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FRED - FHIR Resource Editor

What is FRED?

FRED is an open source web application that enables users to edit JSON FHIR resources and FHIR bundles. Built as an HTML5 app, FRED runs entirely within your web browser - no data is sent to a server. Note - the project is currently under active development. Code is rough, there are bugs and features may change or be removed!

Try it with...

DSTU2:

STU3:

Planned features

Please see roadmap.md

API

Url Parameter Value Action
resource Escaped url for FHIR resource on CORS enabled server (including open FHIR servers) Launches with resource open.
profiles Escaped url for summarized FHIR profiles (see building resource profiles below) on a CORS enabled server. Included are /profiles/dstu2.json (DSTU2) and /profiles/connect12.json (May 2016 connectathon) Configures FRED to support for a particular version of FHIR.
remote 0 or 1 Supports controlling FRED from another web application (using postMessage) when set to 1 (demo).
warn 0 or 1 If set to 0, will suppress a warning when navigating away from the page. Useful when developing with auto-reloading.

Tech

Install FRED locally

  1. Install NodeJs from https://nodejs.org

  2. Clone this repository

    git clone https://github.com/smart-on-fhir/fred
    cd fred
    
  3. Install the dependencies

    npm install
    
  4. Run the dev server

    npm run dev
    
  5. Browse to http://localhost:8080

Commands

Action Command
Start Dev Server npm run dev
Build Static JS Bundle npm run build
Run Tests npm run test
Run Tests on Edit npm run test-watch

Building Resource Profiles

To reduce load time, FRED uses a simplified copy of the (>15mb!) JSON FHIR resource profiles. To convert the FHIR resource profiles into this format, ensure the desired profile bundles and valueset bundles are in the fhir_profiles subdirectory and run npm run build-profiles

About

FRED is a project of SMART Health IT, a joint effort of the not-for-profit institutions, Boston Children’s Hospital Computational Health Informatics Program and the Harvard Medical School Department for Biomedical Informatics.

To stay updated on the project follow @gotdan and @smarthealthit on twitter!

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