SCDM CCDM Exam With Confidence Using Practice Dumps

The most significant difference in theData Manager’s rolewhen using anElectronic Data Capture (EDC)system is thatdata updates are implemented directly by site personnel(Option A).

According to theGCDMP (Chapter: Electronic Data Capture Systems), EDC technology shifts responsibility for data entry and correction from the sponsor or CRO to the investigator site, enabling real-time data entry and validation. This eliminates the need for double entry or remote data transcription, allowing Data Managers to focus onsystem validation, query management, and data quality oversightrather than physical data handling.

However, the EDC system still requires full validation (contrary to Option B). Metrics generation (Option C) and CRF tracking (Option D) are important but not unique to EDC-based workflows.

Thus, the correct answer isOption A – Data updates are implemented by the sites, reflecting the most fundamental operational shift introduced by EDC systems.

Reference (CCDM-Verified Sources):

SCDM Good Clinical Data Management Practices (GCDMP), Chapter: Electronic Data Capture (EDC) Systems, Section 4.1 – Role of the Data Manager in EDC

ICH E6 (R2) GCP, Section 5.5.3 – Electronic Data Entry and Responsibilities

FDA 21 CFR Part 11 – Electronic Records and Signatures: Data Entry Responsibilities

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

When subjects are numberedsequentially within each site, it means that thesubject identification numbers (Subject IDs)restart from 001 at each site. For example, Site 101 may have Subject 001, and Site 102 may also have a Subject 001. In such cases, thesubject number alone is not globally uniqueacross the entire study. Therefore, when integrating or joining data across multiple database tables (for example, linking demographic, adverse event, and laboratory data), both thesite number and the subject numberare required to create a unique key that accurately identifies each record.

According to theGood Clinical Data Management Practices (GCDMP, Chapter on CRF Design and Data Collection), every data record in a clinical trial database must be uniquely and unambiguously identified. This is typically achieved through acomposite key, combining identifiers such assite number,subject number, and sometimesstudy number. The GCDMP specifies that a robust data structure must prevent duplication or mislinking of records across domains or tables.

Furthermore,FDA and CDISC standards (SDTM model)also emphasize the importance ofunique subject identifiers (USUBJID), which are derived from concatenating the study ID, site ID, and subject ID. This ensures traceability, integrity, and accuracy of subject-level data during database joins, data exports, and regulatory submissions.

Thus, in the described scenario, since subject numbering restarts at each site,both the site number and subject numberare required to uniquely identify and correctly join subject data across different datasets or tables.

Reference (CCDM-Verified Sources):

SCDM Good Clinical Data Management Practices (GCDMP), Chapter: CRF Design and Data Collection, Section 4.1 – Unique Subject Identification

CDISC SDTM Implementation Guide, Section 5.2 – Subject and Site Identification (Variable: USUBJID)

FDA Guidance for Industry: Computerized Systems Used in Clinical Investigations, Section 6 – Data Integrity and Record Identification