Global Core Electronic Medicinal Product Information (ePI), published by HL7 International - Biomedical Research & Regulation Work Group. This guide is not an authorized publication; it is the continuous build for version 1.1.0 built by the FHIR (HL7® FHIR® Standard) CI Build. This version is based on the current content of https://github.com/HL7/emedicinal-product-info/ and changes regularly. See the Directory of published versions
The "How to Build ePI Type 1 to 4" tab offers detailed guidance, examples, and best practices for creating ePI resources for each type. It covers:
Recommend first reading the ePI components page to understand what resources make up an ePI, and the use cases to select the appropriate use case and ePI type to suit your needs.
This tab is intended for:
To begin, explore the sub-sections linked below for each ePI type.
Type 1: Narrative Only
Reproduces the local health authority's DOCX or PDF-based template. Which includes all human-readable narrative (e.g., paragraphs, tables, bullets, images), section headings, sub-section headings, and document metadata (e.g., Document title, original date of approval, last date of modification, version, language).
Learn how to build ePI Type 1
Type 2: Narrative with Structured Product Data
Includes structured data about the product (e.g., medication name, ingredients, dosage forms, market authorization holder). This type supports partial machine processing while prioritizing the narrative.
Learn how to build ePI Type 2
Type 3: Narrative with Structured Clinical Data
Includes structured clinical data (e.g., indications, contraindications, warnings, undesireable effects). This type enables machine-readable clinical information for personalization, advanced search, and analytics.
Learn how to build ePI Type 3)
Type 4: Fully Structured
Supports full machine processing and prioritizes structure over narrative (e.g., structured dose instructions, structured adverse event tables). Still includes narrative but the narrative is now a child of a structured component. This type is optimized for machine-to-machine exchange and advanced personalization (e.g., autogenerate an ePI for a specific individual or patient profile grouping).
Learn how to build ePI Type 4)