In a relational clinical database, themost efficient and normalized structurefor data collected repeatedly over time—such asvital signs—isone record per patient per visit.

Each patient will have multiple records, one for each visit when vital signs are assessed. This structure supports:

Time-based analysis (e.g., trends across visits),

Accurate data linkage with visit-level metadata, and

Efficient querying for longitudinal data.

According to theGCDMP (Chapter: Database Design and Build), the relational design principle dictates that data should be stored at thelowest unique level of observation. Since vital signs vary by both patient and visit, the combination ofpatient ID + visit IDforms a unique key for each record.

Option A (per visit) lacks patient identification, while options B and D aggregate data too broadly, losing temporal detail.

Thus,option C (One record per patient per visit)correctly represents the normalized design structure.

Reference (CCDM-Verified Sources):

SCDM GCDMP, Chapter: Database Design and Build, Section 4.2 – Normalization and Table Structure

CDISC SDTM Implementation Guide, Section 5.3 – Visit-Level and Observation-Level Data Structures

ICH E6(R2) GCP, Section 5.5.3 – Data Handling Principles