7 reasons for claims errors and how to avoid them

by Experian Health 6 min read July 20, 2022

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The repercussions of errors on the healthcare claims processing workflow can be major and wide-ranging. It slows the revenue cycle, interrupts cash flow, consumes staff hours, creates frustration for staff and patients, and, in the worst cases, sacrifices revenue. Errors are a perennial—maybe even inevitable—problem but understanding some common reasons behind these mistakes can help. Additionally, digital claims management tools can help you automate claims processing to reduce claims errors, submit cleaner claims, and get paid successfully.

In June 2022, Experian Health surveyed 200 revenue cycle decision-makers to understand the current state of claims management. Watch the video to see the results:

Any number of claim errors can lead to denials: incorrect medical coding, missing prior authorizations, clearinghouse issues and more. Here are 7 of the most common reasons for claim errors:

1. Claim errors can be caused by missing and inaccurate data

“The number one denial issue most providers encounter is eligibility,” says Rob Stucker, Senior Vice President at Experian Health. “These issues begin upstream from the claims process during registration or pre-registration when the patient information that’s collected is either inaccurate or incomplete. It may be as simple as a patient giving their name as Rob instead of Robert, or the registration staff selecting Medicaid as the payer, instead of Medicaid Managed Care. If the eligibility information is even slightly off, the claim will come back as denied.”

Collecting accurate demographic and insurance information up-front using digital patient intake tools opens the digital front door and can help eliminate errors during the healthcare claims management process.

2. Manual processes and disparate systems

Wherever claims processes are not automated, human error and delays can set in. In addition to typical random glitches and mistakes, many healthcare providers struggle with disparate systems from multiple vendors, in which the front-end and back-end do not communicate seamlessly. Using a single vendor with solutions that manage the entire claims processing cycle can provide holistic help.

ClaimSource manages eligibility validation by repurposing Experian eligibility transactions that providers have already run at registration and editing them against the claim.  This process allows providers to double-check the eligibility of the claim before it gets submitted, at no additional cost. In addition, it also does extensive claim editing, submissions, reconciliations, and reporting. This solution creates prioritized workflows and provides access to a national library of documented government and commercial payer edits, as well as custom edits, to meet individual provider needs.

3. Changes in payer requirements can cause claims errors

“Providers tell us that a major pain point is constantly changing payer rules,” says Stucker. “Providers are confident that their claims are good, but the payers’ adjudication rules may have changed without prior notice.” The problem here is exponential: voluminous changes multiplied by a range of communication channels (or faulty communication) multiplied again by a proliferation of payers and policies.

Keeping pace with these changes is difficult without partner support. “We continuously monitor hundreds of thousands of payer website pages each night for updates,” says Stucker. “When a change is flagged, an analyst looks at it and decides whether it should be added as an edit. We update our huge global library of edits on a weekly or even daily basis. These edits enable ClaimSource and our pre-837 editor, Claim Scrubber to automatically review claims for errors using the most recent payer updates.

4. Prior authorizations

Pre-authorizations present challenges at many levels. 8 in 10 providers saw prior authorization requirements increase during 2021. Providers must track changing requirements, obtain authorizations prior to treatment or claims submission, and complete claims that meet complex requirements.

When prior authorization requirements aren’t met, appealing a denial can be complicated at best, and many times prove to be irreversible. According to Medical Group Management Association data, a simple denial takes a seasoned biller two to eight minutes to work, but a complicated denial involving prior authorization requirements can take up to an hour to work, largely thanks to time spent on hold. Ensuring claims are completed as required in the first place using a pre-authorization tool, in combination with a claims editor that validates against pre-authorizations, saves valuable time and stress.

5. Short staffing and new trainees

Staff hours and expertise are both in short supply, as many providers struggle to retain experienced staff and bring new hires up to speed. Having an automated process with built-in review and analytics can help ensure that claims are completed accurately and quickly. A Council for Affordable Quality Healthcare study found automated claims take 25% less time to process than manual claims, boosting productivity and freeing staff up for the more human-intensive aspects of their work. However, the key is “accurate and user-friendly” automation.

A claims vendor should be keeping edits up to date, submitting claims timely and accurately to the correct payer, keep organizations informed on the claim’s status throughout the adjudication process, retrieve electronic remit files, link them to the correct claims, and establish a denial workflow to automatically show denials. This should all be done in an extremely easy to use user interface or directly back into Patient Accounting/Practice Management Systems. If vendors aren’t doing this, then staff will just be working harder instead of smarter.

6. Slow response and follow-through can lead to claim errors 

Although delays themselves don’t necessarily cause errors, they can make resolution difficult and time-consuming. Time is always an issue for providers as claims must be submitted in specific time frames from the date of service. Therefore, getting the claim created, processed through a claims vendor and submitted to the correct payer must be done efficiently, or timely filing deadlines are missed.  The same is true for identifying and re-working denials. Denial backlogs quickly become overwhelming, increasing the odds of items slipping through the cracks or re-submission/appeal deadlines being missed.

Automating status updates with enhanced claim status monitoring can relieve time-strapped staff of having to contact payers manually for the latest information on claims to find out which ones are being paid or denied. Enhanced Claim Status submits automatic status requests based on each payer’s adjudication timeline from the date of claim submission, returning the payer’s proprietary responses weeks before the Electronic Remittance Advice or Explanation of Benefits are processed. This gives staff a huge head start on working denials.

7. Difficulty managing denials

When errors cause claims to be denied, a response is critical. A denials workflow management solution can optimize follow-up by identifying claim denials, holds, suspensions, zero-pays, and prioritizing denials that need the fastest attention. Denial Workflow Manager also allows organizations to track root causes, which in turn can identify operational changes that can be made upstream, and reduce the denials from happening to being with.

Automation is the future of effective claims management

Claims management is becoming more complex and demanding, but the digital tools that automate and improve processes can help providers rise to the occasion. It’s now possible to capture and use accurate data, integrate systems and processes to work together, stay up to date on payer requirements, track claim status, and even manage denials efficiently with the help of technology.

Learn more about other solutions that can help healthcare organizations with claims management.

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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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