This module builds analytical skills for examining existing healthcare workflows and identifying their automation components—triggers, conditions, actions, and exception paths—to support maintenance, troubleshooting, and improvement recommendations. You will be able to break down an existing workflow into its component parts and identify opportunities for automation improvements using Microsoft Power Automate logic in Microsoft Cloud for Healthcare. Understanding how automation works "under the hood" is essential for troubleshooting failed flows and recommending process improvements—tasks entry-level staff perform when flows stop working or processes change.

This module introduces how Microsoft Cloud for Healthcare connects with external source systems, including EMRs, scheduling platforms, referral systems, and operational databases, explaining where integration points exist, what data moves between them, and why integration matters for unified healthcare operations. You will be able to explain the integration landscape and identify where data exchange occurs between systems using Microsoft Cloud for Healthcare connectors and Azure Health Data Services (awareness level). Integration is what turns disconnected healthcare tools into a unified platform; without it, staff manually re-enter data across systems, introducing errors and delays.

This module provides practice validating integrated healthcare records, checking whether referral data that moved from a source system arrived correctly in Microsoft Cloud for Healthcare by comparing against predefined field mappings and reconciliation criteria. You will be able to apply validation checks to integrated records using field mapping specifications and identify discrepancies that indicate integration errors in a referral routing workflow. Integration validation is how organizations catch data transfer errors before they affect operations. A missed field or format mismatch can break downstream automation, reporting, and patient workflows.

This module introduces healthcare interoperability, the ability of different systems to exchange, interpret, and use data, including FHIR and HL7 standards that enable standardized healthcare data exchange in Microsoft Cloud for Healthcare using Azure Health Data Services. You will be able to explain why interoperability matters, how FHIR resources structure healthcare data, and how HL7 messaging supports batch data exchange. Interoperability is what allows healthcare organizations to exchange patient data with other organizations, specialists, labs, and payers; without it, every external communication requires manual data entry or custom one-off connections.

This module provides practice in interpreting interoperable healthcare data, such as reading FHIR resources and HL7 message segments to extract information needed for referral, encounter, and care coordination workflows in Microsoft Cloud for Healthcare. You will be able to read standardized healthcare data exchanges and correctly interpret resource fields to support downstream administrative tasks. When interoperable data arrives from an external system, someone needs to read it and act on it. Entry-level staff are often the first to process incoming referrals, results, and care coordination updates that arrive in standard formats.

This module builds analytical skills for selecting the right Power Platform component based on the healthcare administration need: data capture (Power Apps), workflow automation (Power Automate), or reporting/visualization (Power BI). Learners will be able to evaluate healthcare scenarios and determine which tool is the appropriate solution using Microsoft Power Platform selection criteria. Choosing the wrong tool creates wasted effort and poor solutions; a dashboard doesn't solve a data capture problem, and an app doesn't solve a reporting need.

This module provides hands-on practice deploying a simple Power Platform solution: building a Power App for patient intake tracking connected to Dataverse, with a basic notification flow in Power Automate. Learners will be able to use Power Apps and Power Automate together to capture healthcare data and trigger automated actions in a connected Microsoft Cloud for Healthcare solution. Building connected solutions with Power Platform is the fastest-growing skill requirement for healthcare administration technology roles.

This module builds analytical skills for interpreting healthcare operational dashboards in Power BI: identifying trends, flagging metrics outside acceptable thresholds, and summarizing findings for administrative stakeholders. Learners will be able to read a healthcare operational dashboard and extract actionable insights for decision-making. Dashboards are useless if nobody can read them; entry-level staff who can interpret data and summarize findings for managers provide immediate operational value.

This module provides hands-on practice using Microsoft Copilot to support healthcare administration workflows, such as generating summaries of patient follow-up information, drafting administrative messages, and surfacing workflow-relevant details using structured prompts via Virtual Browser. Learners will be able to use Copilot to produce useful first-draft content that supports healthcare operations under human review. Copilot doesn't replace healthcare professionals; it accelerates routine drafting and summarization, so staff spend time on judgment, not typing.

This module builds critical evaluation skills for reviewing AI-generated healthcare content, such as checking outputs against source records for factual accuracy, scanning for inappropriate PHI inclusion, and assessing whether the content is genuinely useful for its intended workflow purpose in Microsoft Cloud for Healthcare. Learners will be able to systematically evaluate a Copilot-generated draft and produce a revised version that is safer, clearer, and more appropriate for healthcare administration. AI outputs are never "done"; they're first drafts that require human judgment. The evaluation skill is more important than the prompting skill because this is where errors, privacy risks, and misinformation get caught.

This module addresses responsible AI principles specifically for healthcare, covering privacy protection, human oversight requirements, bias recognition, clinical-risk awareness, and validation requirements for AI-generated healthcare content. Learners will be able to identify responsible AI risks in healthcare use cases and recommend mitigation steps using Microsoft Responsible AI principles and healthcare-specific governance requirements. As AI tools become embedded in healthcare operations, every staff member must understand the risks, limitations, and governance controls that keep AI safe for patients.

This project integrates skills from across courses on workflow automation design, system integration validation, interoperability interpretation, Power Platform component selection, dashboard analysis, and responsible AI evaluation into a comprehensive integrated healthcare workflow design document. Learners will be able to design an end-to-end healthcare workflow using Microsoft Power Platform, Power Automate, Power BI, and Copilot-assisted tools as reference context, with integration patterns, interoperability standards, and responsible AI considerations documented throughout. Integrated workflow design is the culminating skill for healthcare technology roles; this deliverable demonstrates the ability to connect automation, data, and AI tools into a cohesive solution that serves patient care.