Technology creates more opportunities for pharmaceutical advancement. The rise of data collection tools, from the humble iPad to advanced monitoring devices, has allowed researchers to improve their data quality and analysis. However, it also makes processes more complicated.
Increased digital data collection means increased data sharing. If one medical professional uses a different set of short-form notes or codes, the data won’t transfer or the information will be incorrect. This is driving researchers to call for standardization and to develop machine-readable systems. These systems represent the next wave in clinical trial development and data sharing.
How Does Machine-Readable Standardization Improve Trials?
As more organizations move toward standardization, they are reaping the benefits of improved clinical trials. These range from small changes in how teams record zip codes to mass standardization of symptoms and medical conditions.
Ben Moscovitch, former project director at The Pew Charitable Trusts, shared one 2019 study that highlighted the use of demographic data to improve patient matching rates. Standardizing basic information, such as how researchers record patient addresses and last names, can lead to a significant increase (8 percent) in match rates.
“These findings should inform federal government actions to improve interoperability, which is the ability of EHR systems to effectively exchange information,” writes Moscovitch.
Not only are researchers working to create sets of universal standards for clinical trial study schedules, but they are trying to ensure these standards are streamlined for an electronic world.
For example, Jozef Aerts, owner of XML4Pharma, published a paper highlighting one of the main challenges of data standardization. Namely, new standards need to be added to existing software tools, which is time-consuming and creates the potential for misinterpretation.
“Ideally, the standard should be in a machine-readable format and be read by a software that then generates implementation software for that standard automatically,” Aerts writes.
One of the best ways to understand how to create machine-readable standards is to review the organizations striving for this goal. There are three key groups working to standardize medical recording: Clinical Data Interchange Standards Consortium (CDISC), TransCelerate, and Fast Healthcare Interoperability Resources (FHIR).
CDISC 360 Project
One of the first groups working to implement clinical data standards is CDISC, a nonprofit organization with the goal of creating clarity. This group is eager to work with incompatible formats and diverse perspectives in an effort to learn how machine-readable data can be created and processed. They are constantly growing and looking for more researchers to partner with.
“You can’t really harmonize anything or combine data without standards,” says Allyson Gage, chief medical officer at Cohen Veterans Bioscience. “If we can get everybody to record data the same way, it will be much simpler and we can accelerate drug discovery.”
The CDISC 360 project activities first began in 2019 and the efforts continue today as more organizations present their challenges and needs.
The TransCelerate Digital Data Flow Initiative
TransCelerate is another nonprofit group that is focused on simplifying pharmaceutical research and development. The purpose of the Digital Data Flow initiative is to create fully automated processes that produce case report forms, procedure manuals, statistical analysis plans and other important assets.
The goal is to use open-sourced and vendor-agnostic systems, which means access won’t be limited by the different software solutions that researchers use. This is how you create full standardization: Everyone uses the same systems, regardless of technology access.
In the short term, the leaders of this project hope to reduce research bottlenecks and eliminate the need to reconcile data across all assets. In the long run, the use of standardized systems should improve trial design as a whole.
Healthcare standardization has been a significant issue for more than 20 years. The HL7 FHIR program is currently on its fourth release, but developers have been working on it for two decades. Fast Healthcare Interoperability Resources was developed because of electronic health records. As patient information increasingly became digital, so did the need to record notes across a unified standard. When a patient moves from one medical office to another, the new healthcare staff can easily access and understand that patient’s full medical history.
“The philosophy behind FHIR is to build a base set of resources that, either by themselves or when combined, satisfy the majority of common use cases,” the developers explain on the HL7 FHIR website. This means the system might not catch every problem, but the standards can be applied to the vast majority of patients.
These three organizations are all working to increase communication across the research and development field. With machine-readable standards, teams can share their data nationwide and across the world. Teams don’t have to worry about words or phrases getting lost in translation and researchers don’t have to change their record-keeping to accommodate different trials. As these groups move forward, recordkeeping should continue to be streamlined, standardized and digitized.