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SCDM CCDM Prüfungsplan:

ThemaEinzelheiten
Thema 1
  • 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.
Thema 2
  • 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.
Thema 3
  • 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.
Thema 4
  • 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.
Thema 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 CCDM Prüfungsfragen mit Lösungen (Q45-Q50):

45. Frage
A Data Manager is importing lab data for a study. The lab data and the associated audit trail is kept at the central lab. What is necessary to maintain traceability of the transferred data at the Data Manager's location?

Antwort: D

Begründung:
Maintaining traceability of external data imports (such as laboratory results) is a fundamental principle of clinical data management. According to the GCDMP (Chapter: External Data Transfers and Integration), Data Managers must retain an unaltered copy of the raw data exactly as received from the vendor.
This archived version serves as a reference for:
Data provenance verification,
Audit trail review, and
Discrepancy resolution between vendor and study database.
Since the central lab maintains its own audit trail, the Data Manager's responsibility is to preserve the original data transmission file before applying transformations, merges, or validations.
Options A, C, and D describe procedural safeguards but do not meet the regulatory requirement of traceable data lineage. Only option B (Maintaining a copy of the data as received) ensures compliance with ICH E6(R2) and FDA 21 CFR Part 11 standards for data traceability and integrity.
Reference (CCDM-Verified Sources):
SCDM GCDMP, Chapter: External Data Transfers and Integration, Section 5.2 - Data Traceability and Version Control ICH E6(R2) GCP, Section 5.5.3 - Data Integrity and Source Data Verification FDA Guidance for Industry: Computerized Systems Used in Clinical Investigations, Section 6.4 - Source Data Traceability and Archiving


46. Frage
Which of the following SOPs are required for management of an EDC system?

Antwort: C

Begründung:
The most essential Standard Operating Procedure (SOP) for management of an Electronic Data Capture (EDC) system is Change Control.
Per GCDMP (Chapter: Computerized Systems and Compliance) and FDA 21 CFR Part 11, any changes made to an EDC system-whether to software configuration, study database design, or system functionality-must follow a documented, validated, and auditable change control process. This ensures that:
Modifications are properly authorized, tested, and approved before implementation.
System validation remains intact.
Data integrity, traceability, and regulatory compliance are maintained.
While vendor management (A) and coding maintenance (C) have supporting SOPs, change control (D) is mandatory for any system handling regulated clinical data. Measurement of data quality (B) is important but not specifically tied to system management procedures.
Thus, option D (Change control) is the correct answer.
Reference (CCDM-Verified Sources):
SCDM GCDMP, Chapter: Computerized Systems and Compliance, Section 5.3 - Change Control and System Maintenance FDA 21 CFR Part 11 - Electronic Records and Electronic Signatures, Section 11.10(a-k) ICH E6(R2) GCP, Section 5.5.3 - Computerized Systems Validation and Change Documentation


47. Frage
Which metric reveals the timeliness of the site-work dimension of site performance?

Antwort: A

Begründung:
The site-work dimension of site performance evaluates how efficiently sites manage and resolve data-related tasks - particularly query resolution, data entry, and correction timelines. Among the given metrics, the median and range of time from query generation to resolution (D) directly measures the site's responsiveness and data management efficiency.
According to the GCDMP (Chapter on Metrics and Performance Measurement), this indicator helps identify sites that delay query resolution, which can impact overall study timelines and data quality. Tracking this metric allows the data management team to proactively provide additional training or communication to underperforming sites.
Other options measure different aspects of project progress:
A reflects overall database closure speed.
B and C relate to study startup and enrollment readiness, not ongoing data work.
Thus, option D accurately represents a site performance timeliness metric, aligning with CCDM principles for operational performance measurement.
Reference (CCDM-Verified Sources):
SCDM Good Clinical Data Management Practices (GCDMP), Chapter: Metrics and Performance Management, Section 5.4 - Site Query Resolution Metrics ICH E6(R2) Good Clinical Practice, Section 5.18 - Monitoring and Site Performance Oversight


48. Frage
A protocol is updated mid-study to add an additional procedure about which data needs to be collected. Which of these statements applies?

Antwort: D

Begründung:
When a protocol is amended mid-study, resulting in additional data collection requirements, the Data Management Plan (DMP) must be updated accordingly and all relevant stakeholders must be notified.
According to the GCDMP (Chapter: Data Management Planning and Study Start-up), the DMP is a living document that defines all data management processes for a clinical study. It must accurately reflect the current data flow, CRF design, validation procedures, and reporting structure. Any protocol amendments affecting data capture, structure, or analysis require immediate DMP revision and distribution to ensure alignment across data management, clinical, and biostatistics teams.
Failure to update and communicate DMP changes can lead to misalignment in data handling and introduce compliance risks during audits or inspections. Therefore, Option B is correct: the DMP must be updated and the change communicated to all stakeholders (e.g., sponsor, CRO, clinical operations, biostatistics).
Reference (CCDM-Verified Sources):
SCDM Good Clinical Data Management Practices (GCDMP), Chapter: Data Management Plan (DMP), Section 5.3 - Maintaining and Updating the DMP ICH E6 (R2) Good Clinical Practice, Section 5.5.3 - Documentation of Protocol Changes and Data Handling Procedures FDA Guidance for Industry: Computerized Systems Used in Clinical Investigations - Section on Data Management Documentation


49. Frage
Which metric will identify edit checks that may not be working properly?

Antwort: D

Begründung:
The best metric to identify malfunctioning or ineffective edit checks is the count by edit check of the number of times the check fired. This allows data managers to assess whether specific edit checks are performing as intended.
According to the GCDMP, Chapter: Data Validation and Cleaning, edit checks are programmed logic conditions that identify data inconsistencies or potential errors during data entry. A properly functioning edit check should trigger only when data falls outside acceptable or logical limits. If an edit check fires too frequently or not at all, it may indicate a logic error in the check's programming or configuration.
By analyzing counts by individual edit checks, data managers can:
Identify checks that never trigger (potentially inactive or incorrectly written), Detect overactive checks (poorly designed parameters causing excessive false positives), and Optimize system performance and review efficiency.
This metric supports continuous improvement in data validation logic and contributes to cleaner, higher-quality clinical databases.
Reference (CCDM-Verified Sources):
SCDM Good Clinical Data Management Practices (GCDMP), Chapter: Data Validation and Cleaning, Section 6.2 - Edit Check Design and Performance Metrics FDA Guidance: Computerized Systems Used in Clinical Investigations - Section on Validation of Electronic Data Systems


50. Frage
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