Coordinate Healthcare AI Projects with Microsoft 365

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Overview

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Set up and run the day-to-day coordination work of a healthcare AI initiative using Microsoft 365. This course covers the practical tools and routines that support real entry-level healthcare AI program management work. You'll configure Teams channels and SharePoint repositories with PHI-aware access controls; use Excel to maintain RAID logs, stakeholder lists, and basic cost and resource views; communicate routine project updates to clinical, operational, and compliance stakeholders via Outlook and Teams; map AI-enabled workflows with human review checkpoints; and coordinate vendor and tool onboarding tasks. By the end of this course, you'll be able to stand up and maintain a complete project workspace and trackers for an entry-level healthcare AI workstream. This course is suitable for learners ready to apply Microsoft 365 to real-world scenarios and who have some familiarity with email and shared documents.

Syllabus

Microsoft 365: Coordinate Project Work
- Configure the collaboration backbone of an entry-level healthcare AI initiative. This module covers a Teams channel that anchors project communication, a SharePoint repository connected to it, an Outlook approach for external stakeholders, and vendor and tool onboarding tasks coordinated across all three.
Microsoft 365: Organize Project Files
- Turn a functional healthcare AI project workspace into a well-organized, audit-ready environment. This module covers approved folder conventions, SharePoint taxonomy application, version history for traceability, and PHI-aware access controls so the right people see the right things.
Project Documentation: Record Requirements, Workflow Changes, and Decisions
- Produce the three types of documentation that carry the most weight in an entry-level healthcare AI role: requirements captures, workflow-change notes, and implementation-decision records. Apply a structured standard so senior leads can pick up your documents and act on them without a follow-up conversation.
Project Documentation: Maintain Audit-Ready Project Records
- Turn a set of project documents into an audit-ready record. Apply approved version-control, controlled-access, and traceability practices to healthcare AI documentation so senior leads and reviewers can trust that what's in SharePoint Online reflects the current state of the initiative, and can be defended in a compliance review.
Stakeholder Communications: Identify Info Needs Across Clinical, Operational, and Compliance Audiences
- Learn to read a healthcare AI project’s stakeholder landscape and identify what each participant category—clinical, operational, and compliance—needs to know at each stage of the initiative.
Stakeholder Communications: Apply Templates to Deliver Targeted Updates
- Turn a stakeholder’s identified information needs into an actual message they will read and act on. Apply the three core communication templates—Teams update, Outlook email, and meeting readout—to deliver concise, audience-tuned healthcare AI project updates.
Workflow Management: Analyze Workflow Steps and Identify AI Touchpoints
- Analyze healthcare workflows from a Healthcare AI Coordinator perspective by identifying AI output touchpoints, required human review checkpoints, and potential exception paths. This foundation supports accurate workflow tracking, risk identification, and effective issue management.
Workflow Management: Track Handoffs, Review Checkpoints, and Risks
- Turn the analyzed workflow into an operational tracking system that a team can actually use. Apply workflow tracking methods to document task handoffs, review checkpoints, and exception paths, and maintain a routine risk register that surfaces operational risks to senior leads before they compound into blockers.
Excel for PMs: Core Structures for Project Tracking
- Build a single healthcare AI project workbook in Excel with three tabs, an expanded RAID log (risks, assumptions, issues, dependencies, actions, and decisions), a stakeholder list that evolves into a RACI matrix, and a cost and resource summary (covering labor and non-labor resources, with CapEx vs OpEx and blended vs standard rate concepts introduced at recognition level), using core Excel structures (tables, filters, basic formulas). This is the foundational workbook work that Module 2 builds on with data validation, formatting, and sharing practices.
Excel for PMs: Validation, Formatting, and Shared-Workbook Practices
- Turn a working tracker into one that stays accurate over time. Apply data validation to prevent entry errors, conditional formatting to make status visible at a glance, and shared-workbook practices, such as access controls, edit protection, and change tracking, to keep the tracker useful when a team is contributing to it.
Project Module: Set Up a Healthcare AI Project Workspace and Trackers
- Produce the artifact package an entry-level Healthcare AI Coordinator delivers on their first initiative: a configured project workspace, a foundational requirements capture, a targeted stakeholder update, an annotated workflow map, and a working task and decision log. 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.

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