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The General Observation Classes - SDTMIG v3.4 - Wiki (cdisc.org)

Most subject-level observations collected during the study should be represented according to 1 of the 3 SDTM general observation classes: Interventions, Events, or Findings. The lists of variables allowed to be used in each of these can be found in the SDTM.

• The Interventions class captures investigational, therapeutic, and other treatments that are administered to the subject (with some actual or expected physiological effect) either as specified by the study protocol (e.g., exposure to study drug), coincident with the study assessment period (e.g., concomitant medications), or self‑administered by the subject (e.g., use of alcohol, tobacco, or caffeine).
• The Events class captures planned protocol milestones such as randomization and study completion, and occurrences, conditions, or incidents independent of planned study evaluations occurring during the trial (e.g., adverse events) or prior to the trial (e.g., medical history).
• The Findings class captures the observations resulting from planned evaluations to address specific tests or questions (e.g., laboratory tests, ECG testing, questions listed on questionnaires).

In most cases, the choice of observation class appropriate to a specific collection of data can be easily determined according to these descriptions. The majority of data, which typically consists of measurements or responses to questions, usually at specific visits or time points, will fit the Findings general observation class. Additional guidance on choosing the appropriate general observation class is provided in Section 8.6.1, Guidelines for Determining the General Observation Class.

General assumptions for use with all domain models and custom domains based on the general observation classes are described in Section 4, Assumptions for Domain Models; specific assumptions for individual domains are included with the domain models.

Datasets Other than General Observation Class Domains - SDTMIG v3.4 - Wiki (cdisc.org)

The SDTM includes 4 types of datasets other than those based on the general observation classes:

• Domain datasets with subject-level data that do not conform to 1 of the 3 general observation classes. These include Demographics (DM), Comments (CO), Subject Elements (SE), and Subject Visits (SV), and are described in Section 5, Models for Special-purpose Domains.
• Trial Design Model (TDM) datasets, which represent information about the study design but do not contain subject data. These include datasets such as Trial Arms (TA) and Trial Elements (TE) and are described in Section 7, Trial Design Model Datasets.
• Relationship datasets, such as the RELREC and SUPP-- datasets. These are described in Section 8, Representing Relationships and Data.
• Study Reference datasets include Device Identifiers (DI) and Non-host Organism Identifiers (OI). These provide structures for representing study-specific terminology used in subject data. These are described in Section 9, Study References.

Datasets and Domains - SENDIG v3.1.1 - Wiki (cdisc.org) 

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