A high balance is not a complete priority rule
The largest denied balance may have limited recovery potential, lack essential documentation, or already be waiting for a specialist. A smaller case may need an immediate action to preserve its opportunity. I would therefore establish which decisions a frontline user needs to make before designing a score or sort order.
The initial population should distinguish new denials, repeat denials, correspondence, and older unresolved cases. One claim can have several reasons or several follow-up records. The leadership view needs a reconciled financial population, while the working view needs enough detail to identify the next action. Sorting duplicated records by their associated account balance can consume effort without changing the amount the organization can collect.
The data should describe readiness as well as dollars
I would request denied amounts, expected recovery estimates where used, actual recovery and write-off activity, payer, reason and remark codes, claim history, and the team's recorded action dates. The request would include appeal or filing dates maintained in the local workflow, documentation status, clinical review needs, and current deferral reasons. A sample of completed cases helps test whether the data predicts a useful action.
I would ask supervisors how they distinguish an actionable case from one waiting on someone else. If the answer exists only in free-text notes, I would review a targeted sample before recommending additional structured fields. Every field added to a denial form creates staff work. The collection should support a decision, reporting need, or handoff that the team will actually use.
The Epic review should distinguish classification from routing
I would examine Owning Area, Source Area, Root Cause, Clinical Root Cause, and any local priority fields on denial records. Ownership should identify the resource responsible for the next step, not automatically blame the department associated with the original error. A clinical-validation dispute and a missing registration element may require very different resolution paths even if the payer uses similar broad codes.
For follow-up workqueues, I would review the selection logic, prioritization properties, allowed deferrals, and the actions that can close or reroute a record. Where CER rules are used, the extract should include context, property parameters, and the profile or workqueue references calling the rule. I would confirm actual account behavior before proposing a scoring change. A correctly populated reporting label does not prove that the case reaches the intended queue.
The priority design should lead to an action
I would define a small number of work patterns with the operations team. One might contain ready-to-submit appeals, another cases requiring clinical evidence, and another payer escalations with a documented next-contact date. The design should avoid moving cases into separate pools solely because a new label is available.
Within those patterns, I would use the organization's validated time limits, collectible amount, recovery evidence, and required effort to decide priority. A scoring system can help, but it needs a transparent explanation and a route for an urgent exception. I would compare its proposed order with experienced users' judgments and inspect the disagreements. That review often reveals missing information or a flawed assumption that a purely numerical score conceals.
Testing should include closure and return to work
I would test a denial with an imminent action date, a partial recovery, a request for clinical review, a new payer response during deferral, and multiple denial reasons on the same claim. Staff should be able to identify the next action and understand why the case appears in their queue. A change in payment or correspondence should result in the expected reevaluation.
I would pay particular attention to closure. A record can close because of a payment, a write-off, a replacement claim, or other activity. The operational result and financial result must remain distinguishable. I would verify how the local Epic version calculates recovery and how manual overrides affect reporting rather than treating every completed record as a successful collection.
The scorecard should reward resolved opportunity
I would measure the share of actionable cases receiving the required action within the agreed interval, with separate views for clinical handoffs and payer responses. The denominator should identify eligible cases and explain exclusions. I would also show cases beyond their action date, repeated deferrals, transfers, and reopened cases so apparent productivity does not hide deferred risk.
For financial performance, I would follow comparable, sufficiently mature denial cohorts to actual recovery and final write-offs. Expected recovery is a prioritization input, not cash. Cases shifted to another workflow must remain in the reconciled population. A lower average balance or more closed records is not enough by itself. The result should demonstrate that the organization directed the right resources toward recoverable and time-sensitive work while maintaining visibility into unresolved clinical or payer barriers.