AI saves time on clinical documentation by moving the work from writing the note to approving a draft. The AI listens along during the conversation and produces a structured note. The clinician corrects and approves. It goes faster, because correcting a text takes less time than composing it. The consultation itself takes just as long.
The entire gain sits in the follow-up work. It grows with the amount of free text in the note and is multiplied by the day's consultations. Reading through and correcting the draft also costs time. That time has to be subtracted before the number holds.
Where does the time saving come from?
The time saving comes from the documentation after the consultation, not from the consultation itself. The patient still has to be examined, heard and advised as before. It is the note that changes. The clinician does not start on a blank page, but on a draft produced from the conversation.
The draft arrives structured. The AI distributes the content across the fields that are already filled in - history, objective findings, assessment and plan in a SOAP note, or the relevant fields in an annual check-up. Instead of composing each section, the clinician reads the draft, moves a sentence, deletes the superfluous and adds what the AI could not know. The work shifts from writing to editing. And editing is faster.
The effect follows the amount of free text in the note. The more there is to compose, the more the draft saves. A long, composite consultation with several issues, a social history and a multi-step plan gives the biggest gain. A short, standardised note, where there was not much to write in the first place, gives a small one. It is in the long notes of everyday practice that the minutes sit.
How much time can AI save per consultation?
It depends on the clinic, but the calculation is the same everywhere. It builds on three figures: the time saved on composing per consultation, the time spent reading through and correcting the draft, and the number of consultations per day. The net saving per consultation is the first figure minus the second. It is multiplied by the day's consultations and grows over a week and a month.
An example: 15 consultations a day, where a note used to take 5 minutes to write and now takes 2 minutes to review and correct. That is 3 minutes saved per consultation - 45 minutes a day, close to 4 hours a week and around 15 hours a month.
The number depends on your clinic: consultation type, how thoroughly documentation is done today, and how much needs correcting in the draft. A clinic with many short contacts saves less per note than one where every patient fills half a page of free text. The most honest way to find your own number is to measure the follow-up work before and after across a series of consultations over a couple of days. People's Clinic has a 30-day trial period - you sign up with a card, but can cancel before payment is taken, so you can measure on your own everyday practice without paying. See the current price under pricing.
Is the time saving realistic - or too good to be true?
A worked example shows the potential, not a guarantee. Three caveats pull the other way, and they belong here if the number is to hold: reading through costs time, the responsibility cannot be delegated, and the saving depends on the integration.
Reading through and correcting costs time. A draft has to be read critically, not skimmed. AI can phrase something imprecisely, omit a finding or include a remark that does not belong in the note. The note is a legal document and the basis for further treatment. Errors have to be caught before it is saved. That time has to be subtracted from the saving, not added to it. The gain is real, but smaller than a draft seen in isolation suggests.
The responsibility still rests with the authorised clinician. The duty to keep records cannot be delegated to a tool. The AI makes a draft. The clinician reads it through, corrects, approves and bears the responsibility for the finished note in the same way as for a handwritten one. The approval is not an extra click. It is the professional control that turns the note into a record. That time is part of the work and part of the time accounting. Read more about the framework in the guide Is AI clinical documentation legal in Denmark?
The saving also depends on how well the tool fits into the workflow. Switching between windows, copy-paste and double entry quickly eats minutes. For XMO, People's sits inside the system, so you work in one window and approve the note where you already keep records. People's does not pull data from the record system itself. See integrations for how it fits with your record system.
This guide describes where the time saving comes from, and which caveats apply - not a promised result for your clinic. The actual number depends on your everyday practice and should be measured concretely. The responsibility for the finished note always rests with the authorised clinician. Questions about setup can be put to support.