Do clinical and non-clinical staff train together?

Clinical and non-clinical staff together, usually: physicians, nurses, department leads, administrators, patient services, and health-tech teams. We can split cohorts by role if your organization wants examples matched to each group's day, and we plan that mix with you before the first session.

Do people need a technical background to keep up?

No. There's no coding or data-science prerequisite. The only thing that matters is familiarity with your own workflows, since the training builds directly on documents your teams already handle.

How much time does this take out of a clinic week?

Two days, roughly 13 hours of instruction, onsite or as live-online sessions, usually split into half-day blocks so clinic and shift schedules keep running.

Will the syllabus actually fit our hospital or clinic?

It's built to. Before the sessions, someone from Zeo looks at documents and workflows from your hospital or clinic. What we find becomes the cases and prompts in the room.

What will this cost a hospital?

Four things decide it: how many people, which delivery format, how much customization, and location. Two hospitals rarely need the same program, so we quote each one on its own. Share your teams and goals and we'll return a proposal shaped around them.

What do we keep once the sessions are over?

Your team keeps the prompt library and document templates. The sessions also produce a 90-day rollout plan. Questions afterward go to us directly, and a refresher only happens if your usage grows into wanting one.

Which specific tools show up in the exercises?

ChatGPT, Microsoft Copilot, and Gemini are what the exercises run on by default, since almost every organization can already reach at least one of them. If yours has approved an enterprise tool or an EHR-integrated assistant instead, we build around that one.

Does any real patient data show up during training?

No. Every case in the room is invented, or fully anonymized before it gets there. A whole module covers keeping patient data out of any tool nobody has approved for it. Handling that correctly is one of the outcomes the program trains toward.

AI Training · Healthcare

AI Training for Healthcare

Clinical documentation, patient communication, and admin workflows all run on text, and text is exactly what generative AI handles best.

This training turns that opening into safe, compliant daily habits, built specifically for clinical and administrative staff.

modules: 6
hours: 13

Some of the 500+ brands we've worked with

Selected brands we’ve worked with across industries.

See all references

This training teaches clinical and administrative staff to draft visit notes, discharge summaries, referral letters, and payer correspondence with generative AI, then check each draft before it reaches a record. It covers patient communication at the right reading level and a review-before-sign habit for every workflow. GDPR and KVKK obligations stay intact throughout.

Clinicians already spend a large share of the day on documentation, and untrained use of consumer chatbots risks a wrong drug name slipping into a summary. This training builds safe habits, not AI engineers — it hands the hours back to patients. The AI training catalog covers the wider life-sciences side separately.

Notes and summaries eat the clinical day

Clinicians spend about 40% of the day writing, not treating — AI-assisted drafting buys back time, not a lower bar for the record.

Billing queries never stop

Prior authorizations, billing questions, and payer letters are repetitive, rule-bound text — exactly what a guided model handles well.

Who has time to write patient instructions twice?

Discharge instructions and handouts need the right reading level for every patient and language — AI drafts the first version, a teammate still checks it.

Staff already use ChatGPT without asking

Someone's already pasting notes into a consumer chatbot to save time — training replaces the guesswork with a sanctioned, logged workflow.

Everyone already has the license

The tools already sit inside Word, Outlook, and the browser — what to hand the model and what to keep for a person is the part nobody trains.

01
Generative AI foundations for clinical and admin teams
120 minBeginner
What large language models handle well and where they quietly get things wrong. Healthcare raises the stakes on both. Clinical and administrative staff leave this session speaking the same language about what to delegate and what to check.
What a language model does when it drafts a note
Where hallucination shows up in clinical text
AI's foothold in Word and Outlook, including your EHR
Tasks worth delegating, decisions that stay with a person
One experiment, week one
02
Prompt structure for clinical and administrative documents
120 minBeginner
This module teaches one repeatable structure (role, context, task, format, checks) and applies it only to documents your teams write themselves, so nothing here is a generic stand-in.
One prompt template, reused across every clinical document type
Giving the model context while patient identifiers stay out
Rewriting a weak first draft instead of settling for it
Setting tone and reading level for what a patient will read
Building the first entries in a team prompt library
03
Clinical documentation and admin workflows in practice
180 minIntermediate
Notes, summaries, referral letters, and payer correspondence go through the same drafting flow here, one clinician-reviewed step at a time, and a review-before-sign check sits at the end of every single one before it reaches the record.
Turning structured input into visit notes and discharge summaries
Referral letters that carry their sources with them
Payer and insurance correspondence, drafted and checked
Shift handovers and meeting notes turned into structured summaries
Reusable department-wide templates
Review-before-sign: the last check before anything is signed
04
Patient communication and triage support
150 minIntermediate
Patient-facing text is everywhere in a clinic: instructions, education material, reminders, and front-desk responses. This module covers writing all of it without losing the plain-language tone patients need. It also draws the line for triage support, marking where AI can help and where a clinician has to decide.
Post-visit instructions at the right reading level
Message flows for appointments, prep, and follow-up
FAQ pages and patient education material, drafted and reviewed
Multilingual patient communication
Where AI can support triage, and where it must not decide
Escalation: the point where a human takes back the case
05
Patient data and privacy under compliance rules
120 minIntermediate
GDPR, KVKK, and patient-privacy rules become concrete here: what can go into an AI tool, what never does, and how to write a policy staff will follow.
What counts as personal and special-category health data
De-identification and synthetic examples in practice
Why a consumer chatbot and an enterprise tool handle your data differently
Where the line sits when a workflow touches EHR data
An AI usage policy your healthcare organization will use
What to log when AI touches a document
06
Adoption and rollout playbook
90 minAdvanced
This module is where individual skill turns into organizational habit: pilots, champions, and the measurement to know whether either is working, plus what keeps usage safe once we're gone.
Picking a first pilot with time savings you can measure
Naming champions department-wide
Measuring adoption by what staff actually do with it
Handling resistance and the reasonable fears behind it
The 90-day rollout plan you build during the sessions

What you will learn

Your visit notes, sign-off ready
Write prompts your team can reuse on the documents it produces every week
Audience-fit patient instructions
Handle patient data so GDPR and KVKK boundaries hold, workflow by workflow
Catch a hallucinated drug name before it reaches a chart
Keep a working prompt library going for your department after the sessions end
Move from a single pilot to a full rollout with outcomes you can measure

Who should attend

Physicians and clinical department leads
Nursing directors and head nurses
Hospital administration and operations teams
Patient services and call-center teams
Health-tech and HIS teams, including EHR product teams
Quality and compliance officers

Clinical shifts set the shape of the two days. Sessions usually break into half-day blocks, and onsite and live-online formats cover the same syllabus.

Format: Onsite or live online
Duration: 2 days (about 13 hours, can be split into half-day sessions)
Group size: Up to 20 participants per group
Language: English or Turkish
Materials: Prompt library, document templates, and exercise workbook
Certificate: Certificate of completion

Using AI in Life Sciences6 modules · 13 hoursPharma and life-sciences teams train on scientific summarization, medical and regulatory content support, pharmacovigilance triage, and governed adoption with qualified human review throughout.View training

AI Training for Veterinary Teams6 modules · 10 hoursA veterinary practice writes consultation notes and discharge instructions every day. Owner messages add to the load. This program trains clinical and support staff to draft that text with AI, built around clinician review, and never touches diagnosis, prescribing, or treatment planning.View training

AI Literacy & Prompt Engineering6 modules · 13 hoursAI literacy and prompt engineering training for your whole company. Teams practice on their own workflows across ChatGPT, Copilot, and Gemini, and walk out with a shared prompt library they use again the next day.View training

Preparing Teams for the EU AI Act6 modules · 12 hoursEU AI Act readiness training for compliance, legal, risk, HR, IT, procurement, and business teams: map AI use, build literacy, ask sharper vendor questions, and leave with an accountable action plan.View training

Start with the care setting and the staff attending. Then name the clinical or administrative documents they own. We will propose sessions that fit their week and preserve every clinician review point.

Two colleagues updating a workflow board and checking a process change

Do clinical and non-clinical staff train together?
Clinical and non-clinical staff together, usually: physicians, nurses, department leads, administrators, patient services, and health-tech teams. We can split cohorts by role if your organization wants examples matched to each group's day, and we plan that mix with you before the first session.
Do people need a technical background to keep up?
No. There's no coding or data-science prerequisite. The only thing that matters is familiarity with your own workflows, since the training builds directly on documents your teams already handle.
How much time does this take out of a clinic week?
Two days, roughly 13 hours of instruction, onsite or as live-online sessions, usually split into half-day blocks so clinic and shift schedules keep running.
Will the syllabus actually fit our hospital or clinic?
It's built to. Before the sessions, someone from Zeo looks at documents and workflows from your hospital or clinic. What we find becomes the cases and prompts in the room.
What will this cost a hospital?
Four things decide it: how many people, which delivery format, how much customization, and location. Two hospitals rarely need the same program, so we quote each one on its own. Share your teams and goals and we'll return a proposal shaped around them.
What do we keep once the sessions are over?
Your team keeps the prompt library and document templates. The sessions also produce a 90-day rollout plan. Questions afterward go to us directly, and a refresher only happens if your usage grows into wanting one.
Which specific tools show up in the exercises?
ChatGPT, Microsoft Copilot, and Gemini are what the exercises run on by default, since almost every organization can already reach at least one of them. If yours has approved an enterprise tool or an EHR-integrated assistant instead, we build around that one.
Does any real patient data show up during training?
No. Every case in the room is invented, or fully anonymized before it gets there. A whole module covers keeping patient data out of any tool nobody has approved for it. Handling that correctly is one of the outcomes the program trains toward.

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AI Training for Healthcare