Sustainable revenue cycle performance too often depends on heroics.

A revenue cycle can look healthy because experienced people know how to compensate for everything that is not.

They know which payer needs the workaround. Which eligibility issue has to be corrected manually. Which claim edit can be ignored. Which queue has to be checked every morning. Which problem has to be caught before the claim goes out.

And because they keep catching it, the KPI still looks good.

That creates a dangerous illusion: the organization sees the result, but not the hidden effort required to produce it.

A Good Metric Does Not Always Mean a Good Process

Revenue cycle leaders naturally manage to outcomes. Clean claim rate, time to bill, denial rate, aging, collections, and other indicators matter because they tell us whether the operation is producing the result we expect.

But a KPI usually tells us what happened. It does not always tell us how much work was required to make it happen.

Two organizations can report the same clean claim rate while operating very differently. In one, claims move through a well-designed workflow with minimal intervention. In the other, experienced staff manually correct eligibility, fix recurring edits, monitor payer-specific exceptions, and rescue problem claims before submission.

The reported outcome may be identical. The operational resilience is not.

Employee Expertise Can Hide Process Debt

Strong employees are supposed to solve problems. The risk appears when the organization begins to rely on those employees to compensate for broken or poorly designed processes.

Over time, workarounds become normal operating procedure.

• An eligibility problem is not redesigned because someone knows how to fix it before billing.
• A payer-specific edit is never eliminated because an experienced biller knows which claims can move forward.
• A workqueue is not automated because one manager checks it every morning.
• A denial pattern never reaches root-cause analysis because the A/R team is good at recovering the money.
• A provider documentation issue persists because a coder knows how to identify and correct it.

Each workaround can look small. Together, they create process debt: hidden operational fragility that accumulates because employee knowledge is substituting for system design.

The Problem Often Appears When the Person Disappears

Key-person dependency can remain invisible for years because the employee doing the work is highly reliable.

Then that person goes on PTO. Changes roles. Takes leave. Gets promoted. Or leaves the organization.

Suddenly, the symptoms become visible:

• Claims begin backing up.
• Time to bill starts increasing.
• Denials rise.
• Exceptions sit unresolved.
• Payer escalations stall.
• Other employees spend more time trying to understand undocumented workflows.

It is tempting to call this a staffing problem.

Sometimes it is. But often the staffing event simply exposed a process problem that had been there all along.

The 30-Day Question

One of the most useful questions an RCM leader can ask is:

Which of our metrics would get worse if one key person disappeared for 30 days?

The answer identifies where operational performance may depend more on individual expertise than on a sustainable process.

If the clean claim rate would decline, ask why. If time to bill would increase, identify which steps depend on that person. If a denial category would spike, understand what they were quietly preventing. If a payer relationship would deteriorate, determine whether escalation knowledge exists anywhere outside that employee’s inbox and memory.

The purpose is not to make employees interchangeable. Expertise is valuable. The goal is to make sure expertise improves the system instead of becoming the system.

How to Find Hidden Key-Person Dependency

Start by looking for processes where the organization hears statements like:

• “Ask Maria. She knows how that payer works.”
• “Only one person knows how to clear that queue.”
• “We have to check those claims manually.”
• “That edit always fires, but the team knows when to ignore it.”
• “If he is out, we usually wait until he gets back.”

Those statements are operational signals.

Then look at the work itself. Which tasks require repeated manual intervention? Which recurring exceptions are being managed instead of eliminated? Which processes lack documented ownership, escalation paths, or measurable root causes? Which KPIs remain strong only because employees are performing work that the metric never captures?

Fix the Process Without Losing the Expertise

The answer is not simply to document every workaround and call the problem solved.

Documentation can reduce risk, but it can also institutionalize unnecessary work. The better sequence is:

1. Identify the dependency. Where does performance rely on individual knowledge or intervention?
2. Understand why the intervention exists. What upstream defect, payer behavior, system limitation, or workflow gap created it?
3. Eliminate unnecessary work. Remove the root cause where possible instead of documenting the workaround.
4. Standardize what must remain. Create clear ownership, escalation paths, and repeatable processes.
5. Automate the right work. Once the process is sound, use technology to reduce repetitive effort and improve visibility.
6. Spread critical knowledge. Cross-train the team so expertise becomes organizational capability rather than a single point of failure.

A Sustainable Revenue Cycle Should Survive Normal Human Events

People take vacations. They get promoted. They change jobs. They get sick. Strong operations are designed with that reality in mind.

A good revenue cycle should benefit from excellent employees without requiring heroics from them every day.

The goal is not simply to produce a good number.

The goal is to build a process that can keep producing it.

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Want to Look for This in Your Own Revenue Cycle?

The free RCIL Revenue Leak Quick Audit includes this key-person dependency test along with 11 additional questions covering front-end revenue integrity, claim production, denials, hidden manual work, and other areas where revenue cycle friction can hide behind healthy-looking metrics.

Joe Jaccarino is the Founder & Principal of Revenue Cycle Insight Lab™, focused on practical approaches to revenue cycle operations, performance, analytics, AI, automation, and technology.