Using Health IT Data Standards to Boost Interoperability for Clinical Research 

Converting data between FHIR and CDISC health IT data standards boosts interoperability of EHR data for clinical research, a new guide says.

To leverage EHR data interoperability for clinical research purposes, health IT stakeholders should convert data between FHIR and CDISC data standards, according to an implementation guide from CDISC and HL7.

The FHIR to CDISC Joint Mapping Implementation Guide defines mappings between HL7’s FHIR standard for healthcare data exchange and three CDISC Standards: CDASH (data collection), SDTM (data tabulation) and LAB (lab data exchange).

The guide, available on CDISC and HL7’s websites, is set to help healthcare organizations boost data interoperability for clinical research purposes by streamlining the flow of EHR data to CDISC submission-ready datasets.

“This release is a significant milestone as CDISC and HL7 work together toward effectively linking healthcare and research while preserving the meaning and quality of the data,” Rhonda Facile, CDISC vice president of partnerships and development, said in a public statement.

“CDISC has held a long-term vision of more efficient use of real-world data from EHRs as source data for research and augmenting clinical trial data to accelerate clinical research processes for the benefit of us all,” Facile continued.

The implementation guide also supports the creation of case report forms that link to data elements defined using FHIR resources with embedded CDISC variables. This is set to cut the time it takes to collect data and reduce duplicate data-entry to improve data quality and decrease costs, representatives said.

“I am pleased to see HL7 and CDISC, two of the most important standards organizations for clinical research, partnering to make data transfer more efficient. The collaborative nature of these two organizations will help to make the Vulcan Accelerator successful in its mission,” said Rob Goodwin, co-chair of the Vulcan HL7 FHIR ACCELERATOR.

The implementation guide went through the HL7 Balloting process and the CDISC Standards Development Process to ensure coordination across healthcare and clinical research stakeholders.

“From the early days of FHIR, one of the things I’ve been most excited about is its ability to make data more easily available to the research space and to help close the loop in evaluating new therapies,” said Lloyd McKenzie, a senior consultant with Gevity and technical lead on the project.

“This implementation guide will help smooth the path to increased use of real-world data in research settings which will let us make better and faster decisions about what treatments are safe and effective,” McKenzie continued.

As the digital health transformation continues, stakeholders are looking to leverage EHR data to support clinical research efforts across the country.

In June, health IT vendors PRA Health Sciences, Inc. and Veradigm announced a partnership to create an EHR-based clinical research network that extends the clinical trial process into EHR workflows. 

The network aims to streamline the clinical trial recruitment process by integrating clinical research as a care option (CRAACO) into the EHRs of 40 million patients.

Representatives said the benefits of the network are twofold: patients will have greater access to CRAACO and researchers will see more diverse clinical trial participation.

“The current approach to clinical trials is disconnected from healthcare delivery and requires manual data collection, which creates barriers for physicians and patients to participate,” Stephanie Reisinger, vice president and general manager of Veradigm’s Life Sciences Research business, said in a press release at the time of the announcement.

“Today, less than one percent of the US population participates in clinical research, despite patients’ willingness to participate if asked,” Reisinger continued. “Under this agreement, the Veradigm and PRA-led network aims to transform the clinical research processes by extending EHR workflows to include clinical research as well as fully leveraging the rich data from digital healthcare delivery.”

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