6 steps to improving the claims adjudication process

by Experian Health 9 min read May 16, 2024

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“Is this claim valid? How much is our financial responsibility?” These are the two big questions payers want to answer when adjudicating healthcare claims. Huge amounts of patient information, clinical data, diagnostic and billing codes, and policy specifications must be analyzed and cross-checked to verify that the right amount is paid to the right party. It’s a complex process. Even the smallest error can result in a claim being rejected or denied, dragging out payment timelines and eating up provider profits. That’s why healthcare providers should reevaluate their claims adjudication process.

Experian Health is pleased to announce that we’ve ranked #1 in Claims Management and Clearinghouse, for our ClaimSource® claims management system, according to the 2024 Best in KLAS: Software and Professional Services report.

The claim adjudication process is a pivotal step in the revenue cycle and determines a provider’s reimbursement for services rendered. It’s a complex process with many moving parts, which means errors or delays can occur at many points along the way. A smooth, streamlined system can reduce the amount of time and money spent on claims adjudication for both the payer and the provider. Here are six steps to improving claim adjudication processes for a better bottom line.

What is claims adjudication?

Claims adjudication is the process by which insurance companies thoroughly review healthcare claims before reimbursement or payout. During this process, they decide whether to pay the claim in full, pay a partial amount, or deny it altogether.If more information is needed, the claim will be rejected and marked as “pending.”

Insurance companies employ this systematic procedure to determine the validity, accuracy, and eligibility of claims against the terms and conditions of their policy. During claims adjudication in healthcare, insurance payers assess the documentation provided by the service provider, examining factors such as the nature of the services, coverage details, and any applicable deductibles. The process can take weeks to resolve itself. This evaluative process ties up billions of dollars in an endless cycle of claims denials and resubmissions.

Following this evaluation, the provider will reject or settle the claim. Additionally, claims adjudication may lead to partial settlements or modifications based on the assessment of the claim. By all accounts claims denials are exceedingly common; a recent Experian Health survey showed that these numbers have increased by up to 15% annually.

Healthcare providers can implement several steps to mitigate the risk of denials, enhance the efficiency of claims adjudication and get paid faster.

Steps to improving the claims adjudication process

The healthcare reimbursement process is bogged down with manual tasks that create errors. Experian Health’s State of Claims 2022 report revealed that the most common claims errors include:

  • Missing or incomplete prior authorizations
  • Failure to verify provider eligibility
  • Mistakes in medical coding

Yet providers have new technologies at their fingertips to improve how and when they get paid. McKinsey reports on data showing that applying the latest artificial intelligence (AI) and automation digital tools to the revenue cycle could save healthcare providers up to $360 billion annually. That makes these tools a kind of adjudication insurance to protect providers against costly claims denials. Here are six ways to apply technology to improve the claims adjudication process.

Step 1: Invest in automation

Some of the benefits of automating healthcare claims management include:

  • Streamlined operations with fewer human errors.
  • Less staff time tied up in claims adjudication.
  • Better data with real-time insights into patient and payer trends.
  • Faster claims processing—and faster payment.
  • Better patient experiences.
  • Happier staff.

Applying AI and automation to claims management can eliminate errors by allowing the technology to validate and cleanse data at the point of entry. Tools like Experian Health’s Claim Scrubber can thoroughly review each line of claim data in seconds. Alerts can flag a human attendant, allowing them to correct mistakes before claim submission.

Automation technology like the Enhanced Claim Status streamlines the revenue cycle by tracking the claims adjudication process in real-time. Instead of submitting a claim and awaiting the payer’s response, this technology provides claim statuses within 24 to 72 hours.

Step 2: Prevent delays with front-end edits and save time spent in claims adjudication

How much time could providers save by correcting front-end mistakes before the claims adjudication process begins?

During claims adjudication, payers will compare claims data to payer edits, to make sure billed services are coded correctly. Therefore, providers must keep pace with current coding requirements and the universal, local and payer-specific edits that apply.If claims are not correct the first time, they’ll fail the payer’s initial automated review, and may be denied or pushed into a queue for manual review by a claims examiner, leading to inevitable delays. Front-end claims editing tools can find errors that might prevent reimbursement, such as missing prior authorization or coordination of benefits codes.

Patient Access Curator, Experian Health’s latest revenue cycle data curator package, helps healthcare providers eliminate errors quickly on the front-end. This solution uses AI to perform eligibility, COB, Medicare Beneficiary Identifier (MBI), demographics and discovery in a single solution, preventing denials at the front end with a single click, within seconds.

Experian Health’s ClaimSource® solution allows organizations to implement customized edits and rules tailored to specific payer requirements. These edits help catch errors related to coding, billing, or other aspects of the claim, preventing inaccuracies from progressing to claims adjudication. While the industry average for claims denials is 10% and higher, Experian Health clients who use ClaimSource have a typical denials rate of just 4%. That’s one reason Experian Health’s ClaimSource solution earned the top KLAS ranking for the second consecutive year.

Step 3: Streamline record-keeping and data management

Electronic record keeping plays a pivotal role in ensuring accuracy in healthcare claims. These platforms allow centralized storage of patient data, including medical history, treatment plans, and billing information. Electronic record systems can enforce standardized coding practices, ensuring that medical codes used for billing and claims adhere to industry standards. They also maintain detailed audit trails, documenting all changes and updates made to patient records. This level of accountability enhances accuracy by allowing organizations to trace any modifications and ensure data integrity throughout the claims adjudication process.

Notably, electronic record-keeping systems seamlessly integrate with healthcare claims management systems. Integration ensures that the information entered into electronic health records (EHR) automatically populates relevant fields in the claim, minimizing the need for manual data entry and reducing the risk of transcription errors.

Step 4: Automatically review coding for accuracy

Coding errors can result in claim denials and delay reimbursements to providers. For example, manual coding introduces the risk of typos or misinterpretation of the medical record. Because of the complexities of payer requirements, an incorrect procedure or diagnosis code could trigger claim rejection. Some procedures require supporting documentation or pre-verification before treatment. At the same time, ICD-10 (codes for patient diagnosis) and CPT codes (that identify services rendered) undergo regular updates. Failing to stay on top of these coding systems increases the risk of a rejected claim.

The solution is to apply AI and automation to improve the chance of claims adjudication success. Two solutions from Experian Health include:

  • AI Advantage™ – Predictive Denials uses AI to spot documentation errors before the claim goes to adjudication. The solution automatically flags claims with a higher potential for denial, allowing the revenue cycle team to fix errors before claim submissions. For claims that have already been denied, AI-Advantage Denial Triage identifies and prioritizes high-value denials, so teams can focus on remits with the highest impact.
  • Denial Workflow Manager allows providers to quickly identify denied claims early in the claims adjudication process. Remittance details show providers the steps necessary to amend the claim quickly for a higher chance of reimbursement. Intelligent data-driven denial analytics spot the root causes of denials, so remedial action can be taken.

Step 5: Create clear patient communication channels

Clear patient communication channels are essential for preventing errors in healthcare claims adjudication. Incorrect patient information can result in claim denials, causing delays in reimbursement and impacting both patients and healthcare providers. Automated patient outreach technology significantly enhances communication while reducing the likelihood of errors. Solutions like Patient Access Curator also work to capture accurate patient data at registration – all in a single click.

Electronic patient portals, powered by automation software, can also solve this challenge. These portals empower patients to update their information directly, ensuring the accuracy of data submitted with claims. Patients can verify and input their demographic details, insurance information, and other relevant data through user-friendly interfaces. Electronic patient portals significantly reduce the risk of errors in patient information by minimizing manual data entry and streamlining the information-sharing process. These tools enhance the efficiency of the claims adjudication process, reduce the likelihood of denials, and promote a smoother experience for patients and healthcare providers.

Step 6: Advocate for policy change

Moving towards claims adjudication automation with uniform industry standards can save providers and payers time and money. Currently, each payer operates within their unique silo of ever-changing reimbursement requirements. A lack of standardization means providers spend hours checking claims against payer requirements.

The first step toward industry standardization requires automation technology to eliminate these time-consuming manual processes. Digital solutions like Experian Health’s online prior authorizationsoftware update requirements directly from payer websites, giving providers a better shot at submitting a clean claim.

Advocating for healthcare policy change toward greater automation and more uniform industry standards is a strategic move that will save time and money and foster a more efficient, transparent, and technologically advanced healthcare ecosystem. This transformation will improve patient care and overall system sustainability.

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

Improving healthcare claims management with Experian Health

Today, nearly 20% of all healthcare claims are denied, and 60% are never resubmitted. That ties up significant revenue in the claims adjudication process. However, better claims management processes can yield reduced denials and faster payments.

Experian Health offers a complete ecosystem of tools to deliver cleaner claims and faster reimbursement. This suite of products creates an integrated technology ecosystem with a track record of increasing the speed at which healthcare providers get paid.

Find out more about how Experian Health’s Claims Management solutions can support a more streamlined claims adjudication process.

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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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