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Solution · Sales & marketingA 2 p.m. cancellation finds a taker from the waiting list before reception finishes its coffee
Appointments confirmed, empty slots refilled
A robot confirms appointments and reminds about them on a rhythm you set, and turns every cancellation into an instant waiting-list offer. Reception stops phoning people; it starts receiving confirmations.
Executive summary
No-shows and late cancellations eat treatment hours, and reception has no time for reminder calls because it is busy serving those who did come.
Confirmations and reminders go out by themselves, on an agreed rhythm. A cancellation triggers the waiting list: an offer reaches the first matching people, and the slot goes to whoever confirms first.
Empty slots refill within hours instead of expiring, and the owner finally sees the numbers: how many visits are lost, at which times, from which booking channel.
the appointment calendar (Bookings or your clinic system); SMS and email to patients; the waiting list; summaries in Microsoft Teams
Business problem
An hour nobody can sell again
In an appointment business the merchandise is time: a doctor’s or therapist’s hour exists exactly once. A visit nobody attended is not postponed revenue but cancelled revenue, while the hour’s costs, people, premises, equipment, were incurred to the last cent.
Reception knows the remedy: confirm, remind, keep a waiting list and phone around when something frees up. It knows it and has no time for it, because during opening hours it serves patients at the desk and a ringing phone. Reminders go out “when it is quieter”, that is, irregularly; the waiting list lives in a notebook; and an 11:40 cancellation of a 2 p.m. visit is simply a loss, because two hours is not enough for a phone round.
Then there is the arithmetic of cancellations: some patients cancel by Instagram message, some by email, some not at all. The calendar looks full to the end, so nobody even sees that the room will stand idle at 2 p.m. Nobody measures the phenomenon either: how much is lost, on which days, with which specialists, from which booking channel the least reliable bookings come.
The result: the clinic buys advertising to win new patients for slots that are lost for want of two text messages. It is the most expensive way of filling a calendar there is.
How it works today
Below is what the work looks like before anything is automated.
- PersonReception calls with reminders when there is a moment, meaning irregularly and not everyone
- Risk of errorCancellations arrive through four channels; some never reach the calendar in time
- WaitingA slot freed by a cancellation stays empty, because a phone round takes an hour nobody has
- PersonThe waiting list lives in a notebook at the desk, in order of writing, without time preferences
- Risk of errorA no-show patient bears no consequence and is back in the calendar a month later
- Risk of errorNobody counts the phenomenon, so the no-show conversation ends at “somehow more often lately”
Why the current process costs more than it appears
The bill that never shows up in a budget.
- Every lost treatment hour is full cost with no revenue; over a month it usually exceeds the salary of the receptionist who was supposed to prevent it.
- Advertising wins new patients for slots lost logistically: you pay twice for the same hour.
- A waiting list without service is an unbacked promise: people who wanted to come sooner hear about a free slot after the fact, or never.
- Missing numbers hide patterns: a specialist with 15% no-shows looks in the diary exactly like one with 3%.
Cost of inaction
The first row is arithmetic any clinic can do on its own numbers in five minutes: the share of lost visits times their value. It usually yields an amount nobody knew about, because it leaks one hour a day rather than in one transfer.
The model assumes the automation will not abolish the phenomenon, only cut it: some absences will remain, because life. But the gap between 9% without a system and 3-4% with confirmations plus a working waiting list is, in this scenario, tens of thousands of euros a year from logistics alone.
A model organisation with realistic proportions – the numbers exist so you can run the same maths on your own data; they are not a client result.
An aesthetic medicine clinic in a regional capital: three rooms, two doctors and three cosmetologists, reception at one and a half posts, bookings by phone, Instagram and a booking portal, the calendar in a clinic system, Microsoft 365.
620 visits a month, an average visit value of €95, 9% of visits lost to no-shows or cancellations too late to react.
Phone reminders “when there is a moment”, a notebook waiting list, cancellations from four channels entered into the calendar with delay.
Reception cannot confirm systematically or phone the list; a slot freed after noon practically always expires.
The robot sends a confirmation on booking, reminders 48 h and 4 h before the visit with one-click confirmation; a missing confirmation and every cancellation trigger waiting-list offers by time preference; reception sees only the human-needed cases in Teams.
In the modelled case no-shows fall to around 3-4%, and most freed slots refill the same day. Model numbers, not the clinic’s records.
Proposed solution
We start with rules that are yours, not ours: when reminders go out, what counts as a confirmation, after how much silence reception’s phone call kicks in, who is offered freed slots and in what order, how patients with a no-show history are treated. It is a one-page document we write together, changeable at any time.
The robot works on your calendar, not beside it: it reads bookings from the clinic system or Microsoft Bookings, sends confirmations and reminders by SMS and email, and records the replies. A cancellation, from whichever channel reaches the calendar, immediately triggers the waiting list: an offer goes to the first people whose preferences match, and the slot goes to whoever confirms first. Nobody is booked without their consent.
Reception gets a short list of cases in Microsoft Teams where a human is needed: a patient did not confirm despite two reminders, someone replied with a question, tomorrow still has an unfilled slot. Once a week the owner receives the numbers: no-shows per specialist, time of day and booking channel, and the waiting list’s hit rate. For the first time you can see where the calendar actually leaks.
UiPath Orchestrator: reminder schedules, a visit queue, retries and an audit trail; UiPath Integration Service connectors for Microsoft Teams and Outlook 365; the SMS gateway you already use, or one we help you choose
Versioned confirmation and waiting-list rules, patient reply handling, slot offer logic, reception cases in Teams and weekly owner numbers
The appointment calendar: Microsoft Bookings natively, or a clinic system (with export or API) via its documented interface; the SMS gateway via API
How the automated process works
- SystemA new booking in the calendar triggers a confirmation with a one-click reply
- AutomationReminders go out 48 h and 4 h before the visit; replies return to the calendar
- AutomationA cancellation from any channel immediately triggers waiting-list offers by preference
- SystemThe slot goes to the first person to confirm; the rest get a polite no and stay on the list
- PersonReception sees only exceptions in Teams: no confirmation, a patient question, tomorrow’s slot without takers
- PersonThe owner gets weekly numbers: no-shows, recovered slots, patterns per specialist and channel
Human-in-the-loop model
Automation handles
- Confirmations, reminders and reply handling, on the agreed rhythm, without exceptions or holidays
- Instant offers of freed slots to the waiting list and assignment to the first confirmer
- Weekly numbers: no-shows, recoveries, patterns per specialist, time and booking channel
People decide
- The rules: reminder rhythm, the definition of a confirmation, waiting-list order, the policy towards repeat no-shows
- Conversations with patients in all atypical and sensitive matters
- Commercial decisions: prepayments, deposits, cancellation policy and its wording
Before and after
Systems and integrations
The stack is short on purpose: one engine, one execution layer, one place where a person decides.
Inputs
- the appointment calendar (Bookings or clinic system)
- the waiting list with preferences
- confirmation and offer rules
- patient replies from SMS and email
Automation layer
- UiPath Orchestrator
- UiPath Robots
- UiPath Integration Service
- UiPath Action Center
Target systems
- confirmed and reminded visits in the calendar
- slots refilled after cancellations
- reception cases and weekly numbers in Microsoft Teams
Human touchpoints: reception cases in Microsoft Teams; a weekly owner summary; a quarterly rules review
Technologies used
reminder schedules, a visit queue, retries, a full record of every message
Areception cases, owner summaries, email where SMS is not enough
Aa booking calendar with a native API inside Microsoft 365, if you use it or want to
Asending and receiving replies; we work with your current gateway or help you choose one
Bthe calendar source where bookings live in an industry system; integration scope depends on its interface
BIllustrative economic model
Numbers you can check against your own data.
The model does not promise zero absences, because zero does not exist: it assumes a drop from 9% to 3.5%, which is what systematic confirmations plus a working waiting list deliver. Visit values and volume belong to the scenario; your own numbers go into the calculator alongside in a minute.
Run the maths on your data
An illustrative estimate based on your inputs. It models freed capacity, not promised savings.
Business benefits
- Treatment hours stop expiring for logistical reasons, and the calendar works closer to full
- Reception stops being a reminder call centre and returns to the patients at the desk
- The waiting list starts working in minutes, so “we’ll let you know if something frees up” becomes true
- The owner sees numbers and patterns, so deposit or cancellation policy decisions rest on data
- Patients get civilised communication: a confirmation, a reminder, an easy way to cancel
The management view
- The firm’s most expensive resource, a specialist’s hour, stops leaking without a trace in any report
- The no-show phenomenon has numbers, a trend and patterns instead of anecdotes
- Scaling bookings (new channels, new specialists) does not require scaling reception
Board-level KPIs
share of visits lost · slots recovered from the waiting list · time from cancellation to refill · confirmations before the visit · no-shows per specialist and booking channel
Security and governance
The automation has exactly the permissions it needs. Not one more.
- The robot works on a minimal data scope: name, contact, slot and visit status; no medical data or treatment descriptions in messages
- Every message sent and every reply has a record: what, when, to whom, from which rule
- Communication rules are versioned and changed only by an authorised person
- Patients’ communication consents are respected: whoever declines SMS gets email, or reception
- Data stays in your Microsoft 365 tenant and your SMS gateway; the robots run in the EU region of UiPath Automation Cloud
Why now
The cost of a treatment room hour has risen faster than treatment prices: an empty hour hurts more than ever.
Patients are used to one-click confirmations at the hairdresser and the dentist; the absence of such communication now reads as neglect.
Booking channels multiply (phone, Instagram, portals), and with them cancellations that never reach the calendar; manual control will not catch up.
Relevant executive roles
The calendar works closer to full, and the no-show conversation rests on numbers rather than reception’s impressions
The waiting list and reminders happen by themselves; the team deals with patients, not the phone
Instead of a hundred routine calls, a short list of cases that genuinely need a human
Common questions and objections
Some certainly do, and nothing breaks for them: silence after two texts ends in a reception phone call, as today, only with a list of the people who genuinely need calling. Clinic practice is stubborn though: most people confirm with one click within a minute, because it is more convenient for them too.
A reminder is one third of the process. The other two are the reaction to a cancellation, a waiting list working in minutes, and the owner’s numbers. The automation ties the channels (portal, phone, Instagram) into one process around your calendar, instead of leaving each channel in its own silo.
Which is why it writes only logistical messages from templates you approved: slot, confirmation, offer. Anything beyond logistics, a question, a doubt, an emotion, lands as a case with reception, full context attached.
When this is not the right solution
- A few dozen visits a month with one practitioner: discipline and good habits suffice, the automation will not pay back
- A calendar kept solely in a paper notebook: first any electronic calendar, then automation
- The expectation of dunning patients for absences: that is a pricing policy decision, not a technical process; the automation can at most communicate it
A question for the next management meeting
How many treatment hours did we lose last month, and what share of those losses would two text messages and a working waiting list have prevented?
Implementation approach
Scope without ambiguity, before anything is signed.
We deliver
- Written confirmation, reminder and waiting-list rules, versioned
- Automated visit communication on your calendar and your SMS gateway
- A working waiting list with offers minutes after a cancellation
- Reception cases in Microsoft Teams and weekly owner numbers
- Two weeks of parallel running with current practice, and care after go-live
We need from you
- Access to the calendar (Bookings or a clinic system with export/API) and the SMS gateway
- Approved message templates and rules, written together in one meeting
- Three months of visit history to compute the starting point
Stages
Discovery
Three months of history: how much is lost, when, with whom and from which booking channel
Rules
Reminder rhythm, the definition of a confirmation, waiting-list order, message templates
Build
Calendar and SMS integration, offer logic, Teams cases and weekly numbers
Parallel run
Two weeks: the automation works, reception observes and polishes the templates
Go-live
Full traffic with a numbers review after the first month
A quick win. Effort depends on what runs your calendar: Bookings is the shortest path, clinic systems depend on their interfaces.
Tuesday, 2 p.m., room two: the doctor is in, the lamp is warm, the patient is not there. Three people on the list would have taken that slot at once.
Send us a visit export from the last three months. We return the arithmetic: how many hours were lost, what they were worth, and what share had a real chance of refilling from the waiting list, had anyone had time to work it.
Count last month’s empty slotsThe neighbouring process usually has the same problem
The patient is in the chair, and one signed page is missing from the file. Again.
See the solution Finance & accountingTreatment packages settled to the endA sold package is a promise, not revenue. Who tracks how much of it remains?
See the solution Customer serviceGoogle reviews collected after every visitThe happy leave in silence. The unhappy one writes on Sunday at 11:40 p.m.
See the solutionIndustries where we deploy this most oftenAesthetic medicineSmall business & services