5 ways health insurance discovery benefits healthcare organizations

by Experian Health 6 min read November 12, 2024

5-ways-health-insurance-discovery-benefits-healthcare-orgs

According to Experian Health’s State of Claims 2024 survey, missing coverage is the top reason for healthcare claim denials for almost a fifth of providers. However, the issue isn’t just about whether a patient is insured — four in ten providers worry about insurance companies paying out even where patients have active coverage. Constantly changing payer policies can result in altered or expired benefits, leaving providers scrambling to secure alternative sources of payment. That’s why many providers are turning to automated health insurance discovery to find missing coverage and catch outdated policies early.

This article looks at how coverage discovery software helps healthcare organizations address some of the most stubborn pain points in the revenue cycle.

What is health insurance discovery?

When a patient comes in for care, one of the first jobs is to figure out exactly what insurance they have — if any — and what it covers. Health insurance discovery is the process of checking whether the patient has active insurance and confirming details of that coverage, such as payer name and plan type, to ensure the cost of care is billed to the correct payer. If a patient has multiple active plans, the provider must also determine how much should be billed to each payer and in what order.

How does it work?

Ideally, coverage discovery occurs pre-service, but it can occur later if a claim is denied, and alternative coverage sources must be found. The main steps in the process include:

  • Collecting insurance details when patients schedule or check in
  • Checking with insurance companies to confirm that coverage is active and will cover planned services
  • Cross-checking payer databases to ensure no coverage is missed
  • Considering a patient’s eligibility for Medicaid or other charity support
  • Coordinating benefits for accurate billing

Benefits of automated health insurance discovery for providers

While respondents to the State of Claims survey are reasonably confident about their coverage discovery processes, the actual outcomes are less robust. Eligibility checks are taking longer and errors are on the rise. Only 54% of providers believe their claims technology can meet current revenue cycle demands. Automation offers a reliable and adaptable solution to bridge the gap between front-end checks and back-end claims management.

Here are a few ways automated health insurance discovery sets the stage for smoother claims submissions and revenue cycle performance:

1. Maximize reimbursement by finding missing coverage quickly

Challenge: Patients don’t always provide complete insurance information, which can cause providers to miss out on opportunities for reimbursement.

How automation helps: Automated health insurance discovery digs deeper than manual processes to find any coverage that may have been missed or forgotten. Experian Health’s Coverage Discovery® solution combs through multiple proprietary databases, including employer information, historical search information, registration history and demographic validation to proactively identify billable Medicare, Medicaid, and commercial coverage. With minimal patient details, it finds additional sources of primary, secondary and tertiary insurance instantly.

In 2023, Coverage Discovery tracked down previously unknown billable coverage in a third of patient accounts, resulting in more than $25 million in found coverage.

2. Reduce the manual workload

Challenge: Staff spend too much time calling payers, logging into portals and manually entering patient data. This is time-consuming and error-prone, especially when one in four resubmissions are worked on by a different person than the one who originally processed it.

How automation helps: Automation eases the admin burden by handling repetitive aspects of insurance verification behind the scenes, freeing staff to focus on more complex tasks. Coverage Discovery saves staff time by continuing to check for health insurance throughout the patient journey, and not just at registration. This final post-service check is vital to detect discrepancies that could lead to denied claims. Staff can also automate the self-pay scrubbing process to further reduce the risk of errors. As providers continue to feel the squeeze from staffing shortages and rising operating expenses, any move to reduce costs while bringing in more revenue is to be welcomed.

3. Prevent eligibility issues

Challenge: Providers often only discover that active benefits have changed after the claim has been submitted. That’s too late. For 43% of providers, it takes at least 10 more minutes to check eligibility when initial checks are incomplete.

How automation helps: With automation, providers can run real-time eligibility checks, ensuring that changes to the patient’s benefits are caught early so claims aren’t denied due to outdated information. Experian Health’s new Patient Access Curator uses artificial intelligence-based data capture technology to return accurate information from multiple sources with a single click. It automatically interrogates data from more than 270 payer responses, including active and billable coverage, plan level detail, chaining and primacy, so providers can verify eligibility and more in an instant.

4. Reduce claim denials and rejections

Challenge: Incorrect or incomplete insurance information results in errors on claims forms or claims sent to the wrong payer, which causes denials, delays and rework.

How automation helps: Automated discovery ensures that the correct payer and coverage information is attached to claims, reducing the likelihood of denial. This solves one of the most frustrating parts of coverage discovery, making the process faster, more accurate and less reliant on manual effort.

Read more: How to leverage AI and automation to minimize healthcare claim denials

5. Improves the patient experience

Challenge: Patients are often confused about their coverage status and worried about whether their healthcare costs will be met by their insurance provider.Medicare beneficiaries, in particular,report difficulty understanding and comparing plan options, leading to potential gaps in coverage.When healthcare providers fail to catch errors or gaps in their information, this erodes trust and negatively impacts how they feel about their experience.

How automation helps: By correctly identifying coverage and verifying benefits eligibility, automation allows providers to give their patients early certainty about how their healthcare costs will be covered. Patients are less likely to receive unexpected or incorrect bills, which prevents delays and disputes. Automated tools can go a step further to improve the patient experience by guiding patients toward additional support and payment plans. For example, Patient Financial Clearance identifies patients who may be eligible for Medicaid or charity assistance, and identifies appropriate payment plans for anyone with an unmanageable self-pay balance.

Case studies: See health insurance discovery in practice

Learn more about how automated health insurance discovery helps providers reduce claim denials, improve cash flow and deliver better patient experiences.

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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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