No-shows are the smaller problem. Cancellations are the big one.

Every practice worries about the patient who simply does not turn up. When we measured a real UK practice, no-shows were 1% of finished appointments and cancellations were nearly a quarter. The money is not in predicting the rare thing; it is in refilling the common one.

What we measured

Across 4,454 finished appointments in one practice, over roughly six months:

What happened	Share	What it means
Did not attend	1.0%	Rare, and impossible to model from so few cases
Cancelled	24.5%	The real leak
Cancelled inside 48 hours	17.8% of cancellations	Hard to refill by hand
Typical notice given	11.7 days	Most people do warn you

The practice's reception team already refilled 70% of freed slots. Even so, 208 hours of chair time went unused, concentrated in two places: the cancellations that arrive with under two hours' notice, which were refilled only a third of the time, and the slow tail of gaps weeks away that nobody has time to chase.

How Lynqpod fills a gap

The cancellation is noticed in about a second, through a webhook from the practice management system.
The people who fit are worked out. A waiting list holds who would come sooner, which clinician they want, which days and times suit them, and whether they are in pain.
They are asked on WhatsApp, up to a handful at once, with the time, the clinician and two buttons.
The first to say yes takes it. Everyone else is told it has gone and stays on the list.
Reception confirms. The booking arrives as a request, the same one they already work through, with a note saying who took it.

Spotting the ones likely to fall over

Risk flags only earn their place if they can be explained to the person picking up the phone. Two signals held up when tested against that practice's own history:

How far ahead it was booked. Appointments made more than three months in advance fell through 58% of the time. Made within a week, 12%.
What that patient has done before. Previous no-shows count for more than previous cancellations.

Tested backwards, the appointments flagged high fell through 76% of the time against a 31% average. Every flag carries its reason in words, such as "booked five months ahead, did not attend once before".

What we left out, and why. Weather is popular in this market, and we could not find it in the data: rain showed nothing, and the temperature effect that looked convincing disappeared once the season was held still. We record it daily so the question can be asked again with a winter's data, but it scores nothing today. A signal nobody can check is not a signal.

What this does not do

It does not charge deposits, though the booking pages can.
It does not write into the diary by itself unless straight-through booking is on.
It does not message anybody until the practice switches it on, and the wording has to be approved by WhatsApp first.

Common questions

Is this just another reminder app?

Reminders are part of it, but a reminder cannot fill a chair. The difference is the waiting list: when a slot frees, real patients are asked and one of them books it.

How fast does a slot actually fill?

That depends on how many patients on the list fit the gap. What the software controls is how fast they are asked, which is within about a minute of the cancellation.

Do patients find being asked annoying?

They asked to be told. The list also limits how often the same person is asked, keeps quiet hours, and stops asking someone who never replies.

What if two patients say yes at once?

Only one can win. The slot is claimed by a single write, and the second person is told it has gone rather than double booked.

See it on your own numbers

The quickest way to judge Lynqpod is to point it at a month you already know. Read-only to start: nothing is written back to your practice management system until you ask for it.

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