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This module introduces the concepts for ingesting clinical data in FHIR format into healthcare data solutions and how the system transforms data into the healthcare data model. By using the interactive exercises, you can explore how to ingest clinical data by using the different ingestion options and unified folder structure for ingesting data.

Learning objectives

This module explains the following concepts:

• Concepts for ingesting clinical data in FHIR format and how the system transforms data into the healthcare data model
• Unified folder structure for ingestion
• How to ingest data by using different approaches
• Microsoft Fabric capabilities that help you explore and analyze the ingested data

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Care management analytics in healthcare data solutions provides a comprehensive analytical platform essential for optimizing patient outcomes and resource utilization in current healthcare landscape. This module covers the care management analytics capability of healthcare data solutions in Microsoft Fabric. You explore the components, deploy them into your Fabric workspace, and learn to use the care management analytics pipelines to construct analytical models, conduct patient population studies. You use the Power BI reports to visually compare various patient populations.

Learning objectives

This module explains the following concepts:

• Overview of Care Management analytics in healthcare data solutions
• How to deploy the solution into your Fabric workspace
• Analyze your care management efforts using the data in your Fabric workspace

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The FHIR service in Azure Health Data Services allows for rapid exchange of health data by using the Fast Healthcare Interoperability Resources (FHIR®) data standard. Healthcare professionals can store and exchange Protected Health Information (PHI) in the cloud by using the FHIR service.

Learning objectives

This module explains the following concepts:

• FHIR service, its capabilities, and its use cases
• FHIR service data and technical architecture
• Integration with Healthcare data solutions in Microsoft Fabric
• FHIR RESTful API framework
• FHIR standards, resource elements, structures, and hierarchy (optional)

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Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) in a Fabric lakehouse is an optional capability of healthcare data solutions in Microsoft Fabric. By using OMOP Common Data Model, you can construct statistical models, conduct population distribution studies, and use Power BI reports to visually compare various interventions and their effects on patient outcomes. Researchers can perform comparative analysis, such as evaluating different procedures and drug exposures or examining correlations between drug exposures and condition occurrences.

Learning objectives

This module explains the following concepts:

• OMOP transformations in healthcare data solutions in Microsoft Fabric
• How to deploy and use OMOP transformations
• How to use notebooks to run a sample scenario with the gold lakehouse

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Healthcare data solutions in Microsoft Fabric help you ingest Digital Imaging and Communications in Medicine (DICOM) data. With the DICOM transformation solution, you can ingest, store, and analyze imaging metadata across various modalities. The imaging and clinical data are stored in Fast Health Interoperability Resources (FHIR) and Observational Medical Outcomes Partnership (OMOP) format. This data helps clinicians and researchers interpret image findings in the correct clinical context, leading to higher diagnostic accuracy, informative clinical decisions, and improved patient outcomes.

Learning objectives

This module explains the following concepts:

• The DICOM transformation capability and how to ingest DICOM imaging data in FHIR format
• Different approaches to use for ingesting data
• Microsoft Fabric capabilities that help you explore and analyze the ingested data

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Microsoft for Healthcare makes enterprise-wide health team collaboration a reality by investing in key capabilities around more secure collaboration, care coordination, and continuous patient monitoring. In this dynamic healthcare environment, organizations can connect, engage, and efficiently manage a frontline healthcare workforce with tools that help them provide the best possible care.

In this Learning Path, you gain a foundational understanding of Microsoft for Healthcare and how it fosters health team collaboration. You’re guided through practical hands-on exercises to set up healthcare applications deployed through Microsoft for Healthcare using Dynamics 365, Power Platform, Microsoft 365, and Azure in your own environment. You dive into various modules of Microsoft for Healthcare applications, including Care Management and Home Health.

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Social determinants of health (SDOH) are social conditions that contribute to an individual’s or a population group’s health outcomes. Ingesting SDOH datasets into a standardized healthcare data model in a Microsoft Fabric data lake unlocks many analytical capabilities for your organization to gain a comprehensive understanding of a patient’s health profile. In this module, you learn about the SDOH datasets – transformations capability and explore its components. You also deploy the solution into your Fabric workspace and then configure and run the notebooks to transform the SDOH datasets into the Fabric lakehouse.

Learning objectives

This module explains the following concepts:

• SDOH datasets – transformations capability in healthcare data solutions
• How to deploy the solution in your Fabric workspace
• How to analyze SDOH data in your Fabric workspace

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With CMS Claims data transformations, you can ingest, store, and analyze claims data in Centers for Medicare & Medicaid Services (CMS) Claim and Claim Line Feed (CCLF) format. CMS Claims data transformations is an optional capability of healthcare data solutions in Microsoft Fabric. In this module, you learn about the CMS Claims data transformations capabilities that are available in healthcare data solutions in Fabric. This module explains how to configure and run the notebooks to transform healthcare data from the CCLF format and then ingest it into the Fabric lakehouse.

Learning objectives

This module explains the following concepts:

• CMS Claims data transformations in healthcare data solutions
• How to deploy the solution into your Fabric workspace
• How to analyze claims data in your Fabric workspace

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This module provides a foundational description of the integration and interoperability challenges and how Microsoft for Healthcare can help overcome those challenges. It provides an overview of the integration and interoperability solutions, such as Azure Health Data Services, Data Integration Toolkit, Dataverse Healthcare API, Data Ingestion ARM Template, and Virtual Health Tables.

Learning objectives

In this module, you’ll:

• Learn about the integration and interoperability challenges in the healthcare and life sciences industries.
• Learn how Microsoft for Healthcare solves integration and interoperability challenges.

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Microsoft for Healthcare helps deliver meaningful outcomes across the healthcare journey. It empowers healthcare organizations and partners to innovate with AI responsibly at every layer of the cloud. From cloud infrastructure to data and AI, security surrounds everything that people do. Microsoft for Healthcare provides trusted, integrated, and powerful capabilities. These capabilities help make it easier for organizations to safeguard people, health data, and infrastructure, empower the healthcare workforce, enhance patient and member experiences, unlock value from clinical and operational data and accelerate research, discovery, and development.

Learning objectives

This module explains the following concepts:

• Key challenges in the healthcare industry
• How Microsoft for Healthcare and AI helps resolve these challenges
• Capabilities that help you innovate with AI responsibly

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