Learning Path 2

Use AI in Medicine

Move from isolated prompts to observable clinical workflows with deliberate human checkpoints.

2 courses 14 lessons 106 minutes
Who this is for
Physicians who already use ChatGPT or another general-purpose AI tool.
What you will leave with
Design an AI-assisted workflow that protects clinical judgment, data quality, and accountability.

A prompt completes a task. Clinical work is a sequence of tasks, decisions, handoffs, and checks.

This path examines that difference. You will learn to map the workflow, define the human checkpoint, build the log before the intelligence, and choose infrastructure that matches the sensitivity of the work.

Course Sequence

Begin in order.

The publication date does not determine the sequence. The learning dependency does.

Course 1

Clinical AI Workflows

Design AI-assisted clinical work as an observable sequence rather than a collection of prompts.

intermediate 39 min 4 lessons

What you will learn

  • Distinguish an AI task from an end-to-end workflow.
  • Place human checkpoints where clinical judgment belongs.
  • Define the logs required before automated interpretation.
  • Choose an infrastructure boundary that matches the data and use case.

Prerequisites

  • Routine use of at least one general-purpose AI assistant.
  1. 01 From Tasks to Workflows Identify the coordination work that remains after an AI model completes an individual task. 11 min
  2. 02 Protect Clinical Sequence Design documentation automation around the order of clinical work and the judgment it must preserve. 8 min
  3. 03 Logs Before Intelligence Establish clean, structured, timestamped ground truth before adding interpretation. 8 min
  4. 04 Choose the Infrastructure Boundary Compare consumer AI with locally controlled models through privacy, governance, cost, and operational requirements. 12 min

Course 2

Ambient Clinical Documentation

Build a vendor-neutral ambient documentation workflow, from pre-encounter preparation through post-encounter verification, grounded in thirty years of clinical documentation history.

intermediate 67 min 10 lessons

What you will learn

  • Explain how clinical documentation evolved from paper charts to ambient AI.
  • Build a pre-encounter, encounter, and post-encounter ambient workflow.
  • Review AI-generated documentation critically before it enters the medical record.
  • Evaluate ambient platforms using durable, vendor-neutral criteria.

Prerequisites

  • Routine use of at least one general-purpose AI assistant.
  1. 01 Why Ambient, Why Now? Understand why ambient clinical documentation matters beyond faster note creation. 6 min
  2. 02 From Paper Charts to Ambient AI Place ambient AI within the longer history of clinical documentation, from 1992 paper charts to the present. 8 min
  3. 03 What Ambient Clinical Documentation Is Understand the ambient documentation pipeline without tying that understanding to a particular product. 6 min
  4. 04 The Three-Phase Ambient Workflow Learn a repeatable, vendor-neutral pre-encounter, encounter, and post-encounter workflow. 8 min
  5. 05 The Patient Conversation Use ambient documentation to improve, rather than degrade, the clinical conversation. 6 min
  6. 06 Review, Verify, and Sign Develop a disciplined post-encounter review habit built around clinical consequence. 6 min
  7. 07 Teach the Tech, Not the Vendor Learn to evaluate ambient technology without becoming locked into a single product. 7 min
  8. 08 Optimizing Your Ambient System Move from simply using ambient documentation to deliberately designing its output. 6 min
  9. 09 Build Your Own Practice Lab Experience the ambient documentation pipeline without purchasing a clinical platform. 7 min
  10. 10 The One-Week Ambient Challenge Evaluate whether an approved ambient workflow improves your work in real practice. 7 min