How is collaborative effort between the regulatory bodies helping in developing standards?

Regulatory bodies in various countries have started realizing the need for and importance of RWD and have started developing the required standards. Discussions on developing standards for RWD have actively been going on between healthcare institutes, companies and researchers. Organizations like CDISC, FDA, HL7 are making major contributions to the setting up of standards.

How CDISC is developing standards for Real-World Data?

CDISC has high expertise in developing standards for clinical trials for structured data collection and analysis. Similarly, they are trying to generate standards for RWD.

• CDISC is actively participating in the pilot projects for developing and validating the standards in real-world settings.
• CDISC RWD Connect Initiative is an initiative taken by CDISC which aims in developing vision and strategy to use of CDISC standards for RWD and in identifying the potential challenges associated.
• The version 1.0 of ‘Considerations for SDTM Implementation in Observational Studies and Real-World Data’ document addresses the most encountered issues while using the SDTM for observational studies and RWD, also to offer the guidance and implementation strategies for addressing the same.
• Currently, CDISC is actively working on making their existing standards more feasible for handling Real-World Data.

Initiatives taken by FDA for Real-World Data Standards:

A single standard is not yet developed by the FDA for handling Real-World Data. But they have developed guidelines on how to submit RWD for regulatory purposes. Their guidance documents outline the process to transform RWD into the format which is compatible with existing FDA-supported data standards.

• ‘Data Standards for Drug and Biological Product Submissions Containing Real-World Data’ is the document which contains the outline on how to transform the RWD to a format that complies with the existing FDA standards.
• ‘Real-World Data: Assessing Electronic Health Records and Medical Claims Data to Support Regulatory Decision-Making for Drug and Biological Products’ is a guidance issue by FDA which is about the considerations for using RWD from claims and EHRs. This guide refers to how the relevant sources have to be selected and how the reliability of the data has to be maintained from collection to curation.
• ‘Real-World Data: Assessing Electronic Health Records and Medical Claims Data to Support Regulatory Decision-Making for Drug and Biological Products’ is a guidance issue by FDA which is about the considerations for using RWD from claims and EHRs. This guide refers to how the relevant sources have to be selected and how the reliability of the data has to be maintained from collection to curation.

The role of HL-7 in developing RWD Standards:

• HL-7 FHIR (Fast Healthcare Interoperability Resources) defines a standardized framework for the exchange of healthcare information.
• The Vulcan Real-World Data (RWD) Implementation Guide, an ongoing project by HL7 International's Biomedical Research & Regulation Work Group ensures the reliability and consistency of RWD data collection and representation across various EHR systems.

Object Management Group (OMG) and Observational Health Data Sciences and Informatics (OHDSI) Consortium for developing RWD Standards:

• Object Management Group can develop standards by modifying the existing data modeling standards, like UML (Unified Modeling Language), which could be adapted for RWD specifically. The Observational Health Data Sciences and Informatics (OHDSI) Consortium plays a key role in the development of RWD standards.
• To capture and analyze the clinical concepts within RWD, OHDSI develops standardized vocabularies and coding systems. This ensures consistency across different datasets and reduces the risk of misinterpreting data.
• OMOP CDM (Observational Medical Outcomes Partnership Common Data Model) is a standardized data model for mapping data from different sources into a common format which eases the analysis.
• OHDSI will also provide open-source analytic tools in coordination with OMOP CDM, which allows researchers to conduct studies on RWD in a standardized way.

What are the challenges associated with the development of RWD Standards?

Development of RWD standards can be very challenging. RWD is continuously evolving and is complex in nature. Therefore, the standards have to be flexible to adapt these. Since, it comes from various sources, it becomes difficult to develop a single standard due to the diverse nature. Patient data is confidential, which demands the need of standards which ensure privacy and security. All these are the challenges that have to be addressed while developing the standards.

Future of RWD Standards:

For developing adaptable standards, automation of data harmonization and advanced analytics, AI and ML are going to be the key players in the future. Advanced analytics methodologies will help in uncovering hidden patterns in the data. Regulatory bodies are going to adapt RWD Standards for drug approval. By addressing the existing challenges, RWD holds a promise of transforming the healthcare industry.