Local AI for reviewing clinic administrative questions

One booking topic, two different questions

An invented data set contains the messages: „Once I have sent the form, is my appointment already booked?” and „Where can I find the booking confirmation?”. The model proposes a shared confirmation category, but the manager separates their meaning: the first is about when a booking becomes binding, the second about where the patient looks for the confirmation.

This distinction shows what to look at in current communication: the text shown after the form is sent and the message the clinic sends. The summary does not prove that these messages cause the questions, but it gives a concrete topic to discuss with reception. The report describes the chosen data set and period, and the number of messages is not the number of people.

What it costs and when it pays back

The count covers the time spent searching, reading and compiling material. What remains is the time to check the result against the source, 25% of today's work in the scenario. We measure both times in a trial on 20 to 100 cases the team has already handled.

Preparing the data and processing locally

The European Commission explains that data which allow a person to be identified again remain personal data, and that anonymisation must be irreversible. If the clinic chooses processing on its own computer or server, the model can run there. Ollama describes local and cloud models and how to switch off cloud features. Where the model runs does not confirm anonymisation, and in this use we do not link the correspondence to a specific patient's history.

Is the current report enough

If the form or the service system already records sensible categories, start with its report. With a small number of messages, tagging topics by hand is often simpler than an app. A model is worth comparing when the content varies and a general topic in the system hides different cases. On the same material, the manager looks at the current tool's report and the proposed grouping and counts the corrections. Handling a single case is covered in the article on an agent for clinic administration.

Where to start

The first stage covers one question about administrative communication and an invented sample on which we discuss the summary. For the call, a description of a question that keeps coming back to reception is enough, with no patient messages. We deploy local models as part of private LLMs, and we build the view for working with sources as an AI app. For the free analysis, a description of one case and of where the materials sit is enough. Confidential files stay in the company, and you get a written plan within 2 working days.