Free Practice Questions for SCDM CCDM Exam

A completedata element definitionin clinical data management should include:

Nameandclear descriptionof the data element,

Data type(e.g., numeric, text, date),

Precisionor scale (if numeric), and

Unit or dimensionalityof measure (e.g., centimeters, inches).

In this example, while the data type (“measured physical quantity”) and precision (0.1) are defined, theunit of measurement(e.g., centimeters or inches) is missing. This omission leads to ambiguity and could cause serious discrepancies when comparing or analyzing measurements.

TheGCDMP (Chapter: Database Design and Build)emphasizes that units and dimensionality must be explicitly defined and consistently applied in all CRFs, metadata dictionaries, and data transformations.

Thus,option D (Unit or dimensionality of measure)is correct.

Reference (CCDM-Verified Sources):

SCDM GCDMP, Chapter: Database Design and Build, Section 5.2 – Metadata and Data Element Definitions

CDISC CDASH Implementation Guide, Section 3.3 – Data Element Metadata Requirements

ICH E6(R2) GCP, Section 5.5.3 – Data Accuracy and Standardized Definitions

The most effective method forquality control (QC)of the query resolution process is toperform random audits of resolved query forms. This ensures that queries are being appropriately raised, addressed, and resolved in accordance with the study protocol, data management plan (DMP), and standard operating procedures (SOPs).

According to theGCDMP (Chapter: Data Validation and Cleaning), QC activities should verify that the data review and query management process maintains high accuracy and consistency. Random auditing of resolved queries enables verification that:

Queries were raised for legitimate discrepancies,

The site’s responses were appropriate, and

The resolution actions taken by data management were correct and well-documented.

Metrics such as turnaround time (options A and C) or query counts (option B) measure efficiency butdo not assess quality. True quality control focuses on ensuring that data corrections preserve accuracy, auditability, and traceability — the fundamental principles ofdata integrityin clinical research.

Reference (CCDM-Verified Sources):

SCDM Good Clinical Data Management Practices (GCDMP), Chapter: Data Validation and Cleaning, Section 5.4 – Query Management and Quality Control

ICH E6 (R2) GCP, Section 5.5.3 – Data Integrity and Validation Procedures

TheScope of Work (SOW)is a contractual document that outlines thespecific deliverables, responsibilities, timelines, and budgetary detailsfor a given project between the sponsor and the contract research organization (CRO).

According to theGood Clinical Data Management Practices (GCDMP, Chapter: Project Management and Communication), the SOW defineswhat work will be performed,how many resources are allocated, andthe expected deliverables. This includes detailed information such as:

The number of database builds or migrations,

Timelines for deliverables (e.g., database lock),

Responsibility distribution between sponsor and CRO, and

Budget parameters for defined activities.

Therefore, if a Data Manager needs to determinehow many database migrations are budgeted for a project, theSOWis the correct document to reference.

Information such as PK sample scheduling (option A), site monitoring dates (option B), or staff contact details (option D) would be found in operational plans or contact lists, not in the SOW.

Reference (CCDM-Verified Sources):

SCDM Good Clinical Data Management Practices (GCDMP), Chapter: Project Management and Communication, Section 6.2 – Scope of Work Definition and Deliverables

ICH E6 (R2) GCP, Section 5.5.3 – Documentation and Responsibilities for Data Management Tasks

FDA Guidance for Industry: Oversight of Clinical Investigations – Sponsor and CRO Agreements

Astandardized data collection elementhas well-defined metadata, consistent naming conventions, and controlled terminology to ensure uniform data collection and interoperability across studies.

Key attributes, as perGCDMPandCDISC standards, include:

Aclear definitionof meaning (A)

Acontrolled set of response values(C)

Metadata specificationslike variable names, formats, and data types (D)

However, thephysical positioningof a data element on a case report form (B) is a matter ofform layout design, not a characteristic of data standardization. While consistent form structure aids usability, it is not part of data standardization or metadata management principles.

Hence,option Bis correct —form positioning is not a standardized data element attribute.

Reference (CCDM-Verified Sources):

SCDM GCDMP, Chapter: Standards and Data Integration, Section 4.1 – Data Element Standardization

CDISC CDASH Implementation Guide, Section 3.2 – Standardized Data Collection Elements and Metadata

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

To submit study data to theFDA in CDISC SDTM format, the sponsor mustmap and transformthe collected data from the study’s operational database (e.g., EDC) intoSDTM-compliant domains.

According toGCDMP (Chapter: Standards and Data Integration)andCDISC SDTM Implementation Guide, this process includes:

Mappingraw data elements from the clinical database to SDTM domains (e.g., DM, AE, VS).

Transformingdata to comply with SDTM structural and naming conventions.

Validatingthe output using CDISC compliance tools (e.g., Pinnacle 21).

Re-entering data (B) is unnecessary, and a letter of intent (C) is not required. SDTM is explicitly accepted by FDA for both retrospective and prospective submissions, so (D) is incorrect.

Thus,option Ais correct —map and transform existing data to SDTM formatfor regulatory submission.

Reference (CCDM-Verified Sources):

SCDM GCDMP, Chapter: Standards and Data Integration, Section 5.3 – Data Transformation and CDISC Mapping

CDISC SDTM Implementation Guide, Version 3.4 – Data Conversion and Submission Requirements

FDA Study Data Technical Conformance Guide, Section 2.2 – SDTM Mapping and Validation