Free SCDM CCDM Practice Exam with Questions & Answers | Set: 3

When a system validation test fails duringElectronic Patient-Reported Outcome (ePRO)system testing, thevalidation documentationmust record theexpected results(what should have occurred) and theactual results(what occurred).

According to theGCDMP (Chapter: Database Validation and Testing), proper system validation documentation ensurestraceability, reproducibility, and compliancewithFDA 21 CFR Part 11andICH E6 (R2). Each test case must include:

Test objective,

Preconditions,

Test steps,

Expected results,

Actual results, and

Pass/fail status.

If a test fails, this documentation provides the objective evidence necessary for deviation handling, issue resolution, and re-testing. While a separateroot cause analysismay be performed later (option D), the validation record itself must focus on verifying outcomes against predefined expectations.

Therefore, the correct answer isB – Expected and actual results.

Reference (CCDM-Verified Sources):

SCDM Good Clinical Data Management Practices (GCDMP), Chapter: Database Validation and Testing, Section 4.4 – Documentation of Test Results

FDA 21 CFR Part 11 – Validation Requirements (Section 11.10(a))

ICH E6 (R2) GCP, Section 5.5.3 – Computer System Validation and Documentation

Whenmerging data from different clinical trials, theuse of a common adverse event (AE) dictionary(such asMedDRAorWHO Drug) is essential to ensure consistency and comparability across datasets.

According to theGCDMP (Chapter: Standards and Data Mapping)andCDISC SDTM Implementation Guide, data integration across studies requires standardized terminology for adverse events, medications, and clinical outcomes. Using the same AE dictionary ensures that similar terms are coded consistently, allowing accurate cross-study analysis, pooled summaries, and safety reporting.

A sharedsoftware platform (option A)is not necessary if data are mapped to standard formats (e.g., CDISC SDTM). Patient population similarity (option B) affects interpretation but not technical data merging. Study design differences (option C) may influence statistical analysis but not data integration mechanics.

Therefore,Option D – Use of a common adverse event dictionary– is the correct and most critical action for consistent multi-study data integration.

Reference (CCDM-Verified Sources):

SCDM Good Clinical Data Management Practices (GCDMP), Chapter: Standards and Data Mapping, Section 5.1 – Use of Standardized Coding Dictionaries

CDISC SDTM Implementation Guide, Section 4.3 – Controlled Terminology and Cross-Study Integration

ICH E3 and E2B – Clinical Data Standards and Safety Coding Requirements

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

When using acopyrighted or validated rating scale(e.g., Hamilton Depression Scale, Visual Analog Pain Scale), anymodification to the original instrument, including preprinting database codes on the CRF, must beapproved by the instrument’s owner or licensing authorityto ensure thevalidity and reliabilityof the instrument are not compromised.

According to theGCDMP (Chapter: CRF Design and Data Collection), validated rating scales are psychometrically tested tools. Any visual or structural modification (such as adding codes, changing layout, or rewording questions) can invalidate prior validation results. Therefore, the CRF designer mustconsult the independent source (copyright holder)for approval anddocument that the validity of the tool remains intact.

Merely consulting statisticians (option B) or verifying database alignment (option D) does not ensure compliance. Thus,Option Censures scientific and regulatory integrity.

Reference (CCDM-Verified Sources):

SCDM Good Clinical Data Management Practices (GCDMP), Chapter: CRF Design and Data Collection, Section 6.1 – Use of Validated Instruments and Rating Scales

ICH E6 (R2) GCP, Section 5.5.3 – Validation of Instruments and Data Capture Tools

FDA Guidance for Industry: Patient-Reported Outcome Measures – Use in Medical Product Development to Support Labeling Claims, Section 4 – Instrument Modification and Validation

In studies utilizingElectronic Data Capture (EDC)systems, many traditional paper-based processes such astracking and retrieving CRFsare eliminated or automated. However,query management and resolutionremain essential because discrepancies, missing data, and protocol deviations still require clarification and correction, regardless of the data collection medium.

According to theGCDMP (Chapter: Data Validation and Cleaning),data queriesare generated automatically or manually when inconsistencies are detected by edit checks. Sites must still respond to these queries electronically to ensure the integrity and completeness of data.

AandDare obsolete with EDC (no physical CRFs).

Brefers to manual data entry updates, which are replaced by direct EDC entry.

C (Resolving queries)continues as a key part of the data management workflow, even in fully electronic environments.

Thus,option Cis correct.

Reference (CCDM-Verified Sources):

SCDM GCDMP, Chapter: Data Validation and Cleaning, Section 5.4 – Query Generation and Resolution in EDC Systems

ICH E6(R2) GCP, Section 5.5.3 – Data Review and Query Resolution Requirements

FDA 21 CFR Part 11 – Electronic Records: Audit Trails and Query Documentation

C

TheQuery frequency counts per data element(Option D) is the best metric for identifyingdata trends and potential systemic data issuesin clinical trials.

According to theGood Clinical Data Management Practices (GCDMP, Chapter: Data Quality Assurance and Control),trend analysisinvolves identifying recurring data issues across subjects, sites, or variables to detect training gaps, protocol misinterpretation, or CRF design flaws. A high number of queries generated for specific fields (e.g., visit date, lab values, or dosing information) may indicate systemic problems such as unclear CRF instructions or site-level misunderstandings.

While metrics such aspercent of data cleaned (A)andtime to database lock (B)reflect overall progress and efficiency, they do not identifyspecific data pattern issues. Thenumber of subjects screened/enrolled (C)pertains to recruitment rather than data quality.

Therefore,query frequency per data elementprovides actionable insights for quality improvement, process refinement, and early identification of potential risks.

Reference (CCDM-Verified Sources):

SCDM Good Clinical Data Management Practices (GCDMP), Chapter: Data Quality Assurance and Control, Section 6.3 – Metrics and Trend Analysis

ICH E6 (R2) Good Clinical Practice, Section 5.18.4 – Risk-Based Quality Review and Data Trends

FDA Guidance for Industry: Oversight of Clinical Investigations – Risk-Based Monitoring, Section 6 – Data Metrics and Trend Evaluation

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

When adata inconsistencyarises — such as a record of “worsening of migraine” without prior documentation of a migraine episode — the Data Manager shouldquery the site for clarification(Option D).

According to theGCDMP (Chapter: Data Validation and Cleaning), data managers must raise aclarification querywhenever data appear incomplete, inconsistent, or ambiguous. The site must confirm whether “worsening of migraine” refers to anew eventor anexacerbation of a preexisting condition. This clarification ensures accurate safety reporting and appropriate medical coding (e.g., MedDRA classification).

Checking the medical history (Option C) may help but does not resolve the inconsistency. Assuming a relationship (Option A or B) without verification would violateGood Clinical Data Management Practiceand potentially misrepresent the adverse event.

Reference (CCDM-Verified Sources):

SCDM Good Clinical Data Management Practices (GCDMP), Chapter: Data Validation and Cleaning, Section 6.3 – Query Generation and Resolution

ICH E2A – Clinical Safety Data Management: Definitions and Standards for Expedited Reporting, Section II – Data Clarification Requirements

FDA Guidance for Industry: Computerized Systems Used in Clinical Investigations – Data Query Management

In a discrepancy management workflow,“Received from site and not yet reviewed”isnot a resolution type— it represents astatus, not a final resolution outcome.

According to theGCDMP (Chapter: Data Validation and Cleaning), resolution types describe how a data discrepancy was finalized or addressed, such as:

Resolved with data correction,

Confirmed as correct (no change required),

Self-evident correction applied by data management, or

Unresolvable discrepancies documented.

In contrast,statusesdescribe the stage of the query (e.g., open, sent, answered, pending review, closed). “Received from site and not yet reviewed” indicates anintermediate workflow statewhere the response awaits validation by data management.

Proper classification of resolution types is essential for performance reporting, audit readiness, and ensuring the traceability of query management actions underICH E6 (R2)andFDA 21 CFR Part 11.

Reference (CCDM-Verified Sources):

SCDM Good Clinical Data Management Practices (GCDMP), Chapter: Data Validation and Cleaning, Section 5.3 – Discrepancy Resolution Lifecycle

ICH E6 (R2) Good Clinical Practice, Section 5.5.3 – Data Handling and Record Management

FDA 21 CFR Part 11 – Electronic Records; Audit Trails and Discrepancy Tracking Requirements

When an investigator retires mid-study and the replacement refuses to use theElectronic Data Capture (EDC)system, thedata managermust not take unilateral action but rathercollaborate with the study teamto explore acceptable solutions.

Per theGCDMP (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 withICH E6 (R2) GCPandFDA 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