Summary
In this module, you learned about the key challenges that healthcare organizations experience with their data as they look to implement advanced data analytics and AI. By using healthcare data solutions in Microsoft Fabric, you explored how to break down data silos and harmonize disparate healthcare data into a unified data estate. You can ingest and transform data from clinical, imaging, and other sources into the standardized healthcare data model that comes with the solutions. The healthcare data model is a composite model that uses standards where they exist, such as Fast Healthcare Interoperability Resources (FHIR) and Digital Imaging and Communications in Medicine (DICOM), and it adds schema definitions for those domains where no standards exist, such as patient engagement data. You also learned about the architecture of the solutions and how they're built on top of Microsoft Fabric. As data is ingested, Microsoft Fabric data lakes represent the data by using a medallion architecture. By using the pipelines and notebooks that come with the solutions, you can transform the raw data into standardized data that's appropriate for advanced analytics and AI.
You can review the following reference architecture links to manage healthcare data: