Case study: Accelerate cash flow by automating claims management

by Experian Health 3 min read January 6, 2023

Case-study-Accelerate-cash-flow-by-automating-claims-management

Hattiesburg Clinic is Mississippi’s largest multispecialty clinic with over 450 physicians serving 19 counties. Claims management, patient collections and payer contract management are handled by the clinic’s Financial Services Department, which includes around 70 staff members.

Challenge

Hattiesburg Clinic in Mississippi sought to improve financial performance in the wake of the COVID-19 pandemic by focusing on reducing claim denials. The Financial Services Department had been hit by staffing shortages, which affected financial results. A more efficient digital claims management solution would attract and retain a high-performing virtual team, while supporting the shift away from existing paper-based systems.

To submit more clean claims the first time, the Department set specific goals to:

  • meet or exceed Epic benchmarks for primary denials
  • maintain accounts receivable (AR) days at 42 or less
  • process secondary and tertiary claims without waiting for the primary electronic remittance advice (ERA) to be posted.

Solution

Already impressed with Experian Health’s Contract Manager and Eligibility solutions, the Department chose another Experian product, ClaimSource®, to help reduce denials. Loretta McLaughlin, Assistant Director of Financial Services, said she was confident ClaimSource was a good candidate for the clinic’s claims platform:

“ClaimSource seemed like the right fit for the department’s goals. The platform’s ability to customize edits, along with the level of customer support available, really set the solution apart from the alternatives.”

ClaimSource uses scalable automation to prioritize claims, payments and denials. This allows staff to use their time as efficiently as possible, by working on the highest-impact accounts first. Using customizable edits and extensive national and local payer edits, it checks each claim for inconsistencies before the claim is submitted. ERA data is automatically integrated into Epic so that staff can check a claim’s status quickly and easily. With real-time reporting, staff gets insights from across the entire claim lifecycle to improve performance.

Outcome

The ability to integrate customizable edits was a big advantage for the clinic. They now have over 90 custom edits that help eliminate time-consuming errors, reduce denials, and allow staff to focus on the right accounts.

As a result, Hattiesburg Clinic has achieved a 6.1% primary denial rate, which exceeds the Epic Financial Pulse benchmark. Despite staffing shortages, they’ve been able to accelerate receivables. They’re also seeing accelerated cash flow, now they can pursue claims from secondary and tertiary payers without awaiting the outcome of primary claims adjudication.

ClaimSource is also creating a better staff experience: the tool eliminates the need for claims to be printed, so staff can work from any location. Now, over 50% of the team work from home. Thanks to automated workflows, output has been consistent despite a reduced workforce. Being able to submit clean claims the first time has a positive impact on AR days as well as staff workload.

Loretta McLaughlin says: “Through ClaimSource’s automation and level of quality work, we have had to do less manual intervention.”

To build on this success, the team intends to explore further opportunities to use automation to improve productivity. Options include automatically generating patient estimates, automating bad debt and refund workflows, and allowing patients to verify insurance eligibility through their patient portals.

Find out more about how ClaimSource helps hospitals, health systems and physician groups reduce denials, protect profits and increase productivity through automated and scalable 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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