streamlit-fhir-questionnaire 0.1.2

Streamlit component for rendering FHIR Questionnaires and capturing user responses as FHIR QuestionnaireResponses.

streamlit-fhir-questionnaire

A Streamlit component for rendering FHIR Questionnaires and capturing user responses as FHIR QuestionnaireResponse resources.

Features

• Render interactive FHIR Questionnaires in Streamlit apps
• Capture structured data as FHIR QuestionnaireResponse resources
• Support for various FHIR question types (string, text, decimal, date, coding, etc.)
• Conditional question display with enableWhen logic
• Real-time streaming mode for progressive response updates
• Built with React and the Tiro Health report renderer

Installation

pip install streamlit-fhir-questionnaire

Quick Start

import streamlit as st
from streamlit_fhir_questionnaire import streamlit_fhir_questionnaire

# Define a FHIR Questionnaire
questionnaire = {
    "resourceType": "Questionnaire",
    "title": "Patient Information",
    "item": [
        {
            "linkId": "1",
            "text": "What is your name?",
            "type": "string"
        },
        {
            "linkId": "2",
            "text": "What is your date of birth?",
            "type": "date"
        }
    ]
}

# Render the questionnaire and capture responses
response = streamlit_fhir_questionnaire(
    questionnaire=questionnaire,
    key="patient_info"
)

# Display the captured FHIR QuestionnaireResponse
if response:
    st.write("FHIR QuestionnaireResponse:", response)

Parameters

• questionnaire (dict, required): A FHIR Questionnaire resource defining the questions
• initial_questionnaire_response (dict, optional): Pre-populate the form with an initial response
• questionnaire_response (dict, optional): Controlled component state for the current response
• key (str, optional): Unique identifier for this component instance
• streaming (bool, optional): Enable streaming mode for real-time updates

Development

Prerequisites

• Python ^3.11
• Node.js and pnpm
• Poetry for Python dependency management

Setup

1. Clone the repository
2. Install Python dependencies: poetry install
3. Set up frontend:

   cd streamlit_fhir_questionnaire/frontend
   pnpm install
   

Running the Example

poetry run streamlit run streamlit_fhir_questionnaire/example.py

Development Mode

1. Create a .npmrc file in the streamlit_fhir_questionnaire/frontend/ directory with your GitHub token:

   //npm.pkg.github.com/:_authToken=YOUR_GITHUB_TOKEN
   @tiro-health:registry=https://npm.pkg.github.com/
   node-linker=hoisted
   

2. Start the frontend dev server:

   cd streamlit_fhir_questionnaire/frontend
   pnpm run dev
   

3. In __init__.py, set _RELEASE = False to use the dev server

4. Run the Streamlit app:

   poetry run streamlit run streamlit_fhir_questionnaire/example.py
   

Building for Production

cd streamlit_fhir_questionnaire/frontend
pnpm build

License

MIT License - Copyright (c) 2018-2021 Streamlit Inc.

Credits

Built by Tiro Health using the @tiro-health/report-renderer library.