Most real-world data (RWD) sets aren’t usable directly from the source. Adopting established standards to curate reliable, sharable insights is key for unleashing the potential of rich data assets.
Data standards are the unsung heroes of healthcare and the life sciences – serving as the foundation for a flexible, interoperable research environment.
These standards help us share ideas, information, and insights across disparate systems so that we are all speaking the same language. This is particularly important when considering RWD, which comes from a wide variety of sources and requires complex cleaning and transformation before it can be used in research and clinical care.
At COTA, we believe that playing an active part in the development and adoption of data standards is essential to maximize the utility of RWD. It is our ongoing mission to curate the most complete, accurate, and clinically relevant datasets available so we can unite the entire healthcare ecosystem, and we couldn’t do it without our partners in the data standards community.
Here are just a few examples of how we are advancing the maturity and uptake of standards to improve collaboration around RWD.
Representing clinical regimens with HemOnc.org
HemOnc.org is the largest freely available source of standardized, coded clinical interventions, regimens, and other important information for oncology and hematology.
We use HemOnc’s standardized codes to represent treatment regimens in our data, making it easier for providers to report accurately and consistently on their treatment choices. By standardizing the way we represent pharmaceutical agents and procedures, we can support the integration of real-world data into clinical decision support tools and other technologies.
Standardizing data formatting with the OMOP Common Data Model
The OMOP Common Data Model (CDM) allows us to take data from many different sources, such as EMRs and claims, and translate them into a common format for analytics. With a library of standard analytics routines to draw from, the open source CDM makes it easier to organize and manipulate RWD in a standardized manner.
COTA is working closely with OMOP to continually refine and develop the common data model. As one of their first external partners, we are thrilled about the opportunity to share our industry-leading experiences and shape a vital resource for the rest of the research community.
Normalizing clinical and claims data with Health Language
Wolter Kluwer’s Health Language is a staple of the analytics toolkit, allowing organizations to effectively leverage data to measure performance, stay interoperable, and achieve their goals. We use Health Language to standardize our ontologies and manage updates to ICD-10 codes so that we can remain agile and flexible when ingesting and analyzing new data.
COTA’s work with these standard frameworks and other shared methods for extracting, curating, and exchanging data, is foundational to our success with real-world data . We will continue to collaborate with data standards champions to promote the adoption and advancement of shared methods for life sciences research and patient care.
With common strategies for bringing data together, we can communicate more effectively, enhance the utility of RWD, and continue to drive innovation in oncology to improve the lives of patients and their families.