The BRIDG model makes a distinction between a study subject and an experimental unit. In most studies for which SDTM is implemented, these terms refer to the same person or animal, but there are studies where the study subject is different from the experimental unit. For those studies, it can be useful to understand these subtly different terms.
For an implementer trying to decide where data belong in SDTM-based datasets, it's pretty clear when data belongs in a trial design dataset, a relationship dataset, one of the new study reference datasets, or one of the special purpose domains. However, it can be difficult to choose the right general observation class dataset, especially if data are about findings.
The International System of Units (SI), commonly known as the metric system, is the international standard for measurement. According to the National Institute of Science and Technology (NIST), the SI rests on a foundation of seven defining constants: the cesium hyperfine splitting frequency, the speed of light in vacuum, the Planck constant, the elementary charge (i.e., the charge on a proton), the Boltzmann constant, the Avogadro constant, and the luminous efficacy of a specified monochromatic source.
In the diagrams below, the red line represents a graph of severity over time for a hypothetical event. For most adverse events, severity cannot be measured on a continuous scale; this line represents hypothetical actual severity, not data that could be recorded. The horizontal lines divide severity into the three categories, "Mild", "Moderate", and "Severe", which are used to describe adverse event severity.
In two previous papers, the PhUSE working group "Investigating the Use of FHIR in Clinical Research" demonstrated that data typically collected in diabetes studies can be extracted from medical records through FHIR (Fast Healthcare Interoperability Resources) and we can automate the process to populate eCRFs (electronic Case Report Forms). These data were then converted to SDTM (Study Data Tabulation Model) which would serve as the source for analysis datasets.
Use of Fast Healthcare Interoperability Resources (FHIR) in the Generation of Real World Evidence (RWE) demonstrated that electronic CRF data could be populated by mapping FHIR resources to CDASH/SDTM variables. To grow the use of FHIR for eSource beyond pilot projects, existing standards and workflows must be adapted to enable repeatable and scalable processes.
There is a lot of interest in the clinical trial community to understand what information can be obtained from Electronic Health Records (EHRs) to support clinical trials. The use of FHIR has been endorsed by the Office of National Coordinator for Health Information Technology (ONC) and is widely being used by EHR vendors.
"Sex" and "gender" are similar but different concepts whose definitions and meanings can be confusing (see, for example, the article Sex and gender: What is the difference? from Medical News Today).
When development of the SDTM and SDTMIG started, SAS was in almost universal use in the pharmaceutical industry and at FDA.
SNOMED (short for SNOMED Clinical Terms or SNOMED CT) is a set of medical terms used widely in clinical practice. Some have asked why CDISC develops its own Controlled Terminology, rather than using SNOMED. There are a number of reasons why we develop terminology:
The terms “domain” and “dataset” are commonly used in CDISC’s nomenclature and found frequently in the Study Data Tabulation Model (SDTM). For example, the SDTM v1.8 includes 134 instances of "domain" and says "A collection of observations on a particular topic is considered a domain." The model includes 78 instances of dataset and certain structures in the model are called "datasets" rather than "domains." Is there a difference between a domain and a dataset?