Streamline coordination of benefits (COB) for fewer claim denials

by Experian Health 6 min read March 27, 2024

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Healthcare leaders often zero in on how uninsured rates affect their bottom line. But another patient group presents a quieter financial dilemma for providers: those with multiple active health plans. In these cases, it’s important to ensure each plan pays the right amount – in the right order. Should any confusion arise, providers may end up with their claims being denied, resulting in underpayments. This is where the coordination of benefits (COB) process comes in.

What is coordination of benefits (COB) and why is it important?

When a patient is covered by more than one plan, the “coordination of benefits” process kicks in to help health plans figure out their respective payment responsibilities. With patients often having multiple insurance policies, ensuring that each policy pays its share is vital. The purpose of coordination of benefits is to prevent overpayment or duplication of benefits, ensuring that the total benefits paid do not exceed the actual cost of the service received. Integrating a digital COB solution within registration and scheduling workflows can help providers ensure they bill primary and secondary payers correctly, preventing unnecessary claim denials.

Challenges of coordination of benefits

Coordination of Benefits is a pivotal aspect of RCM, but it’s not without its hurdles. Here’s a look at the complexities that often arise:

  • Overlapping Policies: Determining which policy pays first can be confusing. Patients with dual coverage might not always be aware of the hierarchy, leading to billing complications. And many legacy systems only select the primary, without consideration for secondary or tertiary. And regional plans add another layer of complexity.
  • Claim Denials: Incorrect coordination of benefits can lead to claim denials or overpayments. This not only affects revenue but also strains the patient-provider relationship when patients are billed incorrectly.
  • Administrative Burden: Manual COB verification is time-consuming and prone to errors. Staff often spend hours cross-referencing policies, which could be better spent on patient care.

Coordination of benefits: the dream vs. reality

In an ideal world, patients would register for care weeks ahead of their scheduled treatment. During the registration process, they would inform the provider of all their active insurance coverage, with correct and complete details close to hand. No plan would go unmentioned, and no policy number misplaced. Registration staff would quickly enter the information into their EMR without error, so coverage could be verified in real-time.

The reality is far different. Recent findings show that 65% of consumers struggle to understand what their health insurance covers. They do not carry copies of their insurance cards. They may not be aware that they are covered under a relative’s health plan. Patient access teams are under-staffed and over-stretched, with little time to ask guiding questions that would uncover additional insurance.

Coordination of benefits efforts should start as soon as it becomes apparent that a patient has active coverage under multiple plans. Unfortunately, the messy reality of coverage discovery and patient registration means patients and providers are left in the dark until a claim is denied. The payer rejects the claim for a COB-related reason, leaving billers with no clue how to resolve it. The problem gets worse from there.

Automating coordination of benefits for faster, cleaner claims

As with all aspects of healthcare billing, there are many complex rules and regulations governing COB transactions. Under HIPAA, health plans and payers (including Medicare and Medicaid) must coordinate benefits for each patient and determine the primary and secondary payers.

Tracking this manually is extremely challenging for providers: using the information provided by the patient (which may or may not be accurate), staff would contact each payer by phone or email to verify coverage. They would then review the COB rules and guidelines for each health plan to determine the primary payer and follow specific rules for billing secondary payers. It’s no wonder that COB transactions are now among the most automated administrative tasks.

Automating coordination of benefits not only saves staff time, but also increases the chances of finding all active coverage, collating complete insurance profiles for the patient, and making an accurate primacy determination. Digital systems also make it easier for providers and payers to communicate with one another, facilitating smoother dispute resolution and regulatory compliance.

Patient Access Curator brings real-time COB to EH clients

In late 2023, Experian Health acquired Wave HDC, bringing clients a new and unrivalled package of real-time coverage and benefits solutions based on AI-powered data curation.

This new solution, Patient Access Curator, helps healthcare billing teams prevent claim denials in seconds through real-time data analysis. This includes COB curation, which automatically analyzes payer responses to identify hidden cues that staff cannot see. If other insurance is identified, the tool alerts the user and triggers additional queries to verify active coverage and build a complete insurance profile for the patient. Each policy is then analyzed further to determine the patient’s primary, secondary and tertiary coverage, reliably sifting out any non-billable coverage.

Since 2020, the technology powering Patient Access Curator has prevented denials amounting to more than $1 billion.

Integrating coordination of benefits automation yields savings throughout the revenue cycle

Integrating COB automation with other RCM tools, such as coverage discovery and eligibility verification, means providers can prevent and manage denials in a single workflow. Doing this during patient registration allows teams to resolve issues in the early stages of the revenue cycle, rather than wait to deal with them once claims are denied.

While catching errors on the front-end results in faster patient registration and clean claims first time, the tool adds value later in the revenue cycle, too. Streamlining the correction process prevents revenue loss and reduces the need for manual intervention.

Here’s how these use cases look in practice:

  • In one multistate practice, the technology automated COB curation with insurance verification during patient registration. This enabled primary coverage corrections for 12% of patient registrations and identified undocumented Medicare and Medicaid coverages for 6% of registrations. Left unchecked, these omissions would have resulted in denials, delays, and missed revenue opportunities.
  • The technology was deployed in the denials workflow at a large health system, where it identified COB corrections for 92% of all COB denials. Of these, 60% were immediately refiled to the correct primary payer, minimizing delays in revenue recovery. In the remaining claims, the tool found evidence of inaccurate or outdated third-party liability records within payer claim adjudication systems.

Providers urgently need revenue cycle processes to be as efficient and reliable as possible – especially when dealing with patients with multiple, complex health plans. A powerful denial prevention solution that slots neatly into the registration workflow means they can maximize revenue with minimal human intervention. And with accurate results delivered in seconds, Patient Access Curator could be just what the doctor ordered.

Get in touch today to find out more about coordination of benefits automation and discuss other ways to increase efficiency on the front-end of the revenue cycle, using Patient Access Curator.

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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. 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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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