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Official URL: http://spezi.health/fhir/ImplementationGuide/fhir.spezi				Version: 0.1.0
Draft as of 2025-08-06				Computable Name: SpeziFhirIG

Stanford Spezi FHIR Implementation Guide

Overview

Stanford Spezi is an open-source, modular ecosystem for building standards-based digital health applications on iOS and other platforms. This Implementation Guide provides comprehensive guidance on representing mobile health data using HL7 FHIR resources, enabling seamless integration with healthcare systems and clinical workflows.

Getting Started

For App Developers

Start building mobile health applications with standardized data representation:

→ Mobile Health Data Implementation

→ Questionnaires and Surveys Implementation

Implementation Guide Contents

Section	Description	Audience
Implementation Overview	High-level architecture and navigation	All users
Mobile Health Data	HealthKit integration, data transformation, clinical mapping	Developers, Clinical informaticists
Questionnaires	FHIR questionnaire creation, ResearchKit integration	Developers, Researchers
Terminology	Code systems, value sets, and standardized vocabularies	Clinical informaticists
FHIR Profiles	Formal resource definitions and constraints	Technical implementers
Examples	Complete implementation examples and use cases	All users

Use Cases

Clinical Care

• Remote patient monitoring
• Chronic disease management
• Preventive health screening
• Patient engagement platforms

Research

• Digital biomarkers collection
• Longitudinal health studies
• Clinical trial data capture
• Population health research

Healthcare Integration

• EHR data synchronization
• Clinical decision support
• Quality measure reporting
• Population health analytics

Getting Help

• GitHub Repository: Stanford Spezi on GitHub
• Documentation: Spezi Documentation
• Community: Join discussions and get support from the Spezi community

Publisher

This Implementation Guide is developed and maintained by Stanford Biodesign Digital Health at Stanford University. It is written in FSH and built with SUSHI and the IG Publisher.

Licensing

This implementation guide is released under the MIT license. However, it includes examples using terminologies such as SNOMED CT, LOINC, and others that may have more restrictive licensing requirements. Please review the licensing terms for any terminologies used in your implementation.