CCDM Exam Dumps - SCDM Clinical Data Management Questions and Answers

UnderFDA 21 CFR Part 11, organizations using electronic systems must ensure thatall system users are trainedto perform their assigned functions before gaining access to the system. The regulation requires documented evidence of training but does not specify how it should be conducted (e.g., exam-based, in person, or language-specific).

TheGCDMP (Chapter: Computerized Systems and Compliance)further clarifies that personnel training should include instruction onsystem functionality, audit trails, data entry procedures, and electronic signaturesto maintain compliance and data integrity. Training must beperformed and documentedbut does not require a specific format or delivery method.

Therefore,option A—Training must be performed—is correct, as it reflects theminimum regulatory expectationper FDA and SCDM standards.

Reference (CCDM-Verified Sources):

FDA 21 CFR Part 11, Section 11.10(i) – Personnel Training Requirements

SCDM GCDMP, Chapter: Computerized Systems and Compliance, Section 5.4 – System Training and Documentation

ICH E6(R2) GCP, Section 2.8 – Qualified Personnel and Training Requirements

TheInvestigatorholds theprimary responsibilityfor ensuring the accuracy, completeness, and timeliness of Case Report Form (CRF) entries. This responsibility is mandated by regulatory requirements underICH E6(R2) Good Clinical Practice (GCP).

The investigator may delegate CRF completion to aqualified designee (e.g., site coordinator), but the ultimate accountability remains with the investigator. The investigator’s signature (electronic or manual) on the CRF serves as certification that the data accurately reflect the source documents and the patient’s participation.

TheGCDMP (Chapter: CRF Design and Data Collection)reinforces this by stating that while data managers ensure design quality and CRAs verify consistency with source data,the investigator is legally responsible for CRF accuracy.

Thus,option D (Investigator)is correct, as it aligns with both GCP and CCDM standards.

Reference (CCDM-Verified Sources):

ICH E6(R2) GCP, Section 4.9 – Records and Reports (Investigator Responsibilities)

SCDM GCDMP, Chapter: CRF Design and Data Collection, Section 5.1 – Investigator’s Role in Data Accuracy

FDA 21 CFR Part 312.62 – Investigator Recordkeeping and Record Retention

Themost common mode of data entryinElectronic Data Capture (EDC)systems issingle data entry.

According to theGCDMP (Chapter: Electronic Data Capture Systems), EDC systems have built-inedit checks, validation rules, and audit trailsthat ensure data accuracy and integrity at the point of entry. These real-time validation capabilities makedouble data entry(a legacy practice from paper studies) unnecessary.

EDC systems automatically verify data as they are entered by site staff, generating queries for inconsistencies or out-of-range values immediately.Blind verification (option B)andthird-party comparisons (option D)are not standard data entry modes but may be used for specialized reconciliation or external data imports.

Thus,single data entry (Option C)is the industry standard approach, ensuring both efficiency and compliance withFDA 21 CFR Part 11andICH E6 (R2)data integrity requirements.

Reference (CCDM-Verified Sources):

SCDM Good Clinical Data Management Practices (GCDMP), Chapter: Electronic Data Capture (EDC) Systems, Section 5.4 – Data Entry and Verification Processes

ICH E6 (R2) Good Clinical Practice, Section 5.5.3 – Computerized Systems and Data Validation

FDA 21 CFR Part 11 – Electronic Records and Electronic Signatures: Validation and Data Entry Requirements

The primary purpose of maintaining anaudit trailas required under21 CFR Part 11isto preserve data integrity. According to the U.S. FDA’s regulation on electronic records and signatures, every change to electronic data must be traceable, including information about who made the change, when it was made, and what the change entailed.

TheGood Clinical Data Management Practices (GCDMP)outlines that an audit trail provides a permanent, chronological record of all modifications to clinical data. This ensures transparency and allows the reconstruction of the course of data entry and modification. The regulation aims to prevent unauthorized or undocumented data manipulation, thereby maintainingthe accuracy, reliability, and validityof electronic records.

TheFDA 21 CFR Part 11, Section 11.10(e)explicitly mandates that systems must usesecure, computer-generated, time-stamped audit trailsto independently record the date and time of operator entries and actions that create, modify, or delete electronic records. This ensures the data remains trustworthy and defensible in regulatory reviews or inspections.

Therefore, the main reason for requiring an audit trail isto preserve data integrity— ensuring that all data captured, modified, or transmitted is authentic, accurate, and complete throughout the study lifecycle.

Reference (CCDM-Verified Sources):

SCDM Good Clinical Data Management Practices (GCDMP), Chapter: Regulatory Compliance and Data Integrity

FDA 21 CFR Part 11 – Electronic Records; Electronic Signatures, Section 11.10(e)

ICH E6 (R2) Good Clinical Practice, Section 5.5.3 – Data Integrity and System Validation

When combining data from two datasets where one uses numeric codes (1 = Male, 2 = Female) and another uses text codes (M, F), each unique value in one dataset corresponds exactly to one unique value in the other.

This relationship is aone-to-one mapping, where each element in one dataset maps directly to a single corresponding element in the other.

1 → M

2 → F

Such mappings ensure consistent data harmonization duringdata integration and standardizationphases, as outlined in theGCDMP (Chapter: Database Design and Integration).

Many-to-one (C)mapping would occur if multiple values (e.g., “Male,” “M,” “Man”) mapped to a single standardized value, which isn’t the case here.

Thus, the mapping isone-to-one, ensuring precise correspondence between both representations of gender data.

Reference (CCDM-Verified Sources):

SCDM GCDMP, Chapter: Database Design and Build, Section 5.4 – Data Mapping and Harmonization

CDISC SDTM Implementation Guide, Section 5.2 – Controlled Terminology and Mapping Rules

ICH E6(R2) GCP, Section 5.5.3 – Data Integrity and Integration Principles

Blood pressure is aquantitative physiological measurement, typically consisting oftwo continuous numeric values: systolic and diastolic pressure. Therefore, the most appropriate and scientifically valid method of data collection is to usetwo continuous variables(e.g., systolic = 120 mmHg, diastolic = 80 mmHg).

According to theGCDMP (Chapter: CRF Design and Data Collection), data fields must be designed to capture the mostprecise, accurate, and analyzableform of clinical data. Numeric data should be collected using numeric data types to allow for range checks, calculations (e.g., mean arterial pressure), and statistical analysis.

Options such as categorical representations (radio buttons or check boxes) introduce rounding, data loss, and analytic limitations. Coding a verbatim diagnosis (option A) is inappropriate for numeric vital sign data and violates the principle of capturing data at the most granular level.

Thus, the correct and validated method per CCDM standards istwo continuous variables, ensuring accuracy, traceability, and analytical flexibility.

Reference (CCDM-Verified Sources):

SCDM Good Clinical Data Management Practices (GCDMP), Chapter: CRF Design and Data Collection, Section 4.2 – Best Practices for Quantitative Data Capture

ICH E6 (R2) Good Clinical Practice, Section 5.5.3 – Data Accuracy and Collection Standards

FDA Guidance for Industry: Electronic Source Data in Clinical Investigations, Section 4.3 – Data Format and Structure Requirements

In Structured Query Language (SQL), theWHEREclause is used to filter records based on specified criteria. The query retrievesall columnsfrom thepatienttable (SELECT *) but onlythose rowswhere themedical_record_numbervalue is greater than 9000.

This means:

Thenumber of columns (fields)remains the same as the original table.

Thenumber of rows (records)will beequal to or less thanthe number of rows in thepatienttable, depending on how many patients meet the filter condition.

Hence, the result set can only beshorter or equal in lengthcompared to the original table. It cannot be longer, wider, or narrower, since no new rows or columns are created.

Therefore,option B—“Shorter or of equal length than the patient table”— is correct.

Reference (CCDM-Verified Sources):

SCDM GCDMP, Chapter: Database Design and Build, Section 5.2 – Relational Database Queries and Filtering Logic

ICH E6(R2) GCP, Section 5.5.3 – Data Retrieval, Filtering, and Storage Principles

FDA Guidance for Industry: Computerized Systems Used in Clinical Investigations, Section 6.4 – Query Logic and Record Subsetting

Before selecting anElectronic Data Capture (EDC)system for a clinical trial, it is essential to have a clear understanding of thefunctional requirements. This serves as theminimum prerequisiteto guide system selection, ensuring that the EDC solution aligns with the protocol needs, data workflow, security requirements, and regulatory compliance.

According to theGood Clinical Data Management Practices (GCDMP, Chapter: Computerized Systems and Compliance), functional requirements describe what the system must do—such as data entry capabilities, edit checks, query management, user roles, audit trails, and integration with external systems (e.g., labs, ePRO). This understanding allows sponsors and CROs to evaluate vendor systems effectively during the selection and qualification phase.

Other options:

B. Installation qualificationandD. Validation planoccuraftersystem selection.

C. Governance documentationsupports operations but is not required before choosing the system.

Hence,option Ais correct — the first and most essential prerequisite before EDC selection is a solid understanding of thefunctional requirements.

Reference (CCDM-Verified Sources):

SCDM GCDMP, Chapter: Computerized Systems and Compliance, Section 4.2 – Requirements Gathering and System Selection

FDA 21 CFR Part 11 – System Validation and Intended Use Requirements

ICH E6(R2) GCP, Section 5.5.3 – Computerized System Selection and Qualification

TheCase Report Form (CRF) Completion Guidelines (CCGs)are critical documents that guide site staff onhow to accurately and consistently record dataon CRFs across all participating sites, especially in multinational trials.

According to theGood Clinical Data Management Practices (GCDMP, Chapter: CRF Design and Data Collection), one of the key components of the CCGs is alist of acceptable abbreviationsand conventions to be used during CRF entry. This standardization ensures data consistency across languages and countries, reduces ambiguity during data review, and facilitates database design and coding accuracy.

Whiletranslation (A)may be useful for training materials, it is not required for CCGs unless specified by regulatory bodies. OptionsCandDare incorrect because data collection should adhere to standardized terms in English (or the study’s official language) — allowing free use of local languages or arbitrary abbreviations introduces inconsistencies.

Hence,option B—“CCGs must contain the list of acceptable abbreviations to be used in the CRF”— is correct.

Reference (CCDM-Verified Sources):

SCDM GCDMP, Chapter: CRF Design and Data Collection, Section 5.3 – CRF Completion Guidelines and Standardization

ICH E6(R2) GCP, Section 5.5.3 – Consistency and Data Recording Requirements

FDA Guidance for Industry: Computerized Systems Used in Clinical Investigations, Section 6.2 – Data Entry Conventions and Documentation

To improve efficiency and ensure consistency across multiple studies, the most effective infrastructure solution is tomaintain a centralized library of standardized forms or screen modules(e.g., CRF/eCRF templates).

According to theGood Clinical Data Management Practices (GCDMP, Chapter: Database Design and Build), using aform libraryallows reuse of validated data collection modules for commonly collected domains such as demographics, adverse events, and vital signs. This reduces database setup time, enhances uniformity in data definitions, and ensures alignment with standards such asCDISC CDASH and SDTM.

While adoptingODM (A)provides standardized data exchange and interoperability, it does not inherently reduce setup workload.Improving design processes (C)enhances efficiency but doesn’t guarantee consistency, andimplementing controlled terminology (D)helps with coding standardization, not database structure.

Therefore,option B—maintaining a library of form or screen modules— provides the most direct and sustainable improvement for scalability and quality.

Reference (CCDM-Verified Sources):

SCDM GCDMP, Chapter: Database Design and Build, Section 5.3 – Use of Standard Libraries and Templates

CDISC CDASH Implementation Guide, Section 3.2 – Reusable CRF Modules and Standardization

ICH E6(R2) GCP, Section 5.5.3 – Standardization and Reuse in Data Collection Systems