3 data-driven denial management strategies for faster claims processing

by Experian Health 5 min read November 4, 2021

In the sixth article in our series on how the patient journey has evolved since the onset of COVID-19, we look at three ways to prevent claim denials and reduce the time to payment. Faster claims processing is at the heart of a better patient financial experience and reduces revenue leakage for providers. For more insights and strategic recommendations to improve the patient journey in 2021 and beyond, download the full white paper.

Nearly seven in 10 healthcare leaders say claim denials have increased in 2021, with an average denial rate of 17%. Inefficient claims processing and claims management systems were already struggling, but the pressures of the pandemic are causing even more rejections.

Vaccination programs, rescheduled electives, and residency relocations contributed to fluctuating patient volumes, putting extra strain on reimbursement workflows. Patients switching health plans, and missing codes for COVID-19 vaccinations and treatment caused further delays and errors. Payer rules for reimbursement of treatment for “Long Covid” remain unclear: the absence of research and standards means claims are rejected because there’s no agreed “medical necessity.”

Slow processes, incorrect patient identities, and poor data management mean the upward trend in claim denials seen over the last five years shows that it is likely to continue. Denials create a fragmented experience for patients because they don’t know how much they’ll need to pay for care, and leaves providers battling to recoup revenue. An effective claims management system is critical for maintaining provider revenue, securing patient reimbursements, and promoting positive patient-provider relationships.

Here, we recommend a three-part strategy that uses data and automation to get claims right the first time.

  1. Prevention is better than cure

One of the primary frustrations for claims management teams is that the majority of denied claims are preventable. Many of the errors that trigger denials could be avoided if databases and records systems could talk to each other. Instead of a reactive response, providers should invest in tools that can proactively prevent mistakes and errors, to ensure they collect every dollar owed.

Digital tools can analyze data to help providers weed out the vulnerabilities in their processes and keep up with payer changes. Incorporating such tools is a sensible first step toward reducing and recovering expenses. One option is ClaimSource, which helps ensure that all hospital and physician claims are clean before being submitted to a government or commercial payer. It unlocks access to extensive federal, state, and commercial payer edits, allows custom provider edits, and incorporates automation tools and customer support. Providers can become confident that their claims will be correct the first time. Improving the likelihood of approval is critical to provider profitability and makes for a smoother patient experience.

  1. Prioritize eligibility checks for cleaner claims the first time

Experian Health’s revenue cycle management experts say that the number one reason for denials is inaccurate eligibility. A 2020 poll by the Medical Group Management Association (MGMA) backs this up: 42% of providers said inaccurate or incomplete prior authorizations were a top cause of denials. Most providers use a medical claims clearinghouse or have systems to check eligibility beforehand. However, if patient identities aren’t verified properly at every touchpoint in the healthcare journey, mistakes can creep in and cause confusion about eligibility. Similarly, if the patient needs additional treatment that isn’t covered in the initial authorization, the resulting mismatch could lead to a denial.

Tools such as Prior Authorizations and Insurance Eligibility Verification can help providers validate patient coverage in under 30 seconds. These solutions integrate with ClaimSource to fill in the gaps of patient information and streamline the claims process. Patients will get better insights into what they owe, and providers can increase efficiency.

  1. Automate workflows to eliminate time-consuming errors with claims processing

Providers are well aware that manual processing slows reimbursement and increases the risk of errors. Tools such as Prior Authorizations and Insurance Eligibility Verification can help by using data and automation to improve accuracy and efficiency. The Council for Affordable Quality Healthcare suggests that automation can shave 20% off claims processing times, which could translate to thousands of hours saved each month. With those extra hours, claims teams will be freed up to complete their lengthy to-do lists and focus their efforts on other priorities. In addition, automated workflows can help assign work to the right specialist, keep track of payer changes, and incorporate repeated identity verification checks to drive down denials.

With a Denial Workflow Manager, providers can automate and optimize their entire denial management process to get real-time insights on denied claims. This system can eliminate manual reviews and quickly identify accounts for resubmission or appeal. It can be integrated with tools such as ClaimSource and Enhanced Claim Status, so providers can monitor claims, denials and remits on the same screen and accelerate the workflow.

As the pandemic continues to pressure profits and patients come to expect more from their healthcare journey, it’s no longer reasonable to accept denials as a cost of doing business. To find out how Experian Health can help your organization reduce denials, recover pandemic losses, and improve the patient experience, contact our team today.

Missed the other blogs in the series? Check them out:

  1. 4 data driven healthcare marketing strategies to re-engage patients after COVID-19
  2. How 24/7 self-scheduling can improve the post-pandemic patient experience
  3. COVID-19 highlights an acute need for digital patient intake solutions
  4. Automated prior authorization: getting patients the approved care they need
  5. Getting a holistic picture of patients with social determinants of health

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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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