Webinar: Introduction to FHIR for Research
Introduction to FHIR for Research is a three-hour training course that aims to provide NIH research scientists and program officers with an understanding of how FHIR could impact their research, and how they can take advantage of it. This webinar covers the background and context of FHIR, what data and tools are available, and examples of research using FHIR. It is broken into three parts:
Part 1: Background and Context of FHIR
This section provides essential background and context on FHIR, including the history and evolution of the standard, its relation to similar frameworks, and its components and data structure.
Part 2: The FHIR Ecosystem
After discussing FHIR background, we'll next turn to discussing the broader ecosystem of FHIR systems and capabilities practitioners can hope to leverage. This section will explore the extent of systems, tools, and applications available to users.
Part 3: Working with FHIR
We will now explore a detailed set of applications for FHIR starting with a sampling of recent FHIR uses in both industry and academia. We will then provide a series of case studies leveraging both Python and R to demonstrate how FHIR can be used to extract and utilize medical data.
Hands-On Workshop: Working with FHIR for Research
Note: All the required links needed for each exercise listed below are located here - FHIR for Researchers (nih-odss.github.io)
The Working with FHIR for Research Workshop is a hands-on training exercise that introduces learners to the methods for extracting and manipulating health data using FHIR standards for the purpose of research using R and Python. The workshop steps students through the following four, hands-on exercises the encompass the following topics:
Exercise 0: Getting Started
Exercise 0 introduces learners to the basic mechanisms for working with FHIR by completing the following steps: establishing a connection to the client server, formatting and submitting a query to the server, processing response data from the FHIR server, and viewing resulting data to confirm it was successfully pulled from the remote server. It includes hands on exercises in both R and Python
Exercise 1: Patients Prescribed Opioids
Exercise 1 steps learners through a use case for patients prescribed opioids to teach the following concepts: understanding a FHIR server’s capabilities, reading FHIR specifications, understanding and searching for FHIR Resources, processing paginated responses, and integrating with other, non-FHIR Application Programming Interfaces (APIs). It includes hands on exercises in both R and Python.
Exercise 2: "Kids First" Data
Exercise 2 steps through a use case leveraging Kids First data to enable learners to better understand how to query FHIR resources in various ways to enable visualizing and analyzing data. It includes hands on exercises in both R and Python.
Exercise 3: Drug-Drug Interactions
Exercise 3 applies knowledge gained in the previous exercises to identify drug-on-drug interactions using FHIR data and NLM APIs. It includes hands on exercises in both R and Python.
Exercise 4: Drug-Drug Interactions
Exercise 4 is a self-paced web-based training that provides learners with a broad view of Electronic Health Records (EHR), terminology systems, and how United States Core Data for Interoperability (USCDI) and Implementation Guides like US Core enable remote access and interoperability. This exercise is meant to augment the materials in Exercises 0-3.
Python Workshop Recording
R Workshop Recording
