Better Insight Yields Better, Faster Claims Payments

by Experian Health 3 min read November 5, 2014

It’s only natural to want to be fairly, fully and quickly reimbursed for services – it’s the basic foundation of business. Yet only in healthcare does attaining this basic transactional norm become challenging. Healthcare providers must be vigilant at all stages in the revenue cycle to ensure the amount they receive is timely and accurate.

Achieving this deceptively simple goal is dependent upon insight – the ability to discern the true nature of a situation and to respond appropriately. Applying insight at critical points in the claims lifecycle can make a marked difference in reducing denials and accelerating payment.

The foundation of a successful claims management strategy begins with contract management, where advanced analytics and data-driven insight can help you quickly and easily pinpoint payment variances and validate reimbursement accuracy for each of your third-party payers. Ensuring compliance with contract terms allows you to identify recurring issues so they can be promptly addressed, while providing the ability to strategically evaluate overall contract performance.

Once you achieve visibility of the contract process, you can apply those findings to other areas, such as claim scrubbing. Boosting the first-time pass through rate eliminates costly, time-consuming rework and speeds reimbursement. A strong claims scrubbing approach involves taking time, prior to submission to the appropriate payer or clearinghouse, to ensure the claim is complete, accurate and meets individual payer requirements.

Once the claim is submitted, it’s not a matter of “out of sight, out of mind.” Tracking claim status early in the adjudication process – rather than waiting for a denial to appear on your desk – helps improve cash flow and maintain a healthy revenue cycle. An online payer portal provides instant insight into the status of each claim and gives you the ability to determine if a claim is lost, denied, pending or being returned.

Regardless of how well you scrub claims before submission, it’s likely that a certain percentage will be denied. You can optimize and accelerate payments by quickly and efficiently identifying denied claims for analysis and re-submission. Use technology to ensure denied claims aren’t overlooked and streamline the workflow associated with claims management.

Finally, taking a comprehensive look at all pending claims and denials allows you to prioritize claims and denials so that your staff can work the highest impact accounts first to improve efficiency and increase revenues.

Advanced technology that provides insight into contracts, payer requirements, claims status and denials holds the key to reducing the claims processing errors that add an estimated $1.5 billion in unnecessary administrative costs to the nation’s health system. Few healthcare organizations can afford to receive less than their fair reimbursement for the care they provide. By implementing a strategic approach that grants insight into each component of the process, healthcare organizations can bolster the bottom line and streamline efficiencies along the way.

To learn more about how to turn these strategies into tangible results, register for our Dec. 3 Webinar, “5 Ways to Accelerate Your Claims Payments.”

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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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