Healthcare claim denial statistics: State of Claims Report 2024

by Experian Health 5 min read October 4, 2024

Healthcare claim denial statistics State of Claims Report 2024

Claim denials are a well-documented challenge for healthcare organizations. Denied claims take much longer to pay out than first-time claims, if they get paid at all. Each one means additional hours of rework and follow-up, pulling in extra resources as staff review payer policies and figure out what went wrong. It’s time-consuming and costly. Beyond dollars and paperwork, denials affect patient care as uncertainty about payments leads to delays in treatment or unexpected out-of-pocket costs.

But how do healthcare leaders feel about the state of claims management today? How are they tackling the administrative burden? Is there any light at the end of the denials tunnel? Experian Health surveyed 210 healthcare revenue cycle leaders to find out.

The 2024 State of Claims report breaks down the survey findings, including insights into how automated claims technology is being used (or not!) to optimize the claims process and bring in more revenue.

What is the current denial rate for healthcare claims?

38% of survey respondents said that at least one in ten claims is denied. Some organizations see claims denied more than 15% of the time. That’s a lot of rework and lost revenue that providers were counting on.

In 2009, claims processing accounted for around $210 billion in “wasted” healthcare dollars in the US. A decade later, the bill had climbed to $265 billion. Industry reports—including Experian Health’s State of Claims series—repeatedly observed a rise in denial rates.

Today, 73% of providers agree that claim denials are increasing, while 67% feel it’s taking longer to get paid. Providers constantly worry about who will pay – and when.

What are the most common reasons for healthcare claim denials?

According to the State of Claim survey respondents, the top three reasons for denials are missing or inaccurate data, authorizations, inaccurate or incomplete patient info. In short? The problem is bad data.

Given how much information has to be processed and organized to fill out a single claim, this isn’t surprising. From patient information to changing payer rules, the sheer volume of data points to be collated creates too many opportunities for errors and omissions. On top of that, the rules are always changing. More than three-quarters of providers say payer policy changes are occurring more frequently than in previous years, making it increasingly difficult to keep up.

Other challenges, such as coding errors, staff shortages, missing coverage and late submissions still play a role, but it’s clear that solving the data problem could make a meaningful dent in the denials problem.

Read the blog: How data and analytics in healthcare can maximize revenue

Could automation improve claim denial statistics?

To help end the cycle of denials, more healthcare providers are turning to claims management software to resolve or prevent the snags that interfere with claims processing and billing workflows and boost claim success rates.

That said, around half of providers still review claims manually. Despite the proven benefits of integrated workflows and automation, the drive to implement new technology during the pandemic seems to have lost momentum: the number of providers currently using some form of automation and/or artificial intelligence (AI) has dropped from 62% in 2022 to 31% in 2024.

Could this be down to a lack of comfort with how new technologies work? Only 28% feel confident in their understanding of automation, machine learning and AI, compared to 68% in 2022.

For those who are curious but cautious, here are a few ways claims automation can help improve claim denial statistics:

  • Connect the entire claims process end-to-end: Using an automated, scalable claims management system like ClaimSource® helps providers manage the entire claims cycle in a single application. From importing claims files for faster processing to automatically formatting and submitting claims to payers, it simplifies the claims editing and submission process to boost productivity.
  • Submit more accurate claims: 65% of survey respondents say submitting clean claims is more challenging now than before the pandemic. There’s a strong case, then, for using an automated claim scrubbing tool to reduce errors. Claim Scrubber reviews pre-billed claims line by line so errors are caught and corrected before being submitted to the payer, resulting in fewer undercharges and denials and better use of staff time.
  • Improve cash flow: Automating claim status monitoring is one way to accelerate claims processing and time to payment. Enhanced Claim Status eliminates manual follow-up so staff can process pended, returned-to-provider, denied,or zero-pay transactions as quickly as possible.
  • Eliminate manual processes: While there are some tasks that genuinely need a human touch, too much staff time is wasted on repetitive, process-driven activities that would be better handled through automation. Denials Workflow Manager automates the denial process to eliminate the need for manual reviews. It helps staff identify denied claims that can be resubmitted and tracks the root causes of denials to identify trends and improve performance. It also integrates with ClaimSource, Enhanced Claim Status and Contract Manager, so staff can view claim and denial information on a single screen.
Experian-Health-Black-Book-Market-Research-Award-2024

Experian Health was client-rated #1 by Black Book™ ’24 in Denial & Claims Management Outsourcing, Health Systems.

Improving claim denial statistics with AI

While automation speeds up the denials workflow by taking care of data entry, AI can look at that data and recommend next steps. Current ClaimSource users can now level up their entire claims management system with AI AdvantageTM, which interprets historical claims data and payer behavior to predict and prevent denials. The video below gives a handy walk-through of how AI Advantage’s two offerings, Predict Denials and Denial Triage, can help providers respond to the growing challenge of denials:

As the survey shows, there’s a growing need for easy-to-implement solutions to the denials challenge. While progress has been made, the findings suggest there’s still room to use automation and AI more to prevent denials and level the playing field with payers.

Download Experian Health’s 2024 State of Claims report for an inside look at the latest claim denial statistics and industry attitudes to claims and denials management.

Related Posts

Andy’s New WP Workflow Test Article Using Quick Edit

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.

October 2, 2026 by Andy.Monte@experian.com
Experian Health ranked #1 in Best in KLAS for 2025

Experian Health is very pleased to announce that we've ranked #1 in the 2025 Best in KLAS: Software & Services report, for our Contract Manager and Contract Analysis product, for the third consecutive year. Contract Manager, when paired with Contract Analysis, empowers healthcare providers by ensuring payers comply with contract terms, identifying and recovering underpayments, and arming them with real claims data to negotiate contracts. This enables providers to negotiate more favorable terms and maintain financial stability.  Clarissa Riggins, Chief Product Officer at Experian Health, says, “In the ever-evolving healthcare landscape, our Contract Manager solution has once again been recognized as the #1 Revenue Cycle Management tool by KLAS for the third consecutive year. This prestigious ranking underscores the significant value our solution delivers to our clients by identifying underpayments and facilitating revenue recovery. We are honored to continue supporting our clients with innovative solutions that drive financial success and operational efficiency.”  Learn more about how Contract Manager and Contract Analysis can help your healthcare organization validate reimbursement accuracy, recover underpayments and boost revenue.   Learn more Contact us

February 5, 2025 by kelly.nguyen
How to increase patient engagement

Learn how providers can increase patient engagement, why it matters and key strategies that deliver improved end-to-end patient experiences.

January 30, 2025 by Experian Health

Spotlight test

Spotlight Description

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Sticky Subscribe Title

Sticky Subscribe Description
Sticky Subscribe

Testing Spotlight Paragraph block

Testing the spotlight block header

Archive Testing

Categories