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Key takeaways: Revenue cycle teams can use automation to reduce repetitive work and apply AI where data-driven prediction, matching or prioritization can improve a workflow. Experian Health’s 2025 State of Claims survey found that 41% of providers now face denial rates of 10% or higher, while 68% say submitting clean claims is more challenging than a year ago. Patient Access Curator™ (PAC) uses AI to support front-end data validation and insurance discovery, while AI Advantage™ helps teams predict denial risk and prioritize denial follow-up. Artificial intelligence (AI) and automation can support administrative work in healthcare. In the revenue cycle, teams depend on accurate information, timely decisions and efficient follow-up to keep claims moving. In revenue cycle management, AI and automation can help organizations reduce manual checks, find data gaps, predict denial risk and prioritize work queues. These tools are most useful when they support staff judgment, payer expertise and compliance oversight. They can handle repetitive, data-heavy tasks so staff can focus on exceptions and decisions that need human review. In 2023, McKinsey & Company reported that research suggests effectively deploying automation and analytics could eliminate $200 billion to $360 billion of spending in U.S. healthcare. For revenue cycle leaders, the practical question is where to apply those capabilities first. The case for applying AI and automation in healthcare Revenue cycle teams juggle many daily tasks. Staff collect and verify patient information, confirm eligibility, identify the right payer, submit clean claims, monitor status, work denials and manage collections. Small data gaps at the beginning of the process can create downstream rework and delays. Rework also consumes staff time, adding to these operational pressures. As costs rise and revenue cycles tighten, there is increasing pressure to do more with less. Experian Health’s 2025 State of Claims survey found that 54% of providers say claim errors are increasing and 90% of claim denials are reworked with at least some human review before resubmission. Providers are also managing broader financial and administrative pressures. The American Hospital Association has reported that prior authorization requirements, claim audits, denials and other payer policies add administrative burden and cost for hospitals and health systems. These requirements also consume staff time to appeal denials and manage payer processes. AI and automation are different but complementary. Automation follows defined rules to complete repeatable work. AI models can identify patterns in data, predict risk and help teams decide where to focus attention. When used together, they can support more consistent revenue cycle workflows. How AI and automation can support revenue cycle workflows Revenue cycle management automation and AI are most useful when tied to a specific workflow and a measurable operational problem. The goal is to help teams act earlier, reduce avoidable rework and focus staff time where judgment is needed most. For example, automation can complete rule-based eligibility checks. AI can help identify claims with a higher likelihood of denial. In insurance discovery workflows, AI can also help identify coverage that wasn’t captured at registration. When these tools fit into existing workflows, they can support more consistent decisions and reduce manual work. Three practical applications include: 1. Improving front-end data quality with Patient Access Curator Patient and coverage information collected early in the revenue cycle can affect downstream claim outcomes. Incomplete or outdated demographic details, eligibility responses, coordination of benefits or Medicare Beneficiary Identifier information can create problems that lead to claim delays or denials later in the cycle. Experian Health’s Patient Access Curator helps prevent claim denials by validating demographics, eligibility, insurance discovery, coordination of benefits and Medicare Beneficiary Identifier data in seconds. PAC’s AI and machine learning capabilities help improve match accuracy, coverage sequencing and data confidence by writing the validated data back into the host system and sequencing payers before the claim is created. This automates work that would otherwise require manual coverage checks. 2. Using insurance discovery to find coverage not captured at registration When active coverage isn’t identified during registration, claims may be delayed or submitted with incomplete insurance information. Insurance discovery looks for coverage that may not have been captured during registration. Patient Access Curator includes insurance discovery as part of its front-end validation workflow. It can help identify and correct missing or incorrect insurance information so claims can be submitted with more complete coverage data. 3. Using AI to prevent and prioritize denials Even with strong front-end processes, some claims still require additional attention. AI can help claims teams decide which claims to review before submission and which denials to work first after payer response. Experian Health’s AI Advantage supports two denial management use cases:1. AI Advantage – Predictive Denials uses a client’s historical claims data and Experian’s knowledge of payer rules to identify claims with a high likelihood of denial before submission so teams can take corrective action.2. AI Advantage – Denial Triage uses AI to segment denials and identify those with the highest potential for reimbursement. This approach can help teams prioritize with more confidence. Rather than treating every claim or denial the same way, teams can use predictive models to focus on the work that needs the most attention. Potential benefits of AI and automation in the revenue cycle A high-performing revenue cycle depends on timely, accurate and consistent work. AI and automation can help providers modernize that work without losing the expertise of the people who manage complex payer and patient situations every day. When applied to the right workflows, these tools can help organizations: Reduce manual data searches that take staff away from higher-value work Improve front-end data quality before claims are created Identify missing or incorrect coverage information earlier Spot claims that may be at higher risk of denial Prioritize denied claims by potential reimbursement Reduce rework caused by inaccurate or incomplete information Give staff more consistent information for follow-up decisions A focused AI strategy starts with the workflow problem, uses data that is relevant to that problem and keeps staff in control of judgment-based decisions. A more proactive approach to revenue cycle management Revenue cycle teams can move from reactive work toward a more proactive approach: catch errors earlier, validate coverage before claims are created and prioritize the claims and denials that need the most attention. Experian Health offers revenue cycle solutions that use AI and automation in targeted ways to support front-end data quality, reduce rework and manage denials. Patient Access Curator supports registration and coverage validation, while AI Advantage supports denial prediction and triage. Learn more about Experian Health’s Patient Access Curator and AI Advantage.
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Morbi fringilla luctus ex, nec rutrum massa iaculis et. Nulla euismod suscipit diam, non venenatis diam malesuada tincidunt. Curabitur nunc urna, hendrerit eget sem eu, congue laoreet erat. Vivamus facilisis massa justo, nec ultricies odio condimentum at. Phasellus id massa posuere, placerat ligula et, gravida diam. Donec pharetra, odio at malesuada molestie, nunc sem cursus metus, vel pretium tortor elit eu ante. Phasellus tempus rutrum elit, sed rhoncus est commodo eget. Morbi in pharetra neque, vitae iaculis lacus. Nullam auctor augue eget dictum maximus. Aliquam sed quam in enim mollis hendrerit. Nullam nibh dui, pulvinar tempor elementum ut, tristique ac eros. Vivamus id vulputate mauris. Phasellus accumsan egestas nunc, sagittis blandit lorem aliquet eu. Nullam et sollicitudin enim, id imperdiet nisi. Proin iaculis convallis lorem malesuada efficitur. Mauris ac massa felis. Etiam vel quam eu lectus finibus consectetur lobortis quis mauris. In gravida aliquet quam nec fringilla. Vestibulum euismod ligula nisl. Sed mattis commodo arcu laoreet aliquet. Donec ac erat turpis. Donec purus risus, aliquam in aliquet et, varius vel neque. Curabitur quis lorem consectetur, pharetra mauris in, luctus enim. Mauris non tortor mauris. Quisque consectetur neque at ipsum viverra porttitor. Integer ornare erat quis vehicula gravida. Mauris nec ipsum euismod, interdum enim sed, laoreet mauris. Donec et magna sodales, euismod nunc ut, pretium dui. Praesent vel nisl eget sapien volutpat lobortis non non leo. Heading 1 Vivamus vulputate at purus sit amet congue. Aliquam rhoncus quis neque quis dictum. Fusce quis turpis in diam fringilla commodo in ut nunc. list item 1 List item 2 List item 3 Heading 2 Vivamus vulputate at purus sit amet congue. Aliquam rhoncus quis neque quis dictum. Fusce quis turpis in diam fringilla commodo in ut nunc. Heading 3 Vivamus vulputate at purus sit amet congue. Aliquam rhoncus quis neque quis dictum. Fusce quis turpis in diam fringilla commodo in ut nunc. Suspendisse blandit augue et metus pellentesque, ut sagittis dolor imperdiet. Sed ut massa eget tortor cursus scelerisque sed id erat. Etiam nisi ante, cursus et facilisis ut, consectetur eu diam. Suspendisse luctus ligula pellentesque, porttitor purus a, tincidunt diam. Nunc sed sapien ac magna posuere commodo imperdiet in justo. Etiam dignissim rhoncus ornare. Morbi convallis ipsum nulla, et convallis lorem commodo ac. Aliquam ultricies rutrum ultrices. Morbi et faucibus sapien. In consequat mollis dolor, a egestas ex pellentesque ac. Maecenas lectus nunc, fringilla eu nisi sit amet, hendrerit pellentesque urna. Vestibulum ante ipsum primis in faucibus orci luctus et ultrices posuere cubilia curae; Ut ultricies est sed ante cursus, quis accumsan quam sollicitudin. Sed in nisl vitae nunc placerat tincidunt eu a lacus. Ut eu erat sodales, blandit erat ac, finibus nibh. Praesent consectetur nibh ac leo elementum imperdiet. Vestibulum vestibulum lorem nec varius dictum. Maecenas orci mauris, condimentum ut vehicula blandit, sodales vitae ligula. Nunc ullamcorper ex eu erat ultrices porta. Phasellus ac varius velit. Aenean volutpat magna sed ex laoreet egestas. Cras pretium tortor neque. Etiam ornare metus urna, nec pretium diam luctus ullamcorper. Suspendisse posuere pulvinar arcu, vel luctus metus tincidunt ac. Vivamus vulputate at purus sit amet congue. Aliquam rhoncus quis neque quis dictum. Fusce quis turpis in diam fringilla commodo in ut nunc. Maecenas dolor nunc, venenatis ac leo ut, blandit tincidunt erat. Vestibulum eu nisi iaculis, dapibus diam eu, mollis massa. Quisque et faucibus elit. Maecenas eu justo ac quam sagittis eleifend ac in mauris. Sed pharetra vestibulum leo, imperdiet porttitor ipsum condimentum faucibus. Pellentesque laoreet sagittis risus, nec suscipit diam aliquet id. Aenean eu leo non orci egestas viverra tempor at metus. Curabitur blandit neque eu urna pretium, ut mattis neque pellentesque. Duis nec ultrices nulla. Cras volutpat erat ac nunc facilisis mollis. Donec quis tortor elit. Nullam vitae purus lorem. Heading 1 Vivamus vulputate at purus sit amet congue. Aliquam rhoncus quis neque quis dictum. Fusce quis turpis in diam fringilla commodo in ut nunc. Heading 2 Vivamus vulputate at purus sit amet congue. Aliquam rhoncus quis neque quis dictum. Fusce quis turpis in diam fringilla commodo in ut nunc. Heading 3 Vivamus vulputate at purus sit amet congue. Aliquam rhoncus quis neque quis dictum. Fusce quis turpis in diam fringilla commodo in ut nunc.
Key takeaways: Revenue cycle teams need contract modeling tools that keep pace with changing reimbursement methods and payer rules. Returning to Experian Health’s Contract Manager and Contract Analysis gave Prevea Health greater confidence in its reimbursement analysis, helping staff identify underpayments earlier and investigate payment variances more efficiently. The changes delivered measurable results, including more than $323,000 recovered per quarter from key procedure codes, a 50% reduction in manual audit time, faster payments and fewer days in accounts receivable. Challenge: Changing reimbursement rules put contract modeling to the test Revenue cycle teams rely on accurate contract models to determine how much they should be paid for each claim and to confirm that payments match the agreed terms. Maintaining these models is increasingly challenging as organizations handle hundreds of agreements with different reimbursement methods and frequently changing payer rules. Prevea Health experienced this firsthand. Processing up to 100,000 claims each month, the organization's reimbursement analysis had become more demanding. The team needed more flexibility and visibility to help them model complex payment scenarios, simplify contract maintenance and calculate expected reimbursement with greater confidence. "Our modeling needs grew more complex, and we needed clearer visibility into our results and greater certainty in the outputs. That’s when we recognized how much we had relied on the precision, flexibility and clarity of Contract Manager and Contract Analysis to have confidence in the accuracy of our numbers."Tony Walch, Revenue and Reimbursement Analyst at Prevea Health Solution: Contract modeling designed for precision, flexibility and clarity Prevea Health had successfully used Experian Health's Contract Manager and Contract Analysis for many years before management changes prompted the organization to move contract performance work into Epic®. It soon became clear that those previous capabilities were needed again. Returning to Contract Manager and Contract Analysis gave the team a more reliable way to compare expected and actual reimbursement, investigate payment variances and identify underpayments. Multiple payer contracts could be modeled in one place, and advanced reporting tools allowed staff to filter and analyze real claims data to understand the financial impact of new payer requirements. The team could drill down to individual procedure codes to understand how different payer contracts reimbursed similar services in different departments. Implementation was structured to avoid interrupting the team's day-to-day reimbursement analysis. Maintaining contract models using this approach would also be less resource-intensive. Experian Health analysts updated the contract logic to reflect changes such as Medicare base years, Geographic Practice Cost Index (GPCI) updates and payer-specific reimbursement rules, helping improve accuracy without adding work for the team. Outcome: Better reimbursement analysis pays off Faster payments, fewer appeals and less time on follow-up Contract Manager and Contract Analysis gave Prevea Health the precision, flexibility and clarity they were looking for. Earlier identification of underpayments meant recoveries could begin sooner, while fewer payment discrepancies reached the appeals stage. Staff spent less time on manual audits and follow-up, payments moved through the revenue cycle more quickly and days in accounts receivable fell. This translated into measurable operational and financial improvements. Key results:– More than $323k recovered per quarter from key procedure codes – 50% reduction in manual audit time – Sustained improvement in payment variances – Faster payments and fewer days in accounts receivable Better analysis leads to better decisions For Walch, two capabilities made the biggest difference: a powerful modeling engine for testing different reimbursement scenarios and reporting tools that showed where revenue was being lost and where action was needed. Variance monitoring highlighted payment discrepancies early, so issues could be resolved before they affected revenue. “Even a small variance in modeling can have a significant impact,” said Walch. “Every undercharge we catch is revenue recovered and insight gained. It reflects how undercharge reporting revealed missed revenue, supported proactive corrections and improved long-term contract optimization, helping us stay ahead of issues rather than react to them.” With greater confidence in their financial analysis, staff could apply the insights to other revenue cycle initiatives. This included charge master optimization and identifying claims reimbursed under “lesser of” payment rules. Prevea Health’s renewed focus on accurate modeling and reimbursement visibility delivered clear operational and financial gains. Procedure code analysis became an ongoing tool for improving contract performance and budget planning. Undercharge reporting produced significant returns. Together, these tools continue to build a reliable foundation for greater financial decisions and better long-term performance. Learn how Contract Manager and Contract Analysis, ranked #1 Best in KLAS for Contract Management, helps healthcare organizations strengthen reimbursement analysis, recover underpayments and improve financial performance. Learn more Contact us Complete the form below to be connected with a member of our Sales team. For Customer Support, including password resets, please visit our Support page.
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Maecenas mollis, nibh at porttitor volutpat, sapien augue lacinia lorem, et euismod ipsum lacus non augue. Integer vestibulum nunc non quam egestas, et malesuada est laoreet. Curabitur aliquam sodales ipsum a dictum. Fusce tincidunt quis tellus et auctor. Maecenas eu dapibus libero. Donec pellentesque turpis augue, vitae condimentum enim maximus eu. Ut tempus aliquam sem ut sodales. Quisque ipsum lectus, sollicitudin eget porta eu, semper a magna. Quisque dolor mi, tempor at dui quis, aliquam sagittis lacus. Aenean tempus, augue eu consectetur consectetur, eros enim sodales risus, sit amet porttitor libero nunc vel massa. Vestibulum eleifend viverra nisi, quis lacinia enim auctor ac. Mauris nisl mi, consequat a mi sed, accumsan iaculis augue. Nam sodales neque eget metus volutpat sodales. Praesent tempus ex neque, id pellentesque nibh elementum ac. Donec suscipit posuere hendrerit. Etiam finibus justo vel neque porta pretium. 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Personal credit report assistance is not available here. If you have questions or issues related to your personal credit report, disputes or fraud alerts, visit Experian.com/help. Lorem ipsum dolor sit amet, consectetur adipiscing elit. Sed egestas malesuada pharetra. Donec nec sapien venenatis, consectetur dui vel, molestie sapien. Donec ac tortor est. Nam mattis nec massa quis volutpat. Nulla ac dictum nulla, volutpat placerat dui. Phasellus ac lacus quis est ultrices suscipit semper quis lorem. Sed ultrices tincidunt pharetra. Integer tempus nisi eu dolor varius dapibus. Ut scelerisque, justo quis pulvinar dapibus, dui augue fermentum dui, imperdiet commodo neque nisl ullamcorper augue. Nam lacinia arcu vel dolor bibendum, quis tempor elit luctus. Cras et lectus tempus, ullamcorper magna at, sodales diam. Morbi a fermentum magna. Donec id placerat felis. Phasellus imperdiet turpis ullamcorper scelerisque molestie. Phasellus tincidunt mattis enim, ac ullamcorper nulla sodales nec. 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Why are healthcare claims denied? Even the smallest mistakes on claims submission can trigger denials. Nearly 70% of providers say submitting clean claims is harder than it was a year ago, and 54% report an increase in claim errors, according to Experian Health’s 2025 State of Claims report. Some common reasons for healthcare claims denials include: Incomplete registration records: 26% of providers report that at least 10% of denials stem from inaccurate or incomplete data collected during registration. Missing patient information: Incomplete or incorrect patient data collected at registration triggers 32% of claim denials, according to Experian Health’s latest State of Claims report. Inaccurate insurance data: Outdated patient insurance information, missing coverage or mistakes made when entering insurance data during registration can lead to rejected or denied claims. Eligibility verification errors: Mistakes during manual eligibility checks or incomplete insurance eligibility verification are common causes of denials. Prior authorization issues: 35% of claim denials are triggered when prior authorizations aren’t obtained or don’t fully meet prior authorization requirements before claims submission. Coding inaccuracies: Missing medical billing codes and coding errors account for 24% of denials. Nearly half of providers say that coding errors are one of the top three most preventable claims errors in the latest Experian Health Claim Denial Management survey. Coordination of benefits (COB) errors: Coordinating benefits across several payers is a complex process and mistakes that lead to denials are common, especially when COB is handled manually.
Understanding contract management for healthcare Key takeaways: Contract management in healthcare is about negotiating, executing and monitoring agreements so providers can check that they are being paid in line with their contracts. Managing contracts across hundreds of payers and changing regulatory requirements is complex. Automation, AI and analytics can streamline contract oversight and identify discrepancies earlier. Tools such as Experian Health’s Contract Manager help providers audit payer performance, flag underpayments and manage contracts more efficiently across the contract lifecycle. The front-end data problem behind claim denials Experian Health surveyed 200 healthcare leaders from January to February 2026 to better understand the reasons for claim denials and opportunities for improvement. What are eligibility-related claim denials? Eligibility-related claim denials happen when a payer denies a claim submission for reimbursement due to patient insurance issues. Inaccurate or missing patient insurance information is a top denial trigger and often starts at the front end, during registration. Evolving payer eligibility requirements and new regulatory mandates also make it challenging for providers to avoid eligibility issues that can lead to denials. The most common causes of eligibility errors in healthcare billing 1. Mistakes made during patient intake: Eligibility-related issues often begin during patient intake – especially when providers use manual registration processes, like paper forms. Incorrect patient information entered on the front-end can cause eligibility issues that lead to billing mistakes, reimbursement issues and denials. Experian Health data shows that incomplete or missing insurance patient registration data is a top cause of claim denials, accounting for 32% of denials in 2025.
