SCDM CCDM Exam Dumps

When designing or configuring data entry screens within an Electronic Data Capture (EDC) system, three critical components are required for each field:

Data Type -- Defines the nature of the data (e.g., text, numeric, date).

Prompt -- The label or question displayed to the user.

Response Format -- Specifies how the user enters or selects data (e.g., free text, drop-down, checkbox).

According to the GCDMP (Chapter: EDC Systems and Database Design), these three attributes form the logical data structure required to build and validate data entry interfaces. They ensure consistency in how information is captured, displayed, and validated during data entry.

While user roles (A) and help text (D) are system-level configurations, not field-level specifications, page numbers (C) relate to printed CRFs rather than digital data screens.

Therefore, option B (Data type, prompt, and response format) correctly identifies the essential information needed to define data entry screens.

Reference (CCDM-Verified Sources):

SCDM GCDMP, Chapter: EDC Systems and Database Design, Section 4.3 -- Screen Design Specifications

CDISC CDASH Implementation Guide, Section 3.2 -- Data Field Attributes

ICH E6(R2) GCP, Section 5.5.3 -- Data Capture and Input Standards

During data reconciliation between a central laboratory and CRF data, the source of truth is typically the central lab database, as it provides directly measured, vendor-generated results.

When the central lab has data but the CRF does not (option C), the Data Manager must first query the central lab to confirm that the result was transmitted correctly, since discrepancies may stem from data processing or timing issues. Once confirmed, a secondary query may be issued to the site to ensure CRF completion and alignment.

Conversely, if the CRF contains data but the central lab is missing results (option B), the issue is site-level, not vendor-level.

According to the GCDMP (Chapter: External Data Transfers and Reconciliation), priority for querying depends on the authoritative source --- for lab data, the central lab is considered the source of record.

Therefore, option C is correct.

Reference (CCDM-Verified Sources):

SCDM GCDMP, Chapter: External Data Transfers and Reconciliation, Section 6.1 -- Reconciliation of Central Lab and CRF Data

ICH E6(R2) GCP, Section 5.5.3 -- Source Data Verification and Vendor Reconciliation

FDA Guidance for Industry: Computerized Systems Used in Clinical Investigations, Section 6.4 -- Data Reconciliation and Traceability

Let's calculate the workload:

200 patients 30 minutes = 6,000 minutes/week

6,000 minutes 60 = 100 hours/week

Over 6 months (~26 weeks): 100 26 = 2,600 hours total

Assuming a full-time Data Manager works approximately 160 hours/month, over 6 months (960 hours) per full-time equivalent (FTE):

2,600 960 2.7 FTEs total for the entire study period

To find the average per month, we divide evenly over 6 months:

2.7 6 0.45 FTE per month, or approximately 50% of a Data Manager per month.

Thus, the correct answer is B. Fifty percent of a Data Manager per month.

This estimate follows GCDMP best practices in resource planning, ensuring adequate data management capacity for ongoing external data handling activities.

Reference (CCDM-Verified Sources):

SCDM GCDMP, Chapter: Project Management, Section 5.3 -- Resource Estimation and Workload Planning

ICH E6(R2) GCP, Section 5.1.1 -- Quality Systems and Adequate Staffing

The section of the Clinical Study Report (CSR) that is most useful for a Data Manager is the one that includes the enumeration and explanation of data errors. This section provides a summary of the data quality control findings, including error rates, missing data summaries, and any issues identified during data review, validation, or database lock.

According to the GCDMP (Chapter: Data Quality Assurance and Control), post-study reviews of data errors and quality findings are essential for evaluating process performance, identifying recurring issues, and informing continuous improvement in future studies.

Other sections, such as clinical narratives (A) or statistical methods (C), are outside the core scope of data management responsibilities. The data error enumeration section directly reflects the quality and integrity of the data management process and is therefore the most relevant for review.

Reference (CCDM-Verified Sources):

SCDM GCDMP, Chapter: Data Quality Assurance and Control, Section 6.4 -- Quality Reporting and Error Analysis

ICH E3 -- Structure and Content of Clinical Study Reports, Section 14.3 -- Data Quality Evaluation

The most significant difference in the Data Manager's role when using an Electronic Data Capture (EDC) system is that data updates are implemented directly by site personnel (Option A).

According to the GCDMP (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 on system validation, query management, and data quality oversight rather 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 is Option 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