Introduction

This implementation guide describes the FHIR R4 artifacts for the (Dutch Breast Implant Registry) DBIR clinical registry.

Interoperability

In modern healthcare, interoperability is a cornerstone of effective data exchange. Clinical registries—repositories of structured data collected for specific patient populations, conditions, or procedures—play a vital role in improving patient outcomes, supporting research, and guiding policy. However, the variability in how these data points are structured and shared across systems poses a significant challenge to seamless integration and use. To address this, mapping clinical registry data to HL7's FHIR (Fast Healthcare Interoperability Resources) standards has emerged as a robust solution.

FHIR is a globally recognized standard for exchanging healthcare information electronically. It provides a framework that defines data formats and elements (known as "resources") and a web-based API for seamless interaction between systems.

Mapping clinical registry data points to FHIR ensures:

  • Standardization: Data is transformed into a universally understood format, improving consistency.
  • Interoperability: Facilitates seamless data exchange across diverse healthcare systems and applications.
  • Scalability: Supports integration with modern technologies like EHR systems, patient apps, and research tools.

How to Read This Guide

If you are not familiar with FHIR at all, please refer to the FHIR homepage to learn the basics.

This chapter provides an overview of the structure, purpose, and intended use of this FHIR Implementation Guide (IG). It helps readers navigate the guide efficiently and understand its components and conventions.

This implementation guide contains FHIR conformance resources that define the expected structure for DBIR data in FHIR. These conformance resources include:

Structure Definitions (also called "profiles"), specifying supported FHIR resources, mandatory fields, and required structures. Codesystems, enumerations of supported codes. Questionnaires, specific survey definitions (e.g., the EQ5D). Valuesets, predefined sets of allowed codes for particular responses. Using these conformance resources, data can be validated by a FHIR server or the official FHIR validation tool.

Example Data The examples folder contains samples of valid GLI FHIR resources. There are four files:

Each of these files is a FHIR bundle resource containing individual FHIR resources adhering to the GLI FHIR specifications.

How This Guide is Organized

This guide contains the following segments

FHIR Mapping

Provides a brief introduction of mapping clinical data points to FHIR.

Data Exchange:

Covers guidelines how to leverage the FHIR standards for data exchange. Data exchange in this IG refers to:

  • the extraction of clinical data from organizations using the DBIR registry
  • transformation of this source data to FHIR Resources, expressed in FHIR bundles
  • validation of the FHIR bundles based on predefined FHIR-profiles
  • persistance of the FHIR bundles into a Clinical Data Repository (CDR) provided by MRDM
  • internal processing of the FHIR bundles into a MRDM data pipeline, similar to a batch upload

FHIR Resources

The FHIR Resources contain FHIR conformance resources that define the expected structure for DBIR data in FHIR. These conformance resources include:

  • Structure Definitions (also called "Profiles"), specifying supported FHIR resources, mandatory fields, and required data structures.
  • Practical steps for aligning the data points from DBIR to FHIR resources.
  • For each FHIR Resource the resource mappings, constraints and examples of each FHIR Resource are included.

Using these conformance resources, data can be validated by a FHIR server or the official FHIR validation tool.