Training course · Perplexity · Healthcare

Perplexity for Healthcare Professionals

AI-powered research with Perplexity: cited answers, source control, Spaces, Deep Research and systematic fact-checking.

Duration
1 day (7 hrs)
Format
Online or on-site
Language
German or English
Participants
open dates or exclusive for your team
Certificate
Certificate of attendance

Overview

“Perplexity for Healthcare Professionals” is designed for roles such as Physicians in hospitals and practices, Nurses and nursing managers and Hospital and practice managers and shows step by step how to use Perplexity productively, safely and transparently in Healthcare – from the fundamentals to advanced workflows.

Perplexity combines language models with live web search and delivers answers backed by numbered citations. That makes it particularly suited to work where currency and traceability matter: market and competitor monitoring, research into regulation and standards, supplier and partner due diligence, or preparing decision papers. In this practical day you learn to phrase research questions precisely, steer the choice of sources deliberately and use follow-up questions to turn an initial answer into a robust research result.

You work with Spaces, where you group research on a topic, add your own files and set instructions for the team. With Deep Research you produce extensive reports that evaluate many sources and bring them together in a structured way. Quality is a key focus: you learn to assess sources, cross-check claims and recognise typical failure patterns such as outdated or misattributed information. We also address data protection and licensing questions for business use. You leave with a reusable research process tailored to your own function.

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 phrase precise research questions and steer the choice of sources deliberately.
  • You assess sources by origin, currency and reliability and trace claims back to the original.
  • You organise research in Spaces and combine web sources with your own documents.
  • You use Deep Research to produce structured reports and decision support.
  • 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 Foundations of AI-powered research
  • How it works: language model, live web search and citations
  • How it differs from a classic search engine and a general chat assistant
  • Framing research questions precisely: time frame, region, source type
  • Follow-ups and drilling down instead of one-off queries
Module 2 Steering and assessing sources
  • Narrowing sources: web, academic literature, your own files
  • Targeting primary sources, official websites and specialist publications
  • Assessing source quality: origin, currency, vested interests
  • Tracing quotes and figures back to the original source
Module 3 Spaces and teamwork
  • Setting up Spaces for topics, projects or client requests
  • Uploading your own documents and combining them with web sources
  • Storing instructions for consistent output formats
  • Sharing research and turning it into pages or reports
Module 4 Deep Research and structured reports
  • Tackling broad questions with Deep Research
  • Producing market overviews, competitor comparisons and topic briefs
  • Turning results into tables, side-by-side comparisons and executive summaries
  • Recognising the limits of in-depth research and refining results
Module 5 Fact-checking, data protection and workflow
  • Systematic fact-checking: counter-research and spotting contradictions
  • Typical failure patterns: outdated, misattributed or fabricated details
  • Data protection, enterprise licences and handling confidential queries
  • A reusable research process and source documentation
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

Experience with online research in a professional context; 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 Perplexity account; we recommend Pro or Enterprise access to use Spaces with files and Deep Research in full.

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.

Suggested dates

All dates are suggestions – your preferred date is always possible.

  • Thu, 26 November 2026 Online Request
  • Tue, 8 December 2026 Berlin Request
  • Thu, 17 December 2026 Online Request
  • Thu, 7 January 2027 Online Request
  • Fri, 15 January 2027 Stuttgart Request
  • Mon, 25 January 2027 Online Request

Frequently asked questions

How does Perplexity differ from ChatGPT or a search engine?

A search engine returns a list of links, and a general chat assistant often answers from its training data. Perplexity searches the web at the moment you ask, summarises what it finds and backs each statement with citations. That makes it particularly well suited to current, verifiable research – although you still need to assess the sources yourself.

Can I rely on Perplexity's citations?

Citations make verification much easier, but they do not replace it. Occasionally a statement is attributed to a source that does not say quite that, or an outdated page is used. In the course you learn a lean fact-checking routine that lets you quickly verify critical statements against the original source.

Is Perplexity suitable for confidential research within a company?

Enterprise plans offer additional commitments on data use and administration. Even so, you should not put trade secrets or personal data into queries unless your internal policy explicitly allows it. We discuss how to phrase queries so that sensitive details stay protected while the research remains useful.

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 “Perplexity for Healthcare Professionals” cost?

The course costs a flat €949 plus VAT per participant – whether online or on-site. This includes 1 training day(s) with a live trainer, course materials, a lab environment and a certificate of attendance.

Can I suggest my own date?

Yes. Our suggested dates are just a guide. In the request form you can always describe your preferred date or period in free text – we check availability and confirm 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 or Kaiserslautern. We can also run the course exclusively for your team.

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