Training course – Google Gemini – Healthcare

Google Gemini for Healthcare Professionals

Make productive use of Google Gemini and Gemini in Workspace: Docs, Sheets, Gmail, Meet, custom Gems and NotebookLM for your sources.

Duration
6 hours, one session
Format
Online or on-site
Language
German or English
Participants
open dates or exclusive for your team
Certificate
Certificate of attendance

Overview

This course connects Google Gemini with the everyday processes of Healthcare. Participants work on realistic scenarios and leave with prompts, workflows and checklists they can use straight away.

For organisations running on Google Workspace, Gemini is the natural AI assistant: it is available as a standalone app and is also built directly into Gmail, Docs, Sheets, Slides, Drive and Meet. In this practical day you learn to combine both access points deliberately. You summarise email threads and draft replies, create document drafts based on existing files in Drive, structure and analyse spreadsheets in Sheets and have Meet take meeting notes automatically – always with a focus on your own day-to-day workflows.

You also build your own Gems: specialised assistants with fixed instructions and knowledge files that standardise recurring tasks across the team. With Deep Research you produce well-founded research reports, and you use NotebookLM as a source-grounded workspace that answers only from your own documents and cites the relevant passages. A dedicated module covers data protection and administration in Workspace environments. You leave with tested prompts, a working Gem and a clear picture of which Google tool suits which task.

Hospitals, practices, care homes and health insurers struggle with staff shortages and a heavy documentation burden that takes valuable time away from patients. Generative AI can provide targeted relief: AI assistants help draft discharge letters and reports, summarise guidelines and studies, write patient information in plain language and support quality reports, rosters and administrative tasks. Automation speeds up appointment management, enquiry handling and internal communication. At the same time, the strictest requirements apply: health data is specially protected, medical confidentiality and professional rules must be observed, and software with a medical purpose may qualify as a medical device. AI in healthcare must therefore distinguish clearly between administrative support and clinical decisions, be operated securely and remain under the responsibility of qualified professionals.

The course is delivered live – either online in a virtual classroom or on-site in our training rooms in Munich, Salzburg, Berlin, Augsburg, Hanover, Bremen, Stuttgart and Kaiserslautern. We can also run it exclusively for your team.

Who is this course for?

  • Physicians in hospitals and practices
  • Nurses and nursing managers
  • Hospital and practice managers
  • Clinical coding and medical controlling staff
  • Quality management and administration in healthcare facilities

Typical challenges we address

  • Coping with heavy documentation alongside patient care
  • Keeping up with current guidelines and evidence
  • Informing patients clearly and in several languages
  • Running administrative, quality and billing processes with limited staff

What you will be able to do

  • You use Gemini in Gmail, Docs, Sheets, Slides and Meet for your recurring tasks.
  • You write prompts that bring existing Drive files and emails into the context.
  • You build a custom Gem and share it with your team.
  • You work source-grounded in NotebookLM and obtain referenced answers from your own documents.
  • Use AI to reduce the burden of documentation, patient information and administration.
  • Distinguish confidently between administrative AI applications and regulated medical devices.
  • Protect patient data in line with the GDPR, medical confidentiality and professional rules.

Course outline

Module 1 Gemini fundamentals and effective prompts
  • The Gemini app and Gemini in Workspace: access points and use cases
  • Prompts with task, context, format and references to Drive files
  • Web search, Deep Research and checking sources
  • Limitations, hallucinations and critical evaluation of output
Module 2 Gmail, Docs and Slides
  • Summarising email threads and drafting context-aware replies
  • Drafting, rewriting and tailoring documents in Docs
  • Pulling in and combining content from Drive files
  • Creating presentation content and images in Slides
Module 3 Sheets and Meet
  • Structuring tables, generating formulas and cleaning data
  • Analyses, summaries and charts in Sheets
  • Letting Meet take meeting notes automatically
  • Deriving action items and decisions from meeting notes
Module 4 Gems and NotebookLM
  • Creating custom Gems with instructions and knowledge files
  • Testing, improving and sharing Gems with the team
  • NotebookLM as a source-grounded workspace for your own documents
  • Generating summaries, study aids and audio overviews from sources
Module 5 Data protection, administration and rollout
  • Privacy commitments for Workspace customers versus personal accounts
  • Drive sharing settings and how they affect Gemini results
  • Handling personal and confidential data in line with GDPR
  • Usage policies and quality assurance within the team
Module 6 Practice lab: Healthcare
  • Drafting letters and reports
  • Summarising guidelines and studies
  • Patient information
  • Nursing documentation support
  • Quality and administrative documents
  • Enquiry and appointment management
Module 7 Data protection, quality & transfer to daily work
  • Health data is a special category under Article 9 GDPR and subject to medical confidentiality, in Germany under Section 203 of the Criminal Code; it may only be processed in approved, contractually secured environments. Software with a medical purpose, such as diagnostic or therapy support, can be a medical device under the MDR and is then high-risk AI under the EU AI Act.
  • Ground rules for safe AI use in your team
  • Checking results: facts, sources, tests and the four-eyes principle
  • Personal action plan for the next 30 days
  • Open questions, outlook and resources for further learning

Practical scenarios from your field

Drafting letters and reports

An AI assistant in an approved environment structures findings and progress notes into a draft discharge letter or report, which the responsible physician fully reviews and corrects.

Summarising guidelines and studies

AI summarises guideline recommendations, studies and product information and compares key statements, as a starting point for continuing education and with references to the original sources for verification.

Patient information

Clinical content is turned into clear patient information, plain-language supplements to consent materials and leaflets in several languages, which are medically reviewed and approved.

Nursing documentation support

AI helps turn bullet points into structured nursing reports and handovers, draft care plans and harmonise wording, while the nurse remains responsible.

Quality and administrative documents

Procedures, hygiene plans, quality reports and training materials are created and updated with AI support, without the need for any patient data.

Enquiry and appointment management

Automations sort incoming enquiries from patients and referring physicians, answer standard organisational questions and prepare appointment suggestions, while medical questions go to qualified staff.

Prerequisites

Confident everyday use of Google Workspace (Gmail, Drive, Docs, Sheets); no prior AI knowledge is required. You work in a healthcare organisation, in a clinical, nursing, administrative or management role.

Technical requirements

A laptop with an up-to-date browser and a Google Workspace account with Gemini features enabled; alternatively a Google account for the Gemini app and NotebookLM.

Data protection & compliance

Health data is a special category under Article 9 GDPR and subject to medical confidentiality, in Germany under Section 203 of the Criminal Code; it may only be processed in approved, contractually secured environments. Software with a medical purpose, such as diagnostic or therapy support, can be a medical device under the MDR and is then high-risk AI under the EU AI Act.

Dates & locations

For every location we suggest a date roughly four weeks ahead. Your preferred date is always possible.

  • Munich Thu, 10 December 2026 6 hrs Request
  • Salzburg Wed, 16 December 2026 6 hrs Request
  • Berlin Wed, 16 December 2026 6 hrs Request
  • Augsburg Fri, 11 December 2026 6 hrs Request
  • Hanover Wed, 16 December 2026 6 hrs Request
  • Bremen Thu, 10 December 2026 6 hrs Request
  • Stuttgart Thu, 10 December 2026 6 hrs Request
  • Kaiserslautern Tue, 15 December 2026 6 hrs Request
  • Online Mon, 14 December 2026 6 hrs Request

Frequently asked questions

What is the difference between the Gemini app and Gemini in Workspace?

The Gemini app is a standalone chat assistant for research, writing and analysis. Gemini in Workspace works directly inside Gmail, Docs, Sheets, Slides and Meet and can draw on your emails and Drive files. In practice they complement each other: the app for open questions, the integrated version for work on specific documents.

Why would I use NotebookLM in addition to Gemini?

NotebookLM restricts its answers to the sources you upload – policies, studies or project files, for example – and points to the relevant passages. This reduces hallucinations and works well for getting up to speed on a topic, building internal knowledge collections or preparing training material. Gemini is broader in scope and can also draw on the web.

Is my Workspace data used to train Gemini?

For Google Workspace customers, Google commits that content from Gmail, Drive and other services is not used to train models outside your domain without permission. Different rules apply to personal accounts. Either way, GDPR and your internal policies remain decisive – in the course we review the relevant settings together.

May patient data be processed in AI tools?

Only in environments approved by your organisation, secured under data protection law and compatible with medical confidentiality. Publicly available consumer tools are unsuitable. Many use cases, such as quality documents or patient information, need no patient data at all. We show you how to get started safely.

When does AI software become a medical device?

The intended purpose is decisive: software intended for diagnosis, monitoring or therapy decisions for individual patients can fall under the MDR. General text and administrative support usually does not. In the course you learn to recognise this boundary and keep clinical decisions with qualified professionals.

How much does “Google Gemini for Healthcare Professionals” cost?

The course costs a flat €949 plus VAT per participant – whether online or on-site. This includes 6 hours of live training with a trainer, course materials, a lab environment and a certificate of attendance.

Can I suggest my own date?

Yes. For every location we suggest a date roughly four weeks ahead. In the request form you can always describe your preferred date or period in free text – we check availability and get back to you within one working day.

Is the course online or on-site?

Both are possible: live online in a virtual classroom or on-site in Munich, Salzburg, Berlin, Augsburg, Hanover, Bremen, Stuttgart and Kaiserslautern. We can also run the course exclusively for your team.

Can the course be tailored to our team?

Yes. Tailor-made courses cost approx. €4,500 more, depending on the topic and by arrangement. We agree content, examples and exercises with you in advance.

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