Description:

Development of a real-time data translation layer that is able to convert in-house EHR data from FHIR-like information packets to OMOP-CDM format.

Background/History

Healthcare data can be sparse, heterogenous, making the integrated analysis difficult. There are growing efforts to harmonize the multimodal data to enable cross talk between various informatics systems in healthcare. 

The two of the main interoperable standards are Fast Healthcare Interoperability Resources (FHIR https://www.hl7.org/fhir) and Observational Medical Outcomes Partnership (OMOP https://ohdsi.org/omop/). They are developed for different real-world usage and needs. 

FHIR

FHIR is a health information exchange standard that defines a specification of API based exchange of health information content in a standard, simplified data model to facilitate information sharing between health information systems such as EHRs (electronic health record), PHRs (professional health record), payer systems, personal medical devices, etc. 

FHIR allows on-demand access to componentized patient health data along with cross references to other related information. FHIR systems typically support transaction-oriented tasks or processes. 

OMOP

OMOP provides similar capabilities for the sharing of health research data using a common data model (CDM) for relational databases. The OMOP CDM allows for the systematic analysis of disparate observational databases and supports analytical tasks or processes.

FHIR based systems usually provide capabilities on an individual basis (Patient) basis. OMOP works at a cohort level.

Data from systems like FHIR end up in OMOP databases through data pipelines. And OMOP allows for analyzing this data as a whole. FHIR systems can be viewed as transactional in nature (storing day to day data as it happens) and OMOP databases are more like data warehouses that aid in reporting and analyzing the data after the fact.

Purpose

The primary objective of this project is to model clinical data for the entire hospital record in FHIR to OMOP CDM standards and apply analytics on this standard data format to answer several questions relevant to research and patient care. 

Data is stored in different formats in FHIR and OMOP systems. There needs to be some kind of transformation. We need to convert data in one format to another.

Once the data is published to OMOP CDM, the focus will be to make use of a tool like Atlas (https://atlas-demo.ohdsi.org/) or custom R or Python applications to perform observational analyses to generate real world evidence from patient level observational data.

Benefits

A real-time data translation layer that is able to convert in-house EHR data from FHIR-like information packets to OMOP-CDM format. Once translated, we aim to have the enterprise EHR data at CAMH available, in both FHIR and OMOP formats. 

How

• Assess the cross talk of data between FHIR - OMOP vocabularies using available open-source libraries
• Deploy a translational API/Batch process in a sandbox that converts FHIR to OMOP CDM
• Test the API/Batch process on a real-world EHR data based in FHIR format and evaluate the data conversion quality
• Implement analytics over the OMOP data to test the pipelines validity

Further reading

FHIR: https://www.hl7.org/fhir

OMOP: https://ohdsi.org/omop/

Additional information

Resource Stack