The IELTS Co-Owner Lost 94% of Its Value. The Reason: Visas.

Class Central is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Microsoft

Accelerate Healthcare AI Coordination with Microsoft Copilot

Microsoft via Coursera

Go to class Write review

Overview

Google, IBM & Meta Certificates – 40% Off
One Coursera Plus subscription covers most Professional Certificates on Coursera.
Unlock All Certificates
Use Microsoft Copilot to speed up routine project coordination tasks while building the sound judgment to verify, refine, and safely distribute AI-generated outputs. This course covers prompt writing, drafting meeting summaries, milestone tracking in Planner, and evaluating Copilot outputs against accuracy and PHI-safety criteria. You'll write effective Copilot prompts for healthcare AI program management tasks; draft and validate meeting summaries, action lists, and status updates using Copilot in Word, Teams, and Outlook; track milestones, task ownership, and blockers in Microsoft 365 Planner; apply basic meeting facilitation practices alongside Copilot-assisted summarization; and evaluate Copilot outputs for factual accuracy, PHI sensitivity, and appropriate task ownership before distribution. A GenAI Literacy module on responsible AI augmentation for healthcare program managers is included. This course is suitable for learners with foundational Microsoft 365 collaboration skills and who are ready to layer Copilot into established Microsoft 365 coordination routines. No prior AI tool experience is required.

Syllabus

  • Copilot Prompting: Apply the Five-Component Prompt Framework
    • Learn the five-component prompt framework: how role, task, context, constraints, and format transform a vague request into a Copilot prompt that produces a usable first-pass draft. Apply the framework to a routine healthcare AI PM task and refine the prompt through iteration to improve output quality.
  • Copilot Prompting: Distinguish Prompt Patterns by Task Type
    • Different Copilot tasks call for different prompt patterns. Learn to distinguish the four patterns used most often in healthcare AI PM work, such as drafting, summarization, comparison, and follow-up generation, and match each pattern to the task type it fits.
  • Meeting Summaries: Prepare Source Notes and Draft with Copilot
    • Build the two connected halves of the Copilot meeting-summary loop: Prepare an agenda and structured notes that give Copilot something to work with, then use Copilot prompts to draft the summary, action list, or status update. The validation half of the loop comes next.
  • Meeting Summaries: Validate and Refine Before Distribution
    • Close the meeting-summary loop with the practice that turns Copilot drafts into team-ready documents. Apply a structured validation checklist against source notes to catch fabrication, missing content, PHI mishandling, misassigned actions, and tone mismatches, then refine the draft to the point where a senior lead could distribute it with only light review.
  • Planner Coordination: Track Milestones with Board and Calendar Workflows
    • Stand up the Planner board that anchors a healthcare AI initiative's week-to-week coordination. Apply the routines that keep milestones, dependencies, and follow-ups visible, including Planner buckets and tasks, calendar synchronization for milestone dates, and the disciplined update rhythm that senior leads rely on.
  • Planner Coordination: Analyze Status Inputs to Identify Issues
    • Turn the Planner board into a working tool for weekly status review. Analyze the routine status inputs, including task states, dates, assignments, and dependencies, to identify the four issue categories that most often derail entry-level initiatives: delayed tasks, missing owners, unresolved dependencies, and active blockers.
  • Output Evaluation: Apply the Six-Dimension Review Framework
    • Learn to review a Copilot-generated project artifact the way an entry-level Healthcare AI Coordinator has to, against a structured six-dimension framework that catches the issues most likely to matter. Accuracy, PHI sensitivity, task ownership, deadlines, dependencies, and blockers each get their own criteria, and each has clear remediation or escalation guidance.
  • PHI Safety: Redact Inputs, Minimize Exposure, Route Incidents
    • Learn the input-side and incident-side PHI practices that keep sensitive content out of Copilot in the first place, and route incidents correctly when exposure happens anyway. Apply redaction practices to prompt inputs, apply the minimum-necessary principle to what Copilot sees, and document the escalation route for PHI exposure incidents.
  • GenAI Module: AI Augmentation for Healthcare Program Managers
    • Build the mental model for how generative AI actually fits into an entry-level Healthcare AI Program Manager's work. This module frames Copilot and other generative AI tools as augmentation, such as extending what a PM can accomplish and not replacing PM judgment, and introduces the Responsible AI principles that guide when, how, and whether to use these tools on routine healthcare AI PM tasks.
  • Project Module: Create a Copilot-Assisted Project Status Packet with PHI Review
    • Bring together everything from LC 3 to produce the Copilot-assisted artifact package an entry-level Healthcare AI Coordinator delivers as a routine weekly deliverable: a project status packet built from Copilot-drafted content, informed by the Planner board state, and reviewed against both the evaluation framework and PHI-safe practices. You'll take the same discovery inputs a real coordinator would receive and produce five integrated artifacts that a Senior AI Program Manager could pick up and act on without rework.

Taught by

Microsoft

Tags

Reviews

Start your review of Accelerate Healthcare AI Coordination with Microsoft Copilot

Go to class

Never Stop Learning.

Get personalized course recommendations, track subjects and courses with reminders, and more.

Sign up for free
Someone learning on their laptop while sitting on the floor.