The audit

Find out what happens to your patients after they walk through the door.

One export from your booking system, about a week of my time, and a conversation at each end. What comes back is an economic model of your clinic and a short list of what is actually limiting revenue.

01

Discovery call

Thirty minutes on your clinic and what you are trying to decide. Whether the audit is right for you gets answered here, before any data changes hands.

02

One export

Appointment history out of Jane, Mindbody, or whatever you run on. You pull it yourself. I will show you exactly which report and which settings. Nothing identifying leaves your system.

03

The model gets built

Roughly a week. Patient journeys, retention, service economics, and capacity, reconstructed from your own history, with a short check-in once I have seen your data so the model reflects your clinic, not just your export.

04

Executive debrief

An hour together on what the model found, what it is worth in dollars, and which two or three things deserve your attention first.

What the audit looks at

01

Patient profiles, and who your biggest spenders actually are

02

Which services carry the clinic, and which just fill the schedule

03

Where patients typically drop off, and how early it happens

04

Which patients quietly stopped coming, and which are worth reaching out to

05

How your providers compare on keeping patients, not just seeing them

06

Where your pricing has drifted behind what the work is worth

What findings look like

Three examples of what an audit surfaces.

Scenario A

A 6-point retention lift adds $42K in annual revenue, with no new patients.

This clinic sees 700 new patients a year and 62% return after their first visit. Moving that rate to 68% retains 42 additional patients. Retained patients generate $1,150 in average annual revenue versus $150 for patients who stop after one visit.

Before first-visit return rate
62%
$150 avg
After first-visit return rate
68%
$1,150 avg
Incremental annual revenue
+$42,000
42 additional patients retained at $1,000 more annual value per patient.
Scenario B

A 10% price increase on your flagship service adds $28K with zero change in volume.

A price increase may not cost you patients. The model shows the real tradeoff before you commit to it. Applied to this clinic's highest-volume service, a 10% increase adds $28,000 annually at current volume. The useful question isn't whether anyone leaves, it's how many you could afford to lose.

$280K
Annual revenue from flagship service before
$308K
Annual revenue after 10% increase
Incremental annual revenue
+$28,000
The clinic could lose roughly 9% of service volume before giving back the gain from the price increase.
Scenario C

The retention gap between team members is worth $47K a year.

Provider A retains 58% of patients at 12 months. Provider B retains 27%. That 58% is a repeatable set of behaviours, not luck. At current patient volume, bringing the team to Provider A's number is worth $47,000 a year, and it requires no new patients.

12-month patient retention by provider
Provider A
58%
Provider B
27%
Recoverable annual revenue
+$47,000
Provider-level retention doesn't show up in standard EHR reporting. The gap is only visible once retention is split by provider.

Figures are representative of clinic economics at this scale. Your model reflects your own patients, service mix, and pricing.

Common questions

The things founders ask before the first call.

What happens to my patient data?

Nothing identifying leaves your system. Before the export reaches me, dates are stripped and patient IDs are regenerated, so the analysis runs on behavior rather than people. I never see a name, and I do not need one to find the pattern. You pull the export yourself, so nothing touches your booking system but you.

Is this HIPAA compliant?

The audit is designed so the question barely comes up: the data I receive is de-identified before it leaves your building, so no protected health information reaches me. Deeper engagements that call for richer data are formalized properly, with a business associate agreement, when the scope justifies it. Happy to walk through the specifics on the call.

Is this just AI doing the analysis?

LUFT delivers everything AI does not supply i.e. knowing which questions to ask, pattern recognition across clinics, knowing whether a finding is real or hallucination due to structural bias, having a human that can call you out on the actual issues.

Am I big enough for this?

The bar is not a revenue number. It is enough visit history to model, usually three or more years, and enough complexity for the answers to matter: multiple providers, services, or revenue streams. Put differently, if you are big enough to be making hiring, pricing, or capacity decisions, you are big enough for those decisions to have numbers behind them.

How much of my time does this take?

Two conversations and one export. Thirty minutes for the discovery call, a few minutes to pull the report from your booking system with my instructions, and an hour for the executive debrief. The week of modeling in between is my time, not yours.

I'm not a data person. Will I understand what I get?

The debrief is a conversation, not a dashboard. You leave with two or three findings in plain language, each with a dollar figure attached and a clear sense of what acting on it looks like. If anything in the walkthrough needs a statistics degree to follow, I have done my job badly.

Will this feel like an audit of my staff?

No. The model measures process, not people. When a provider-level pattern shows up, it is almost always an operational finding, a rebooking habit, a scheduling difference, not a performance verdict. What gets shared with your team, and how, is entirely your call. Most founders end up using the findings to give their staff clearer systems, not harder conversations.

Is this going to turn into a pitch for more work?

The audit is useful on its own or it is not worth doing. Some of what it finds you will fix yourself in a week. Some findings need a tool your front desk can work from, and some open bigger questions, like whether a second location pencils. You will know which is which by the end of the debrief, and none of it obligates you to do anything further with me. One-and-done is a perfectly good outcome.

Luke Bujarski, founder of LUFT

Start with the discovery call.

Thirty minutes with Luke. No pitch, no data required. Pick a time below and you're booked.

Prefer email? lb@luft.net