patient record, setting the stage for accurate coding and billing. Charge posting: Submits claims to relevant payers using the appropriate charge posting or charge entry process  — including a detailed breakdown of all services provided to the patient, patient information, history and insurance or payment plan status. Coding and billing: Checks payer codes for the services that have been delivered — using diagnostic (Dx) codes, place of service (POS) codes, current procedural terminology (CPT) codes, Healthcare Common Procedure Coding System (HCPCS) codes and others to determine payable amounts. Claims management: Submits claims and facilitates communication between providers and payers during the claims adjudication process, providing early intervention for denied claims and reworks as needed. Payer contract management: Ensures timely reimbursements — auditing payer performance, keeping track of changing requirements and identifying reimbursement discrepancies and patterns of non-reimbursement. Patient billing and collections: Bills patient for remaining amount owed after insurance reimbursement — collecting balances using in-house collections teams or outside collections agencies. ​​​Common challenges in revenue cycle management (RCM) To avoid escalating administrative costs and revenue leaks, teams must remain vigilant against challenges that disrupt the revenue cycle — including data errors, billing code mistakes, claims denials and payment delays. It can often be overwhelming for busy RCM leaders to sidestep obstacles. However, staying on top of challenges in revenue cycle management is critical to ensuring healthy cash flow and smooth-running daily operations.  Here’s a closer look at six common roadblocks RCM leaders need to keep tabs on: Incomplete documentation: Missing or outdated insurance information — and other missing or incorrect patient data — can lead to coding errors, claim denials and billing delays. Mistakes are most common when organizations use outdated manual processes, like paper forms. Coding errors: Mistakes made during billing code submissions — often due to error-prone manual processes or rapidly changing payer requirements — can lead to denials, delays and reworks. Claim denials: Claims denials are on the rise, leaving healthcare organizations to face potential hits to the bottom line from delayed or unpaid claims, while adding extra administrative burden for reworks. High days in accounts receivable: Collection delays are often a major roadblock in the revenue cycle — disrupting cash flow and potentially leading to extra administrative costs and bad debt.   Patient payment responsibility increases: Rising healthcare costs, including out-of-pocket expenses and high-deductible healthcare plans, put more financial burdens on today’s patients, leaving many struggling to pay their medical bills. Regulatory complexity: New price transparency regulations, implementation of the One Big Beautiful Bill Act, patient privacy safeguards under the Health Insurance Portability and Accountability Act (HIPAA), payer compliance changes and other rapidly evolving healthcare requirements can bottleneck revenue cycle processes and slow down reimbursements.  ​​​Strategies to improve healthcare revenue cycle performance Leaders tasked with improving healthcare revenue cycle performance can adopt RCM strategies that turn roadblocks into opportunities for growth. Here are five strategies to streamline RCM processes, boost performance and maximize revenue.  Implement automation Quick, accurate and efficient patient access processes are the foundation of healthy revenue cycles. Revenue cycle leaders should look at technology-forward solutions that leverage automation to boost efficiencies across all stages of the revenue cycle – from registration and scheduling to prior authorizations, claims processing and collections.  Utilize real-time eligibility checks Finding missing health insurance is critical to keeping revenue cycles on track. Real-time insurance eligibility verification allows providers to quickly confirm active coverage at any point in the revenue cycle, including additional coverage a patient may have forgotten.   Avoid solutions that require heavy staff training or certifications Revenue cycle management solutions that are easy to onboard and require little to no staff training or special certifications are often more efficient to implement and utilize — minimizing administrative costs and allowing busy staff to focus on other priorities.  Consider outsourcing vs. in-house billing Implementing tools that streamline key steps in the RCM process—like coding, claims submissions and collections—allows busy billing teams to maximize their time, save on administrative costs, accelerate collections, and avoid unnecessary outsourcing to third parties.  Choose the right metrics to ​​monitor Identifying and monitoring key revenue cycle performance indicators (KPIs) aligned to specific RCM priorities offers real-time insights into key stages across the revenue cycle — including patient access, collections, claims and contract management. Check out this guide to choosing the right key performance indicators for your revenue cycle dashboard to ensure the effective implementation of RCM ​​strategies. RCM in the era of modern technology and ​​AI Reimbursement delays commonly stem from error-prone manual revenue cycle processes. Overworked staff burdened by time-consuming administrative tasks related to RCM often further compound reimbursement issues. However, adopting solutions that utilize revenue cycle management automation, machine learning and AI allows healthcare organizations to overcome numerous pain points and ensure prompt reimbursement.   While constantly evolving, today’s top revenue cycle management technology often relies on:  Interoperability and data integration: Data-driven, turnkey revenue cycle management healthcare tools share data and function together seamlessly across the revenue cycle — using machine learning, automation and AI to constantly improve RCM.  Patient engagement tools and payment portals: AI-powered patient engagement tools and automated solutions improve patient access and accelerate collections rates.  Use of predictive analytics: Built-in predictive analytics offer actionable insights that improve patient access, claims processing, collections and other key areas of the revenue cycle.   Revenue cycle management case studies​​ Exact Sciences Ken Kubisty, VP of Revenue Cycle at Exact Sciences, shares how Experian Health’s Patient Access Curator™ helped their organization reduce claim denial errors and added $75 million in insurance company collections. Community Medical Centers Brandon Burnett, VP, Revenue Cycle at Community Medical Centers, shares how their organization partnered with Experian Health to implement AI Advantage™, which uses artificial intelligence to prevent and triage claims denials. Weill Cornell Medicine In a recent on-demand Webinar, we shared how Weill Cornell Medicine and Experian Health implemented a smarter collections strategy that delivered $15 million in recoveries using Collections Optimization Manager. Watch the on-demand webinar > How to choose the right RCM software or vendor Revenue cycle leaders who want to improve their organization’s RCM process often benefit from implementing RCM software or partnering with a vendor that specializes in healthcare revenue cycle digital solutions.   When choosing a solution, look for these key features: Patient access tools to improve registration, scheduling, estimates and payments. Insurance verification software with the ability to perform real-time eligibility checks and stay on top of ever-evolving regulations and payer policies. Claims management solutions that improve accuracy and efficiencies across claims submission and denials management processes. Collections software to streamline patient collections and reduce bad debt. Contract management tools to audit payer compliance against contract terms and maximize reimbursement rates. Data and analytics tools to monitor the revenue cycle, track key performance metrics and gain valuable insights. Questions to ask vendors Vetting vendors is critical to finding the best RCM software. Each healthcare organization has unique needs, so it’s important to vet vendors carefully to find the right revenue cycle management solutions.   Consider these questions when scoping out revenue cycle software solutions and vendors: Implementation: What’s the implementation process like? How does staff training and onboarding work?   Integration: Will the RCM software work with legacy systems? If not, what processes can it replace?   Customization: What types of customization options are available? What legacy systems are supported?   Scalability: How flexible is the solution? Does the RCM software have the ability to scale?   Usability: Is the software user-friendly? How easy is it to navigate the platform, share data and manage multiple stages of the revenue cycle?  Reporting: What types of reporting and analytics are built-in? Can KPIs be customized?   Cost: How does pricing work? Is it determined by functionality? Number of users? Size of organization?  Customer support: What type of customer support is available? Will the organization have a dedicated customer service representative? Are experts available to help customize the software for the organization's needs or analyze data? Build vs. buy decision-making Adopting technology to streamline revenue cycle management is often a large investment. Finding the best solution often comes down to the healthcare organization's unique needs, including budget, existing technology stack and other factors.   Ultimately, the tools chosen will have a significant impact on an organization’s financial and operational health, making the decision to build a custom solution or purchase turnkey RCM software a critical one. While there’s no “right” choice, revenue cycle leaders should consider the pros and cons and vet vendors carefully to help ensure long-term success. Why choose Experian Health for revenue cycle management​ Working with an industry-leading revenue cycle software solution partner, like Experian Health, allows healthcare organizations to modernize and speed up their entire revenue cycle management process. Experian Health offers a wide range of award-winning revenue cycle management tools that allow organizations to optimize every stage of the revenue cycle — from patient access to collections, claims management and payer contract management.   Robust automated solutions help organizations eliminate manual processes, submit cleaner claims, maximize collections and cash flow – all while staying compliant with the latest regulations and improving the patient experience at every stage of the journey. Experian Health’s built-in RCM analytics leverage data to analyze, track and further optimize performance. Turning revenue cycle roadblocks into opportunities for ​​growth Today’s healthcare revenue cycle leaders face more RCM obstacles than ever before — from increasingly complex billing processes and rising healthcare costs to frequent regulatory and payer requirements and staff shortages. However, providers also have unprecedented access to RCM technology solutions designed to streamline all stages of the revenue cycle management process. Healthcare organizations that embrace RCM software solutions – especially tools that use AI, automation and machine learning – can optimize revenue cycle management, boost overall financial resiliency and keep revenue flowing for many years to come.   Learn more about how Experian Health’s revenue cycle management solutions can help healthcare organizations generate more revenue and increase their bottom lines. Learn more Contact us

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

Healthcare claims denials are on the rise, despite more than a decade of industry-wide technological advances aimed at improving claims management processes. However, in recent years, the introduction of artificial intelligence (AI) into the healthcare ecosystem has begun transforming how healthcare organizations manage patient access — and the entire revenue cycle. The State of Claims: 2025 Download the full report to uncover actionable strategies and see if AI is what can break the denial cycle for your organization. This article summarizes a recent webinar with Experian Health’s Vice President of Innovation, David ‘Fig’ Figueredo, and Kate Ankumah, Product Manager for Patient Access Curator™, as they break down how healthcare organizations can use AI to build scalable, data-driven revenue cycle solutions and deliver measurable value across the patient access ecosystem. 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 > Evolution of AI in healthcare For more than a decade, a progression of technology – mostly rooted in automation – has attempted to solve the issue of rising denials. Today, with the help of AI solutions, the process is shifting away from transactional activities to a more intelligence-driven approach. AI tools can be implemented at every stage of the revenue cycle to solve persistent challenges – like benefit coordination, eligibility verification, and claims management. And while most providers have the capability to add AI solutions, claims denials continue to climb. “With all of the investment by organizations like Experian Health and HIS system vendors, there still is a high prevalence of an issue with coordination of benefits and eligibility denials.”David Figueredo, Experian Health’s VP of Innovation Figueredo further points out that while revenue cycle leaders are aware of AI and its potential, they often remain skeptical of the technology or are unsure how to best leverage AI tools for denial prevention. Overcoming perceptions about AI Healthcare leaders sometimes struggle with negative perceptions around adopting AI solutions. Figueredo notes this is common, and wants organizations to know that with AI, “There’s a lot of power, hope and expectation around the use of applied technologies and automation in the revenue cycle process.” Concerns about implementing AI for revenue cycle management vary widely. However, according to the results of an Experian Health data study presented during the webinar, "accuracy and reliability” are often a top worry among healthcare organizations considering adopting AI technology. Other common concerns about leveraging AI solutions include data privacy and security, cost of implementation, staff resistance and labor risk, and lack of transparency. Healthcare organizations also want to base the decision to utilize AI on measurable results. Where in the revenue cycle has AI been implemented? How did it improve denial rates? Finding a path forward with AI AI offers healthcare organizations the potential to increase operational efficiencies, reduce administrative burdens, and reduce costs. While many revenue cycle leaders are most willing to place bets on using AI for patient eligibility verification and claims management, barriers to adopting AI still exist. Figueredo notes: “We’re seeing a lot of organizations that are interested [in AI], but also guarded about its use. Healthcare leaders typically have a specific goal in mind for using AI and want to see real-world results.” He reminds healthcare leaders that with AI, we “can do things we couldn’t do before – but it’s how it’s applied in solving things in the [revenue cycle] process” that really matters. For many healthcare providers, the question becomes: Does adding AI solutions to the revenue cycle provide acceleration? Improve patient access? Reduce the number of manual touches? Can AI do more of the work consistently so staff labor can be reapplied to other focus areas? Does AI help mitigate ongoing staff shortages? Will it cut costs for healthcare organizations already operating on thin margins? Adopting AI: RCM best practices When modernizing the revenue cycle, Figueredo reminds healthcare providers to have a clear set of guidelines and recommends ensuring AI solutions are designed to meet specific revenue cycle goals. Top priorities for healthcare organizations often include: Reducing manual interactions: While there are still some situations that require human intelligence to make decisions, countless simple tasks can be automated to minimize manual workload. Fixing issues on the front end: Early interventions to proactively correct potential issues with claims before they become a bigger problem, like incorrect patient demographics or eligibility information, can be critical to preventing denials. Supporting real-time integration: To avoid relying on batch auditing or poorly informed automated decision-making in the revenue cycle, HIS systems and patient access platforms, like scheduling and billing, must be designed to handle real-time corrections. Adopting AI for COB with Experian Health’s Patient Access Curator Turnkey AI tools, like Experian’s Health’s Patient Access Curator (PAC), allow healthcare organizations to implement a comprehensive patient access COB solution that touches every step of the revenue cycle process – starting with patient registration. PAC consolidates important functions like eligibility checks, MBI, demographics and discovery into one seamless solution to maximize clean claims and minimize denials, appeals and resubmissions. Kate Ankumah, Product Manager for Experian Health’s Patient Access Curator, explains: “We know that bad data is like a virus. If it starts bad, it ends up on the claim – even if you try to solve it mid-stream, it’s already saved somewhere. At the point of scheduling, at the point of registration, [with the Patient Access Curator], we’re giving you the most accurate data so that it can live and get accurate to the claim." Case study: Experian Health and OhioHealth See how OhioHealth cut denials by 42% with Patient Access Curator and solved claim errors at the source. Benefits of leveraging AI for COB and claims management Adopting COB solutions powered by AI and machine-learning, like Experian Health’s Patient Access Curator, healthcare providers can improve overall accuracy during claims processing on the front end – and at every step of the revenue cycle. And when errors are reduced from the start, healthcare organizations typically benefit from less wasted staff time, decreased denial volumes, accelerated denial management, and fewer contingency vendor fees – plus a better patient experience overall. Patient Access Curator is available now – learn how your healthcare organization can get started and prevent claim denials in seconds. Learn more Contact us