CCDM Exam Questions and Answers | Exam-Dumps (Page: 3)

QUESTION: 17

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

Count by edit check of the number of times the check fired
Count by site of the number of times any edit check fired
Average number of edit check identified discrepancies per form
Average number of times each edit check has fired

Answer(s): A

Explanation:

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

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QUESTION: 18

What should be done if the site continues to provide inconsistent data after several re-queries?

Continue to re-query until the site changes the data
Gently lead the site to the correct response
Escalate the issue to the appropriate site contact personnel
Do nothing, the data will remain inconsistent

Answer(s): C

Explanation:

If a clinical site continues to provide inconsistent or illogical data after multiple queries, the correct course of action is to escalate the issue to the appropriate site contact personnel, typically the Clinical Research Associate (CRA) or Site Monitor.
According to the Good Clinical Data Management Practices (GCDMP), persistent data discrepancies often indicate a misunderstanding of the protocol, CRF instructions, or data entry procedures at the site level. Repeatedly re-querying the same data without escalation wastes time and risks introducing bias or error. By escalating through formal communication channels, the issue can be clarified through re-training, documentation review, or site monitoring visits. The GCDMP emphasizes that escalation ensures data accuracy, site accountability, and protocol adherence, maintaining both data quality and regulatory compliance. Data managers must document the escalation process in the Data Management Plan (DMP) and ensure proper follow-up resolution is achieved.

Reference:

(CCDM-Verified Sources)
SCDM Good Clinical Data Management Practices (GCDMP), Chapter: Communication and Issue Escalation, Section 4.2 Handling Persistent Data Discrepancies ICH E6 (R2) Good Clinical Practice, Section 5.18 Monitoring and Site Communication FDA Guidance for Industry: Oversight of Clinical Investigations Risk-Based Monitoring, Section on Issue Escalation

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QUESTION: 19

Which competency is necessary for EDC system use in a study using the medical record as the source?

Screening study subjects
Using ePRO devices
Resolving discrepant data
Training on how to log into Medical Records system

Answer(s): D

Explanation:

In studies where the medical record serves as the source document, the Electronic Data Capture (EDC) system users (typically study coordinators or site personnel) must have appropriate training on how to access and log into the medical record system. This competency ensures that data abstracted from the electronic medical record (EMR) are complete, accurate, and verifiable in compliance with Good Clinical Practice (GCP) and Good Clinical Data Management Practices (GCDMP).

According to the GCDMP (Chapter: EDC Systems and Data Capture) and ICH E6(R2), all personnel involved in data entry and verification must be trained in both the EDC and the primary source systems (e.g., EMR). This ensures that the integrity of data flow--from source to EDC--is maintained, and that personnel understand system access controls, audit trails, and proper documentation of source verification.
While resolving discrepant data (C) and screening subjects (A) are part of study operations, the competency directly related to EDC system use in EMR-based studies is the ability to properly log into and navigate the medical records system to extract source data.

Reference:

(CCDM-Verified Sources)
SCDM GCDMP, Chapter: Electronic Data Capture (EDC), Section 5.1 Source Data and System Access Requirements
ICH E6(R2) Good Clinical Practice, Section 4.9 Source Documents and Data Handling FDA Guidance: Use of Electronic Health Record Data in Clinical Investigations, Section 3 Investigator Responsibilities

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QUESTION: 20

A Data Manager is importing data from an external facility.
Which is commonly checked first?

Incoming files have the expected number of records
Incoming files are conformant to the data transfer specifications
Data in incoming files are consistent with existing data in the study database
Data in the incoming files are internally consistent

Answer(s): B

Explanation:

When importing external data (e.g., laboratory or imaging results) into a clinical database, the first step in data import quality control is to verify that incoming files conform to the pre-specified data transfer specifications (DTS).
According to the GCDMP (Chapter: External Data Transfers and Integration), the Data Transfer Specification defines file structure, variable names, data types, delimiters, record counts, and validation rules. The initial import check confirms that the received file matches the technical and structural requirements before content or record consistency is evaluated. Subsequent checks--such as record counts (A), data consistency with existing database (C), and internal logical consistency (D)--are performed only after the file structure is validated and confirmed to match the specifications. Failure to perform this first check may cause import errors or corrupted data loads.
Thus, the first and most critical verification step is ensuring file conformity to the agreed data transfer specifications, making option B correct.

Reference:

(CCDM-Verified Sources)
SCDM GCDMP, Chapter: External Data Transfers, Section 4.2 Data Transfer File Validation and Import Checks
ICH E6(R2) GCP, Section 5.5.3 Validation of Computerized Systems and Data Imports

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QUESTION: 21

Which list should be provided to support communication with sites regarding late data and queries?

List of entered and clean data by site
List of subjects screened and enrolled by site
List of user account activity by site
List of outstanding data and queries by site

Answer(s): D

Explanation:

Effective site communication in data management relies on transparent reporting of pending issues such as open queries, missing data, and overdue updates. According to the Good Clinical Data Management Practices (GCDMP, Chapter: Communication and Metrics), the list of outstanding data and queries by site provides a direct, actionable overview of what each site needs to address, supporting accountability and timely resolution.
This list typically includes subject identifiers, query types, dates generated, and status of resolution, allowing data managers to prioritize site follow-ups. Regular distribution of this report fosters efficient collaboration between the data management team, monitors, and site staff, ultimately improving database cleanliness and timeline adherence.
Options A and B reflect general study status but do not target data issue resolution. Option C pertains to user access oversight, not data progress. Hence, option D is the correct and most operationally relevant answer.

Reference:

(CCDM-Verified Sources)
SCDM GCDMP, Chapter: Communication and Metrics, Section 5.2 Site Reporting and Query Management Metrics
ICH E6(R2) GCP, Section 5.18 Site Oversight and Communication Requirements

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QUESTION: 22

In development of CRF Completion Guidelines (CCGs), which is a minimum requirement?

CCGs are designed from the perspective of the Study Biostatistician to ensure that the data collected can be analyzed
CCGs must be signed before database closure to include all possible protocol changes affecting CRF completion
CCGs must include a version control on the updated document
CCGs are developed with representatives of Data Management, Biostatistics, and Marketing departments

Answer(s): C

Explanation:

Case Report Form Completion Guidelines (CCGs) are essential study documents that instruct site staff on how to complete each field of the CRF correctly. A minimum requirement for CCGs, according to Good Clinical Data Management Practices (GCDMP, Chapter: CRF Design and Data Collection), is that they must include version control.
Version control ensures that all updates or revisions to the CCG--arising from protocol amendments or clarification of data entry rules--are documented, dated, and traceable. This guarantees that site personnel are always using the most current version and supports audit readiness. Option A describes an important design consideration but not a minimum compliance requirement. Option B is inaccurate, as CCGs must be approved and implemented before data collection begins, not after. Option D includes an irrelevant stakeholder (Marketing). Therefore, option C--"CCGs must include a version control on the updated document"--is correct and compliant with CCDM and GCP standards.

Reference:

(CCDM-Verified Sources)
SCDM GCDMP, Chapter: CRF Design and Data Collection, Section 4.3 Development and Maintenance of CRF Completion Guidelines
ICH E6(R2) GCP, Section 8.2.1 Essential Documents and Version Control Requirements

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QUESTION: 23

In an EDC study, an example of an edit check that would be inefficient to run at data entry is a check:

Against a valid list of values.
Across visits for consistency.
Against a valid numeric range.
On the format of a date.

Answer(s): B

Explanation:

In Electronic Data Capture (EDC) systems, edit checks are categorized based on when and how they are executed -- typically immediate (at data entry) or batch (post-entry). Checks that require data from multiple visits or forms are generally inefficient to run at data entry because they depend on information that may not yet exist in the system.
According to the Good Clinical Data Management Practices (GCDMP, Chapter: Data Validation and Cleaning), cross-visit consistency checks -- such as comparing baseline and follow-up blood pressure or verifying date order between screening and dosing -- should be executed as batch or scheduled validations, not at the point of data entry. Running these complex checks in real time can slow system performance, increase query load unnecessarily, and confuse site users if related data are not yet entered.
Conversely, edit checks against valid ranges, formats, or predefined value lists (options A, C, and D) are simple, local validations ideally performed immediately at data entry to prevent basic errors. Therefore, cross-visit consistency checks (Option B) are best executed later, making them inefficient for real-time data entry validation.

Reference:

(CCDM-Verified Sources)
SCDM Good Clinical Data Management Practices (GCDMP), Chapter: Data Validation and Cleaning, Section 6.4 Real-Time vs. Batch Edit Checks
FDA Guidance for Industry: Computerized Systems Used in Clinical Investigations Section on Edit Checks and Data Validation Logic
CDISC SDTM Implementation Guide Section on Temporal Data Consistency Validation

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QUESTION: 24

What action should a data manager take if an investigator retires in the middle of an EDC trial and the replacement does not agree to use EDC for the remainder of the trial?

Notify the project manager and request that the site be closed.
Explore other options for the site with the study team.
Talk with the clinical research associate to identify alternative sites.
Discuss the use of the site's data with the project statistician.

Answer(s): B

Explanation:

When an investigator retires mid-study and the replacement refuses to use the Electronic Data Capture (EDC) system, the data manager must not take unilateral action but rather collaborate with the study team to explore acceptable solutions.
Per the GCDMP (Chapter: Project Management in Data Management), any deviation from the established data capture method -- particularly a change that affects regulatory compliance, data consistency, or site operations -- requires a cross-functional assessment. The study team, which includes clinical operations, project management, regulatory affairs, and data management, should evaluate feasible alternatives such as:
Allowing paper CRF entry followed by centralized data transcription, Retraining site staff on EDC use, or
Temporarily suspending data entry until compliance can be restored. Immediate site closure (option A) or unilateral decisions by data management (options C and D) violate escalation and communication protocols. Collaborative decision-making ensures continuity,

compliance, and data integrity, in line with ICH E6 (R2) GCP and FDA 21 CFR Part 11.

Reference:

(CCDM-Verified Sources)
SCDM Good Clinical Data Management Practices (GCDMP), Chapter: Project Management and Communication, Section 5.2 Handling Site and Investigator Changes ICH E6 (R2) Good Clinical Practice, Section 4.1 Investigator Responsibilities FDA Guidance for Industry: Computerized Systems Used in Clinical Investigations Section on EDC Operations and Site Management

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SCDM CCDM Exam (page: 3) SCDM Certified Clinical Data Manager Updated on: 07-Feb-2026

QUESTION: 17

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QUESTION: 24

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SCDM CCDM Exam (page: 3)
SCDM Certified Clinical Data Manager
Updated on: 07-Feb-2026