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SCDM CCDM Exam Syllabus Topics:| Topic | Details | | Topic 1 | - Data Processing Tasks: This section measures skills of Clinical Systems Analysts and focuses on handling, transforming, integrating, reconciling, coding, querying, updating, and archiving study data while maintaining quality, consistency, and proper privileges over the data lifecycle.
| | Topic 2 | - Coordination and Project Management Tasks: This domain evaluates the skills of a Clinical Systems Analyst in coordinating data management workload, vendor selection, scheduling, cross-team communication, project timeline management, risk handling, metric tracking, and preparing for audits.
| | Topic 3 | - Testing Tasks: This section measures the skills of Data Managers and involves creating test plans, generating test data, executing validation and user acceptance testing, and documenting results to ensure systems and processes perform reliably and according to specifications.
| | Topic 4 | - Review Tasks: This section measures the skills of Data Managers and involves reviewing protocols, CRFs, data tables, listings, figures, and clinical study reports (CSRs) for consistency, accuracy, and alignment with data handling definitions and regulatory requirements.
| | Topic 5 | - Design Tasks: This section of the CCDM Exam measures skills of Data Managers and covers how to design and document data collection instruments, develop workflows and data flows, specify data elements, CRF forms, edit checks, reports, database structure, and define standards and procedures for traceability and auditability.
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SCDM Certified Clinical Data Manager Sample Questions (Q65-Q70):NEW QUESTION # 65
An asthma study is taking into account local air quality and receives that data from the national weather bureau. Which information is needed to link research subject data to the air-quality readings?
- A. Location, time and subject identifiers
- B. Location, time, subject and site identifiers
- C. Location and time identifiers
- D. Location identifier
Answer: C
Explanation:
When integrating external environmental data such as air quality readings with clinical study data, it is essential to use location and time identifiers to properly align the environmental data with subject-level data.
According to the Good Clinical Data Management Practices (GCDMP, Chapter: Data Management Planning and Study Start-up), external data sources (like national weather or pollution databases) must be merged using common linkage variables that allow synchronization without breaching subject confidentiality. In this case:
Location identifiers (e.g., city, postal code, or region) align the subject's study site or residential area with the environmental dataset.
Time identifiers (e.g., date and time of data collection) ensure that the environmental readings correspond to the same period as the subject's clinical observations.
Including subject identifiers (option C or D) is unnecessary and would pose privacy and data protection risks. Instead, linkage is typically done at the aggregate (site or regional) level, maintaining compliance with HIPAA and GDPR.
Reference (CCDM-Verified Sources):
SCDM Good Clinical Data Management Practices (GCDMP), Chapter: Data Integration and External Data Handling, Section 4.3 - Linking External Data Sources ICH E6 (R2) GCP, Section 5.5.3 - Data Traceability and External Data Management FDA Guidance for Industry: Use of Electronic Health Record Data in Clinical Investigations, Section 5.2 - Linking and Integration Principles
NEW QUESTION # 66
An international study collects lab values. Sites use different units in the source documents. Which of the following data collection strategies will have fewer transcription errors?
- A. Use a structured field and print standard units on the data collection form
- B. Allow values to be entered as they are in the source document and derive the units based on the magnitude of the value
- C. Allow values to be entered as they are in the source and the selection of units on the data collection form
- D. Have all sites convert the values to the same unit system on the data collection form
Answer: C
Explanation:
In international or multicenter clinical studies, laboratory data often originate from different laboratories that use varying measurement units (e.g., mg/dL vs. mmol/L). The Good Clinical Data Management Practices (GCDMP, Chapter on CRF Design and Data Collection) provides clear guidance on managing this variability to ensure data consistency, traceability, and minimized transcription errors.
The approach that results in fewer transcription errors is to allow sites to enter lab values exactly as recorded in the source document (original lab report) and to require explicit selection of the corresponding unit from a predefined list on the data collection form or within the electronic data capture (EDC) system. This method (Option B) preserves the original source data integrity while enabling centralized or automated unit conversion later during data cleaning or statistical processing.
Option B also supports compliance with ICH E6 (R2) Good Clinical Practice (GCP), which mandates that transcribed data must remain consistent with the source documents. Attempting to derive units automatically (Option A) can lead to logical errors, while forcing sites to manually convert units (Option D) introduces unnecessary complexity and increases the risk of miscalculation or inconsistent conversions. Printing only standard units on the CRF (Option C) ignores local lab practices and can lead to discrepancies between CRF entries and source records, triggering numerous data queries.
The GCDMP emphasizes that CRF design must account for local variations in measurement systems and ensure that unit selection is structured (dropdowns, controlled lists) rather than free-text to prevent typographical errors and facilitate standardization during data transformation.
Therefore, Option B-"Allow values to be entered as they are in the source and the selection of units on the data collection form"-is the most compliant, accurate, and efficient strategy for minimizing transcription errors in international lab data collection.
Reference (CCDM-Verified Sources):
Society for Clinical Data Management (SCDM), Good Clinical Data Management Practices (GCDMP), Chapter: CRF Design and Data Collection, Section 5.4 - Laboratory Data Management and Unit Handling ICH E6 (R2) Good Clinical Practice, Section 5.18 - Data Handling and Record Retention CDISC SDTM Implementation Guide, Section 6.3 - Handling of Laboratory Data and Standardized Units FDA Guidance for Industry: Computerized Systems Used in Clinical Investigations, Section 6 - Source Data and Accuracy of Data Entry
NEW QUESTION # 67
According to ICH E6, developing a Monitoring Plan is the responsibility of whom?
- A. Data Manager
- B. Monitor
- C. CRO
- D. Sponsor
Answer: D
Explanation:
According to ICH E6(R2) Good Clinical Practice (GCP), Section 5.18.1, the Sponsor is ultimately responsible for developing and implementing the Monitoring Plan.
The Monitoring Plan defines:
The extent and nature of monitoring (e.g., on-site, remote, risk-based).
The responsibilities of monitors.
The communication and escalation procedures for data quality and protocol compliance.
While the CRO (B) or Monitor (D) may perform monitoring activities under delegation, the Sponsor retains legal accountability for ensuring a compliant and effective plan is developed and maintained. The Data Manager (C) may contribute by outlining data review workflows, but is not responsible for authoring or owning the plan.
Therefore, option A (Sponsor) is the correct answer.
Reference (CCDM-Verified Sources):
ICH E6(R2) GCP, Section 5.18.1 - Purpose and Responsibilities for Monitoring SCDM GCDMP, Chapter: Regulatory Compliance and Oversight, Section 5.3 - Sponsor Responsibilities in Monitoring and Quality Assurance FDA Guidance for Industry: Oversight of Clinical Investigations - Sponsor Responsibilities (2013)
NEW QUESTION # 68
A study takes body-composition measurements at baseline using a DEXA scanner. Which information is needed to correctly associate the body-composition data to the rest of the study data?
- A. Subject number
- B. Study number and visit number
- C. Study number and subject number
- D. Subject number and visit number
Answer: D
Explanation:
To properly associate body-composition data (from a DEXA scanner) with other study data, both the subject number and the visit number are required.
According to the GCDMP (Chapter: Data Management Planning and Study Start-up), every clinical data record must be uniquely identifiable and linkable to a specific subject and study event. The subject number identifies the participant, while the visit number defines the temporal context in which the measurement was taken.
Without both identifiers, data integration becomes ambiguous-especially if multiple assessments occur over time (e.g., baseline, week 12, end of study). Including both ensures data traceability, integrity, and alignment with the protocol-defined schedule of events.
Study number (option A) alone does not distinguish between visits or subjects, and visit number alone (option C) lacks linkage to the individual participant.
Reference (CCDM-Verified Sources):
SCDM Good Clinical Data Management Practices (GCDMP), Chapter: Data Management Planning and Study Start-up, Section 4.4 - Data Linking and Identification Requirements ICH E6 (R2) GCP, Section 5.5.3 - Data Traceability Principles FDA Guidance for Industry: Computerized Systems Used in Clinical Investigations - Data Identification Requirements
NEW QUESTION # 69
A study numbers subjects sequentially within each site and does not reuse site numbers. Which information is required when joining data across tables?
- A. Subject number
- B. Study number and subject number
- C. Subject number and site number
- D. Site number
Answer: C
Explanation:
When subjects are numbered sequentially within each site, it means that the subject 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, the subject number alone is not globally unique across the entire study. Therefore, when integrating or joining data across multiple database tables (for example, linking demographic, adverse event, and laboratory data), both the site number and the subject number are required to create a unique key that accurately identifies each record.
According to the Good 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 a composite key, combining identifiers such as site number, subject number, and sometimes study 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 of unique 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 number are 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
NEW QUESTION # 70
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