The edit count does not identify the problem
I would begin with a specific edit family and a consistent definition of a new error. A claim can fail several edits, return after a correction, or appear in more than one workqueue. Counting each appearance as another defective claim makes the problem look larger and obscures which failure arrived first. My baseline would retain individual errors while reporting unique affected claims separately.
I would also distinguish claim edits from DNB holds and charge review exceptions. They may concern the same underlying data, but they operate at different points in billing. The investigation should establish whether an upstream control failed to catch the issue, an edit is unnecessarily duplicated, or the claim requires a legitimate downstream check. The presence of two controls is not itself evidence that one should be removed.
The data request should connect the error to its source
I would request edit identifiers, error messages, first and subsequent occurrence times, payer and claim definition, claim type, departments, workqueues, and the corrections users made. A sample of both resolved and unresolved claims is necessary. The resolved cases show what an effective fix actually changed; the unresolved ones show whether the assigned team can perform it.
I would ask the application team for claim definition configuration, the checks or rules attached to it, and the rules selecting records into claim edit workqueues. Those are separate pieces of the design. An edit can identify an error correctly while its routing sends that claim to the wrong team. I would include user instructions, owning areas, supervisors, and recent change history so that build review does not overlook how staff are expected to work.
The technical review needs two levels
In Epic, I would trace an example through error detection and queue selection. A claim definition can use configured edit checks or claim edit rules. The queue then uses its own selection criteria to identify which errored claims staff should see. I would obtain the relevant CER records where rules are involved, including context, referenced properties, parameters, and the configuration that uses the rule. An extension-based check requires review of its own supported configuration, not an assumption that a CER extract contains all of the logic.
I would compare the intended error code and ownership with actual behavior. A registration correction should not require the billing team to change protected payer or provider configuration. A master-file problem should have a clear escalation to an authorized build owner. Catch-all visibility also matters: claims that fail an edit but miss every specific operational queue still need someone accountable for investigating them.
I would also compare a claim in a specific workqueue with the complete error population for the same service area. That comparison can identify a gap in routing coverage without changing the edit itself. A missing specific assignment and an incorrect error result are separate findings.
The fix should reduce new errors and protect correct claims
I would validate the root cause with the originating department before proposing a change. For example, a missing provider attribute may require a provider maintenance process, while an incorrect visit setup may require a scheduling or department correction. The edit team should participate because it knows the practical correction, but it should not automatically inherit responsibility for preventing a problem generated elsewhere.
Acceptance testing should include a claim that genuinely fails, a claim that should pass, a corrected claim, a claim with several errors, and a claim for a payer outside the intended scope. I would verify both the message and the workqueue destination. Where instructions change, a staff member should be able to use them without additional verbal explanation. The team should also know how to escalate an unexpected increase after release and how to reverse the configuration change if necessary.
The scorecard should show recurrence
I would measure new affected claims divided by the relevant submitted or generated claim population for the same period and payer scope. I would separately report total edit occurrences, repeat failures after correction, and the number of claims with multiple errors. A lower queue balance with unchanged inflow usually reflects faster cleanup rather than prevention.
For throughput, I would track time from first error to a clean subsequent submission, along with unresolved older claims and transfer counts. A claim leaving one workqueue is not enough if it immediately fails another edit. The financial view should use appropriate collectible balances and actual progression to submission or payment, rather than summing overlapping queue balances. An operating review should then compare the same error family over several billing cycles and assign new findings to the department that can change the source. The objective is less repeat work with a control that continues to catch genuine mistakes.