Case Study 2 — The Two Positions: A Composite

Constructed. The organization and the figures are not real. The decision — reducing front-end staffing because its cost is visible and its output is not — is entirely ordinary, and this is the only case study in this book where the failure was a deliberate management decision, correctly reasoned on the numbers that were available.**

Background

Section 24.10 stated the structural problem in one line:

The front end is measured by the back end's failures, and it is staffed by the front end's budget.

This is what that sentence produces when somebody is under pressure to reduce cost.

The composite

Constructed.

A multi-site practice. A new administrator is asked to find savings, and does the sensible thing: looks at where the money goes.

Patient access is an obvious candidate. Its staff are among the lowest-paid in the organization, there are a lot of them, and — this is the crucial part — their output does not appear on any report.

She looks for evidence that the function is producing value. She finds none, and she is not being lazy: the organization does not measure the front end at all. No verification rate, no authorization capture rate, no front-end denial classification. Chapter 24 §24.10's five measures do not exist in this practice, and it is not unusual in that.

She eliminates two positions across the sites and redistributes the work.

The saving is real, immediate, and appears on the report she was asked to improve.

What happened over the following eight months

(Constructed.)

Nothing, for about six weeks. Registration continued. Patients were seen. Claims went out.

Then the denials began arriving, because that is how long the cycle takes: an error made in week one becomes a claim in week two, adjudicates in week five, and enters a work queue in week six.

The denial volume rose, and it rose in specific categories:

• Eligibility — verification skipped under time pressure, or run at check-in only
• Authorization — services performed without one, because nobody had time to check the list
• Coordination of benefits — the MSPQ administered inconsistently
• Registration data — names, dates of birth, member numbers

The business office noticed the volume and reported it.

And the organization responded by adding a position in the business office.

Why that response made sense

This is the part worth taking seriously, because the response was not stupid.

The problem presented as a business office problem. The queue was in the business office. The overtime was in the business office. The manager raising it was the business office manager, and what she said was true: we cannot work this volume with current staffing.

Nobody had a number connecting the two events. The front-end reduction and the denial increase were six weeks and two departments apart. There was no report on which they appeared together, and the person who would have had to notice — someone holding both budgets and both operational pictures — did not exist.

And the added position worked. The queue came down. From the report's point of view, a problem was identified and solved.

The arithmetic nobody did

(Constructed, and the figures are illustrative.)

Two front-end positions eliminated. One business office position added. Net headcount: minus one. The saving is real.

Now the part that was not counted.

Every denial worked costs staff time — §24.1's thirty to sixty minutes for a worked denial, against half a minute for the same error caught at registration. A ratio of roughly ninety to one.

Some denials are not won. Chapter 29 covers overturn rates; the ones that are not won are not costs — they are lost revenue, which does not appear on a staffing report at all.

Some hit timely filing. Chapter 18's Case Study 1 and Chapter 14's Case Study 2 both ended there.

And the patient experience degraded in ways that produce no number: longer check-in, less explanation, surprise balances. Chapter 32 §32.6's argument about statements is downstream of this.

The saving was measured. The cost was distributed across three departments, two budgets, and a category — lost revenue — that appears on no staffing report at all.

How it surfaced

(Constructed.) Not through analysis. Through a coincidence of timing.

The organization began a payer contract negotiation and needed its denial data cleaned up. Someone classified a year of denials by root cause — Chapter 29 §29.4's discipline, undertaken for an unrelated reason.

The front-end categories had roughly doubled, and the increase started in a specific month.

Somebody remembered what had happened that month.

What it shows

First, this is the only failure in this book that was a deliberate decision, correctly reasoned. Every other case study involves a configuration nobody chose, an omission, or a rule nobody read. This administrator made a decision, on the evidence available, and the evidence was incomplete in a way she had no means to detect.

Second, an unmeasured function is indefensible. Not "hard to defend" — indefensible, in the literal sense that there is no defense available. The front end could not produce a single number showing what it prevented, and a function that cannot show what it prevents will be cut by any competent administrator eventually.

Third, the cost moved and the saving stayed. The saving appeared in one department's budget, where it was measured. The cost appeared as denial volume in a second department, overtime in a third, and lost revenue in a category that appears nowhere. Chapter 23's Case Study 2 said the mistake is treating one number as a report card; this is the same failure applied to a staffing decision.

Fourth, the corrective response reinforced the error. Adding a business office position solved the visible problem and confirmed the diagnosis — the queue came down, the report improved, and the organization learned that back-end staffing fixes denial volume. Which is true, and expensive, and not the cheapest available answer.

And fifth, the discovery was luck. A contract negotiation prompted a denial classification that nobody had run for its own sake. This is the eighth finding in this book that came from a person or a coincidence rather than a control — and by now the count is itself the argument.

The lesson

A function that cannot demonstrate what it prevents will eventually be cut, and the people who cut it will be right on the evidence they have.

Four carry-forwards:

Measure the front end before you have to defend it. Chapter 24 §24.10's five measures, plus the sixth. None of them is expensive and all of them are impossible to reconstruct retroactively.

Classify denials by root cause, always. Chapter 29 §29.4. Without it, a front-end failure and a coding failure are the same row on a report, and no staffing decision can be made intelligently.

Report front-end denials to the front end, weekly, with accounts attached. §24.10's argument. It is feedback, not discipline, and it is the only mechanism by which the people causing the errors ever learn they are causing them.

And when a saving is proposed, ask where the cost goes. Not whether there is one — where. A saving that moves a cost into a different budget is not a saving, and the only way to see it is to ask before the decision rather than after.

Discussion questions

1. The administrator made a defensible decision on incomplete evidence. What should she have asked for before deciding, and would the organization have been able to produce it?

2. Adding a business office position solved the visible problem and confirmed a wrong diagnosis. How would you have known? What would have had to be measured?

3. "An unmeasured function is indefensible." Is that fair to the front end, or is it a demand that low-paid staff justify their existence in a way other functions are not required to?

4. The discovery came from a contract negotiation. Design the report that would have found it on purpose. What does it need, and who owns it?

5. This is the eighth finding in this book that came from a person or a coincidence rather than a control. At what point does that stop being a series of anecdotes and become a claim about how revenue cycles actually work? State the claim, and say whether you believe it.