7 ways to prevent costly claim denials

by Experian Health 4 min read July 30, 2019

Managing the revenue cycle draws in considerable resources for healthcare organizations, even when it’s working as planned. The American Medical Association puts direct transaction costs and inefficiencies associated with the “claims management revenue cycle” at around 25-30% of overall healthcare spending. But when errors are made and claims end up being denied, providers could end up missing out on as much as   The total revenue leakage is probably higher, when you consider the opportunity cost of staff time spent sorting out denials.

Among the most common reasons for denials are missing or incorrect billing information, non-covered charges for care, and absent authorizations. Thankfully, these are all issues that can be minimized with the right strategies and tools.

By optimizing your revenue cycle from the outset so that claims are right first time, you can save hassle and expense later on.

Here are 7 ways to proactively reduce claim denials in your health system.

  1. Figure out why claims are denied

First things first. You need to understand where denials are occurring in your revenue cycle and why. You can determine the root cause of denials by analyzing data that’s already available to you alongside information on industry trends. A business intelligence tool can help you use advanced data analytics to find opportunities for improvement, and generate actionable insights that are focused on your specific KPIs. Once you know where the weak points are, you can get the ball rolling with solutions.

  1. Prioritize the big-impact fixes

In all likelihood, most providers will have the opportunity to improve the claims process at several points in the revenue cycle. You can’t do everything at once, so identify the areas with the greatest potential impact on your hospital’s bottom line. Can denials be traced to a particular department, service line or physician? Has a certain payer changed their approach? Compare the cost of implementing processes to tighten up the weak points in the cycle with the amount of revenue likely to be recovered to ensure you get the biggest ROI for your efforts.

  1. Automate patient access for more accurate claims

Up to half of denied claims occur early in the revenue cycle, during patient access and registration. Automating the patient access workflow with real-time data can create a more efficient and accurate process, linking front and back office staff with shared systems that minimize errors and staff time.

Martin Luther King Community Hospital experienced these efficiencies first-hand, when they integrated eCare NEXT® within their existing Cerner® system. As a result, their registration process became more streamlined, enabling them to cut two to three minutes from more than half of their registrations.

  1. Ensure patient matching is as accurate as possible

Incorrect patient matching is a major source of revenue leakage for many providers, with around a third of claims denied on the basis of inaccurate patient identification. When it costs $25 to rework a claim and around $1000 for each mismatched pair of records, that’s a lot of lost revenue. Resolve your patient identities with the most robust data sources, and not only will you reduce claim denials, you’ll also have a more complete picture of each patient, which in turn will give them a better patient experience.

  1. Streamline prior authorization checks

A survey by the American Medical Association found that prior authorization checks created a substantial burden for providers, with physicians spending an average of nearly 15 hours per week dealing with related tasks. For patients, this process can lead to delayed or even abandoned treatment. Using automated software, you can check claims against payer rules for medical necessity, frequency, duplication and modifiers, so you can quickly spot any claims that may be denied and correct them before submission.

  1. Process claims effectively

Once you’ve streamlined the front-end of the claims process, you should of course look for ways to improve efficiencies throughout the rest of the cycle and immediately before the claim is sent to the payer. In fact, providers are expected to invest up to  , as the need to crack down on denials grows.

Submitting claims in the correct format is a common and frustrating challenge. Since each payer has different requirements and formatting preferences for claim forms, edits should be customized. A revenue cycle service provider can help you build these custom edits and check each claim line by line, so you can submit with confidence and avoid having to redo them later.

  1. Monitor and analyze your revenue cycle

Regular analysis is essential to consistently improve denial rates. By monitoring your internal processes across a range of metrics, you can gain a holistic view of the entire revenue cycle to see where there are further opportunities to optimize performance and prevent denials. When you have confidence in the freshness and accuracy of your data – including patient access data, payer performance information and patient matching – you can make confident decisions about exactly what needs to happen to improve your claims denials.

Learn more about how leveraging data-driven insights to tighten up your claims management systems and take proactive steps to find lost revenue.

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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.

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