Towards the Representation of Genomic Data in HL7 FHIR and OMOP CDM.

High throughput sequencing technologies have facilitated an outburst in biological knowledge over the past decades and thus enables improvements in personalized medicine. In order to support (international) medical research with the combination of genomic and clinical patient data, a standardization and harmonization of these data sources is highly desirable. To support this increasing importance of genomic data, we have created semantic mapping from raw genomic data to both FHIR (Fast Healthcare Interoperability Resources) and OMOP (Observational Medical Outcomes Partnership) CDM (Common Data Model) and analyzed the data coverage of both models.

Prototypical Clinical Trial Registry Based on Fast Healthcare Interoperability Resources (FHIR): Design and Implementation Study.

Background: Clinical trial registries increase transparency in medical research by making information and results of planned, ongoing, and completed studies publicly available. However, the registration of clinical trials remains a time-consuming manual task complicated by the fact that the same studies often need to be registered in different registries with different data entry requirements and interfaces.

Objective: This study investigates how Health Level 7 (HL7) Fast Healthcare Interoperability Resources (FHIR) may be used as a standardized format for exchanging and storing clinical trial records.

Design for a Modular Clinical Trial Recruitment Support System Based on FHIR and OMOP.

The MIRACUM consortium is developing a Clinical Trials Recruitment Support System to support the data-driven recruitment of patients for clinical trials. The design of the prototype includes both open source solutions (OMOP CDM, Atlas) and open standards for interoperability (FHIR). The aim of the prototype is to create a patient screening list of potential participants for a clinical study.

Extraction and Prevalence of Structured Data Elements in Free-Text Clinical Trial Eligibility Criteria.

Understanding the prevalence of structured data elements within clinical trial eligibility criteria is a crucial step for prioritizing integration efforts to supported automated patient recruitment into clinical trials based on electronic health record data. In this work, we extract data elements from 50 clinical trials using a collaborative, crowd-sourced, and iterative method. A total of 1.