The goal of a schema definition is to describe the data source (its shape such as field names, data types etc.) to the system. Data source schemas are provided to the engine as a configuration of FHIR StructureDefinition resources. The tutorial explains how schemas are defined and how they provide metadata and validation for input data, ensuring the mapping process starts with well-defined data structures.

This tutorial demonstrates the process of creating mappings. It showcases the use of HL7 FHIR resource templates and the toFHIR-specific template language. The video explains how to use FHIRPath expressions and toFHIR methods to define mappings effectively.

Mapping variables in toFHIR enable users to create and reuse repetitive expressions efficiently. This feature enhances the flexibility and reusability of your mappings, making your overall mapping process more streamlined. Follow along with the video to understand how mapping variables can optimize your toFHIR workflows.

toFHIR empowers users to set preconditions for mappings, acting as filters to determine whether a mapping should be executed based on specific conditions. By setting clear criteria based on the source data, you can filter out records that do not meet the specified conditions. In this tutorial video, you'll explore the process of defining a precondition for an example mapping, gaining a comprehensive understanding of how preconditions enhance mapping process.

Mapping contexts in toFHIR, which are simple CSV files, are categorized as concept-map and unit-conversion. The objective of a mapping context is to provide a term/concept mapping or unit conversion by defining these in separate CSV files instead of embedding into the mapping scripts depicted with FHIRPath. These contexts play a vital role in facilitating the exchange and mapping of healthcare data. Concept-maps enable the mapping of concept codes between different systems, while unit-conversion focuses on mappings between different healthcare data units. In this tutorial video, you'll learn how to define a mapping context and effectively utilize it within your mappings, expanding your capabilities in toFHIR.

Jobs serve as complete ETL pipelines, bringing together essential definitions such as schemas, mappings etc. When executing a job, toFHIR seamlessly orchestrates the entire process, from reading the specified data to executing the defined mappings and writing the results to the designated FHIR sink. In this tutorial video, you'll learn the step-by-step process of defining a job, including configuring data source settings, setting up FHIR sink settings, and selecting mappings to be executed

The toFHIR GUI provides a separate panel for the execution of jobs. After executing a job, users can easily access valuable information such as the number of successfully created FHIR resources and any encountered errors. Learn how to examine logs for any faulty resources and take appropriate actions to ensure optimal mapping outcomes. This video tutorial demonstrates how to execute a job seamlessly within the GUI and provides guidance on analysing the execution results.

toFHIR provides a built-in testing feature that allows you to validate your mapping definitions at the time of its development. Run tests to ensure that the mappings are working as expected and that the generated FHIR resources meet the desired standards. This video shows how to test your mappings in toFHIR.

toFHIR can utilize remote FHIR terminology services and allows create and manage your own local terminology service. This tutorial video unveils the process of creating a local terminology service from scratch, empowering you to ensure accurate data representation and seamless concept exchanges. It also presents a comprehensive understanding of how to leverage the local terminology service within your mappings for enhanced healthcare data integration.