New survey on denial management in healthcare

by Experian Health 4 min read October 27, 2022

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In 2009, processing claims was listed as the second greatest contributor to “wasted” healthcare dollars in the US, at an estimated $210 billion. A decade later, that amount was estimated at $265 billion. Today, healthcare providers are still grappling with denied healthcare claims, with both challenges and solutions accelerated by the pandemic. To put the scale of operational and delivery changes into perspective, Experian Health recorded well over 100,000 payer policy changes for coding and reimbursement between March 2020 and March 2022. The implications for claims processing are immense, which is why healthcare providers need to reevaluate their denial management strategies and invest in new technology that can help increase reimbursements.

In June 2022, Experian Health surveyed 200 revenue cycle decision-makers to understand how they feel about the current situation. What are the priorities of those on the front line of denials management? And how can technology contribute to improvements? This article breaks down the key findings.

Takeaway 1: Denials are increasing and reducing them is priority #1

  • 30% of respondents say denials are increasing by 10-15%
  • Nearly 3 out of 4 respondents say that reducing denials is their top priority

For most respondents, claims management is more important now than it was before the pandemic, because of payer policy changes, reimbursement delays and increasing denials. Respondents attribute this to insufficient data analytics, lack of automation in the claims/denials process and lack of thorough staff training.

When it comes to improving denial rates, staffing seems to be the greatest challenge. More than half of respondents say staff shortages are slowing down claims submissions and hampering efficiency. Shrinking offices mean there is less staff to handle the growing volume and complexity of claims. It’s no surprise, then, that around 4 in 10 respondents are also concerned about keeping up with rapidly changing payer policies and keeping track of pre-authorization requirements.

Providers recognize that technology can help reduce denials while easing the burden on staff. A tool like ClaimSource manages the entire claims cycle using customizable work queues that make it easy to prioritize accounts, saving staff time and avoiding the errors that lead to denials. This also incorporates payer edits to ensure that claims are clean before being submitted to the payer. And if claims do end up needing further attention, Denials Workflow Manager eliminates time-consuming manual processes and allows providers to attend to high-risk claims quickly, so there’s less chance of delayed reimbursement.

Takeaway 2: Automating denials management in healthcare is critical

  • 52% of respondents upgraded or replaced previous claims process technology in the last 12 months
  • 51% are using robotic processes, including automation, but only 11% are using artificial intelligence

Prior to the pandemic, automation was sometimes perceived as a threat to jobs. But with changing employment patterns and evidence of the broader benefits of automation, attitudes are shifting. Automation can make life easier for staff by removing manual tasks to allow them to focus on other priorities. It speeds up the healthcare claims processing workflow, reduces the risk of errors, and enables better communication between providers, patients and payers.

Providers recognize that automation drives more efficient claims management. The survey revealed that 45% of respondents turned to automation to keep track of payer policy changes, 44% had automated patient portal claims reviews, and 39% had digitized patient registration in the last year.

Automation supports all stages of the claims management process, from auto-filling patient data during registration, to generating real-time claim status reports for back-office staff. Payer authorizations were a common challenge for providers, and a perfect fit for automation. Experian Health’s Prior Authorizations solution eliminates the need for staff to visit multiple payer websites, automates inquiries, and offers real-time updates on pending and denied submissions so staff knows when to intervene.

Takeaway 3: Providers are searching for denial management solutions that will achieve the greatest ROI

  • 91% of those likely to invest in claims technology say they will replace existing solutions if presented with a compelling ROI

The majority of providers may be on the lookout for better claims management solutions, but they vary in how they measure ROI. Predictably, one of the most common metrics is how much staff time can be saved, with 61% concerned with hours spent appealing or resubmitting claims, and 52% looking at time spent reworking claims versus reimbursement totals. Rates of clean claims and denials were also popular metrics, at 47% and 41%, respectively.

Using Denials Workflow Manager and ClaimSource alongside additional claims management solutions like Claim Scrubber and Enhanced Claim Status can deliver an even stronger performance against the above metrics. Each solves a specific challenge within the claims management workflow, but when used together, the ROI is multiplied.

Overall, there’s optimism that digital technology and automation can help healthcare providers improve claims and denial management and reduce the amount of “wasted” dollars. This survey shows that providers are keen to grasp the opportunities offered by automation to optimize the reimbursement process and get paid sooner.

Download the report to get the full results on the State of Claims 2022, and discover how Experian Health can help organizations with their denial management strategies.

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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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