Guide · Multi-site decisions

Which of Your Clinics Is Actually Worth Your Time?

How to decide which site to keep, fix, reduce, renegotiate, or leave, based on records instead of feelings.

You work in three places. The hospital pays the least, but it pays on time, every month. On paper, the private clinic pays about 50 percent more per hour. In reality, two or three patients cancel late or fail to show up each week, and those slots go unpaid. Billing is disorganized, and you end up fixing it yourself. Payment for May arrives in July. The third site sits somewhere in between, and you have never actually calculated what it earns you.

For the past year, you have told yourself you should drop one of them. You have not, because every time you try, you run into the same problem: you cannot truly compare them.

Here is why the comparison fails, in numbers. Suppose the private clinic pays 150 dollars per hour and the hospital pays 100. A private clinic afternoon includes four scheduled hours. One patient does not show up, so that hour goes unpaid, leaving 450 dollars. Then you spend an additional hour at home fixing billing issues. That is 450 dollars for five hours of work, or 90 dollars per hour. The better paid clinic ends up paying less than the hospital.

No payslip shows this calculation. Each site gives you a rate, but none accounts for the surrounding time. This guide shows how to build that missing number, with just five minutes of notes per week.

Why you cannot compare your clinics from memory

This is not just a personal blind spot. It is a documented cognitive pattern. In one study, researchers followed 7,370 emergency physicians across 416,720 visits for shortness of breath. On a typical day, these physicians ordered pulmonary embolism testing in about 9 percent of cases.

However, in the ten days after diagnosing a pulmonary embolism, a vivid and memorable case, the same physicians increased their testing rate by 1.4 percentage points, roughly a 15 percent rise, even though prevalence in population remains the same. Over time, the effect faded, and testing rates returned to baseline.

The rate on your contract is not the cost of the clinic

The feeling misleads in one direction; the headline rate misleads in the other. When researchers shadowed 57 physicians through 430 hours of ambulatory practice, the doctors spent 27% of the office day face to face with patients and 49% on the EHR and desk work: nearly two hours of paperwork for every hour of medicine, plus another one to two hours at home each night. Your contract prices the hour with the patient. It says nothing about the other two, and those are precisely the hours that differ most from site to site.

The hidden hours have company. In the AMA's 2024 survey, physicians completed an average of 39 prior authorizations per week, consuming 13 hours of physician and staff time, and 89% said the burden feeds burnout. A patient who simply does not show up costs roughly $200 in lost revenue; one large study measured $196 per missed visit. At any site that does not pay you for empty slots, that loss is yours. Two clinics offering the same rate can be two entirely different jobs once you count what surrounds the hour.

So both instruments you have been using are broken: the feeling measures the wrong week, and the rate measures the wrong number. What remains is the one thing that measures both correctly: a small written record, kept per site.

Score each clinic on six dimensions

Read each site on six lines: what you truly earn per clinical hour, whether the money arrives in full and on time, how much administrative friction surrounds the work, how many unpaid no-shows you absorb, how long you need to recover after a session, and whether there is room to grow. Score each line from 1 to 5 and the comparison stops being a mood. The figures below are an illustration, not data:

DimensionClinic A (main)Clinic B (second)Clinic C (locum)
Realized income per hour4 (steady)2 (lower, unpaid no-shows)5 (highest, short days)
Payment reliability5 (on time)2 (frequent delays)4 (occasional lag)
Workload friction / admin2 (light)4 (high prior auth, messy billing)3 (moderate)
No-shows / cancellations2 (rare)4 (frequent, unpaid)3 (mixed)
Recovery cost2 (recovered next day)4 (wiped out 48h later)3 (tired but manageable)
Growth potential4 (room to expand)2 (limited, unstable)3 (unclear)

Notice what the table does to Clinic B. Its rate looked acceptable; that is why you took it. Yet it sits low on realized pay and reliability while sitting high on friction, unpaid no-shows, and recovery. Seen on one line, that clinic was having a hard month. Seen on six, it is an arrangement working against you, and the longer it runs the more it quietly costs.

Five moves, one per clinic

A scored table gives you a direction, not yet a verdict. The verdict comes from naming, for each site, one of five moves:

  • Continue: sustainable growth or underdeveloped potential; keep or gently expand sessions.
  • Fix: capacity bottleneck; address workflow, scheduling, or documentation first.
  • Reduce: volume trap with resistant terms; cut hours, reallocate to higher-value work.
  • Renegotiate: reliability risk; use your record of delayed or partial payments to renegotiate timing and process.
  • Remove: operational incompatibility; when deliberate fixes do not change workload or pay over months, plan a staged exit.

Most clinics are not disasters; they are one of these five, waiting to be named. When two moves seem to fit at once, take the more severe reading: the gentler one is usually the bias arguing for the clinic you already hoped to keep.

What to write down: five minutes a week

This costs about five minutes a week. For each clinic, note one workload score from 1 (stable) to 5 (burnout), the single friction that kept recurring, and any change you tried and whether it held. Then, once a month, one sitting: pull the numbers each site already keeps (patients, no-shows, sessions, what was actually paid) and mark each payment clean, late, or partial. You are not building a new system; you are copying totals that already exist.

One rule protects the whole exercise: if you skip a week, leave it blank. A week filled in from memory is a week edited by the same bias this record exists to bypass, and it will quietly flatter your favorite site.

Three months to suspect, six months to decide

By month three a pattern starts to surface; resist acting on it. Three months is long enough to suspect a clinic and too short to be fair to it. Six months gives you three full cycles of workload and pay, plus room to try one honest correction and watch whether it holds. That is the difference between dropping a clinic and ruling it out.

Set the decision rule before you see the data

The last move borrows a trick from research design: decide the threshold before you see the data. Write the rule down now, while no clinic has recently ruined your evening, so the six-month review is a reading and not an argument:

Decision rule. At six months, if a clinic has average workload and recovery scores of 4 or higher for at least three of the months, AND its realized pay per hour sits in the lowest third of your sites OR its payments are recurrently delayed or partial, treat it as a Reduce or Remove candidate and plan a staged reduction over 60–90 days, mindful of contracts. If a clinic shows stable workload (scores of 2 or lower), reliable payments, and usable growth potential, classify it as Continue or Expand.

And that dissolves the wall from the beginning. You could not compare your three clinics because you were comparing three feelings; six months from now you will be comparing three columns of numbers against a rule you wrote while calm. The physicians in the PE study could not stop a vivid case from bending their judgement. Nobody can. But with the record and the rule in place, the bending no longer matters. The bad week still happens; it just no longer gets a vote.

References

  1. Sinsky C, Colligan L, Li L, et al. Allocation of Physician Time in Ambulatory Practice. Annals of Internal Medicine. 2016;165(11):753–760. acpjournals.org
  2. Ly DP. The Influence of the Availability Heuristic on Physicians in the Emergency Department. Annals of Emergency Medicine. 2021;78(5):650–657. pubmed.ncbi.nlm.nih.gov
  3. Whelehan DF, Conlon KC, Ridgway PF. Medicine and heuristics: cognitive biases and medical decision-making. Irish Journal of Medical Science. 2020. springer.com
  4. American Medical Association. 2024 Prior Authorization Physician Survey. ama-assn.org
  5. Kheirkhah P, Feng Q, Travis LM, Tavakoli-Tabasi S, Sharafkhaneh A. Prevalence, predictors and economic consequences of no-shows. BMC Health Services Research. 2016;16:13. bmchealthservres.biomedcentral.com

Frequently asked questions

Which clinic should I drop if my income is similar across them?
If income per hour is similar, look at workload and recovery cost: reduce or drop the clinic with recurrent high workload scores, frequent unpaid no-shows, and heavier recovery, especially if honest workflow fixes have not changed it over several months.
Is my second clinic worth it if it pays well but exhausts me?
A clinic with good headline pay but consistently high workload and recovery scores is a capacity bottleneck or operational incompatibility. If targeted changes do not lower friction over several months, its effective value is lower than it looks, and reducing or leaving becomes reasonable.
How do I evaluate multiple practice locations without adding more admin?
Use a light path: one weekly workload note per clinic and a single monthly sitting where you pull activity and payment data from each site's existing systems. This keeps the record small while revealing which location quietly generates the most friction or unreliable pay.
Should I leave one of my clinics if pay is late but the work is rewarding?
Late or partial pay with good clinical work is a reliability risk. Use your record of delays and shortfalls to renegotiate payment terms first, and only consider exit if payment stays unstable after a fair attempt to improve it.
How do I know if a heavy month is a bad stretch or a structural signal?
Ask what a colleague would need to be convinced. One month convinces nobody; the same friction named in your own notes, month after month, in your own handwriting, is the kind of evidence that survives even your best excuses for the clinic.

Loguaron is the paper system built to hold exactly this record across sites, without screen time. The Loguaron workbook turns this analysis into six decision patterns, read from your own record. Run one week free → · See the workbook →

Related evidence: Observe the System → · Log Reality →

Last reviewed: July 2026.