Registration and eligibility errors are the single largest cause of claim denials, accounting for roughly a quarter of all denials year after year, according to the Revenue Cycle Denials Index. That's worth sitting with. Eligibility verification exists specifically to catch coverage problems before a patient is ever seen, so when a denial traces back to eligibility, it means the problem was sitting there, findable, before the claim was ever submitted. 

So, here's what eligibility verification confirms, where it tends to break down, and how practices can improve accuracy. 

What Is Eligibility Verification in Healthcare? 

Eligibility verification is the process of confirming a patient's insurance coverage before or at the point of care, rather than discovering coverage issues after a claim has already been submitted and denied. It's typically done through a 270/271 transaction, where a practice sends a real-time request to a clearinghouse and receives a response confirming the patient's coverage. 

Done correctly, eligibility verification confirms three things: 

• Coverage status: whether the patient's insurance is active and applies to the scheduled service 

• Patient responsibility: what the patient is expected to owe out of pocket under their specific plan 

• Plan details: deductibles, copays, coinsurance, and any relevant coverage limitations 

This step is critical for two reasons. First, it gives the patient an accurate cost estimate before their visit instead of a surprise bill after it. And secondly, it's the first line of denial prevention, the point where most eligibility-related denials could have been caught. 

Common Eligibility Verification Errors 

Most eligibility errors come from a few common causes: 

A one-time check. A clearinghouse check tells you what's true at the moment you run it. Run it once at scheduling and never again, and you miss every coverage change between booking and the visit date, especially with how often patients switch plans or hit deductible resets close to their appointment. The earlier the check, the staler the answer by the time the patient shows up. 

Incomplete or inaccurate patient data. A misspelled name, wrong date of birth, or mismatched insurance ID is enough to return an incorrect eligibility result or cause a downstream denial, even when the coverage itself is valid. 

Not every policy on file gets checked. When a patient has more than one policy, checking only the primary plan misses details that change what the patient owes. 

Manual verification delays. Calling payers directly can catch what automated checks miss, but it's slow and labor-intensive, and doesn't scale well when a practice is trying to verify dozens or hundreds of patients a week. 

Treating verification as a one-time compliance step. Coverage can change close to the appointment date, especially with frequent plan switching. A check done too early loses accuracy by the time the patient actually arrives. 

The Consequences of Eligibility Verification Errors 

Start with the denials themselves. MGMA estimates that 50 to 65 percent of denied claims are never reworked at all, meaning that revenue isn't delayed; it's gone. The claims that do get reworked aren't free either: MGMA puts the average administrative cost at $25 per claim, a number that compounds fast at volume. 

Then there's the patient's side. A patient who wasn't given an accurate estimate before their visit is far more likely to dispute or delay the bill after it. It undermines the exact transparency the No Surprises Act's Good Faith Estimate requirement was built to create. 

How to improve eligibility verification 

• Verify more than once. Check at scheduling, then again close to the visit date. Coverage changes between booking and appointment are common enough that a single early check is closer to a guess than a verification. 

• Don't treat the first result as final. When a check comes back incomplete, ambiguous, or inconsistent with what the patient told you, escalate it, whether that's a second data source, a payer portal check, or a direct call. 

• Decide how confident is confident enough. Set an internal standard for how reliable a result must be before it reaches a patient as an estimate. Without a defined bar, every result gets treated as fact, regardless of how solid it actually is. 

• Keep a human in the loop for hard cases. Automation handles volume well, but it doesn't resolve every edge case. Unusual plans, conflicting responses, and missing data need a person with eligibility expertise, not an automated best guess. 

• Standardize intake and check every policy. Clean data capture at registration and a routine check of all policies on file to eliminate two of the most common error sources before verification even starts. 

None of this is complicated. It's discipline: the same checks, in the same order, for every patient, every time. The hard part is that doing it manually is exactly the workload most practices can't absorb. 

This is the process to verify, escalate, confirm, and only then hand the patient a number. Myriad MediPay follows this method to automate end to end, from eligibility through the Good Faith Estimate to collection. If you'd rather see it than read about it, explore a live eligibility account through Myriad's demo.