Pass the SCDM Clinical Data Management CCDM Questions and answers with CertsForce

In aCRF-to-database quality control (QC) audit, auditors compare data recorded on the paper Case Report Form (CRF) with data entered in the electronic database. If discrepancies exist thatcannot be explained by documented data handling conventions, they are classified asaudit findings.

PerGCDMP (Chapter: Data Quality Assurance and Control),data handling conventionsdefine acceptable data entry practices, transcription rules, and allowable transformations. These conventions ensure that CRF data are consistently interpreted and entered.

If a discrepancy deviates from these established rules, it indicates a process gap or error in data entry, validation, or training. Discrepancies justified by protocol design or CRF guidelines would not constitute findings.

Therefore,option C (Discrepancy not explained by the data handling conventions)correctly identifies the criterion for a true QC audit finding.

Reference (CCDM-Verified Sources):

SCDM GCDMP, Chapter: Data Quality Assurance and Control, Section 6.1 – Data Handling Conventions and QC Auditing

ICH E6(R2) GCP, Section 5.1 – Quality Management and Documentation of Deviations

FDA Guidance for Industry: Computerized Systems Used in Clinical Investigations, Section 6.5 – Data Verification and Audit Findings

The best choice for managingStandard Operating Procedures (SOPs)in a compliant and auditable manner is aDocument Management System (DMS).

According to theGCDMP (Chapter: Regulatory Requirements and Compliance)andICH E6 (R2), SOPs must beversion-controlled, securely stored, retrievable, and auditable. Avalidated DMSsupports controlled access, document lifecycle management (draft, review, approval, and archival), and electronic audit trails, ensuring full compliance withFDA 21 CFR Part 11andGood Documentation Practices (GDP).

WhileLearning Management Systems (C)track training, they are not intended for document control.Spreadsheets (B)andpaper systems (D)cannot provide adequate version tracking, access security, or audit capability required for regulatory inspection readiness.

Reference (CCDM-Verified Sources):

SCDM Good Clinical Data Management Practices (GCDMP), Chapter: Regulatory Requirements and Compliance, Section 5.2 – SOP Management and Document Control

ICH E6 (R2) GCP, Section 5.5.3 – Document and Record Management

FDA 21 CFR Part 11 – Electronic Records and Signatures, Section 11.10 – System Validation and Document Controls

Thebest practicefor developingelectronic Case Report Forms (eCRFs)is to involvecross-functional team membersthroughout the design process.

According to theGCDMP (Chapter: CRF Design and Data Collection), eCRFs should be collaboratively developed bydata management, clinical operations, biostatistics, medical, and regulatory teams. Each function provides a unique perspective — data managers focus on data capture and validation; statisticians ensure alignment with analysis requirements; clinicians ensure medical relevance and protocol compliance.

Collaborative development ensures that the eCRFs arefit-for-purpose, capturing all required data accurately, minimizing redundancy, and supporting downstream data analysis.

Options A and B violate good data management practice because sites should not directly access coded terms (to prevent bias), and fields shouldnever auto-populate without explicit source verification. Option D is outdated; while paper CRFs may inform structure,EDC-optimized eCRFsshould leverage system functionality rather than mimic paper.

Reference (CCDM-Verified Sources):

SCDM Good Clinical Data Management Practices (GCDMP), Chapter: CRF Design and Data Collection, Section 4.2 – Collaborative CRF Development

ICH E6 (R2) GCP, Section 5.5.3 – Data Collection and System Validation

FDA Guidance for Industry: Electronic Source Data in Clinical Investigations, Section 3.4 – CRF Design Considerations

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

According to theGCDMP (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. Thedata error enumeration sectiondirectly 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

Thebest practicewhen implementing aprotocol amendmentthat affects CRF content or data collection timing is toupdate the eCRF completion guidelines and notify sites before implementing the change.

According to theGCDMP (Chapter: CRF Design and Data Collection), theeCRF Completion Guidelines (eCRF CG)are an essential study tool that instructs site personnel on accurate and consistent data entry. When new data elements or collection time points are added, the guidelines must berevised, version-controlled, and communicatedto all users prior to implementation to ensure sites collect and enter data correctly.

Simply relying on the revised CRF (option C) or updating the document without notification (option B) violates communication and training standards. Likewise, notifying sites without updating the documentation (option D) leaves insufficient reference material for data entry compliance.

Reference (CCDM-Verified Sources):

SCDM Good Clinical Data Management Practices (GCDMP), Chapter: CRF Design and Data Collection, Section 5.5 – Managing CRF Revisions and Site Communication

ICH E6 (R2) GCP, Section 5.18.4 – Communication of Protocol Amendments and Documentation Updates

FDA Guidance for Industry: Electronic Source Data in Clinical Investigations, Section 4.3 – Site Communication and Documentation Management

In studies where themedical record serves as the source document, theElectronic Data Capture (EDC)system users (typically study coordinators or site personnel) must have appropriatetraining 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) andGood Clinical Data Management Practices (GCDMP).

According to theGCDMP (Chapter: EDC Systems and Data Capture)andICH 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.

Whileresolving discrepant data (C)andscreening subjects (A)are part of study operations, thecompetency directly related to EDC system use in EMR-based studiesis 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

In international or multicenter clinical studies,laboratory dataoften originate from different laboratories that use varying measurement units (e.g., mg/dL vs. mmol/L). TheGood Clinical Data Management Practices (GCDMP, Chapter on CRF Design and Data Collection)provides clear guidance on managing this variability to ensuredata consistency,traceability, andminimized transcription errors.

The approach that results infewer transcription errorsis toallow sites to enter lab values exactly as recorded in the source document (original lab report)and to requireexplicit selection of the corresponding unitfrom a predefined list on the data collection form or within the electronic data capture (EDC) system. This method (Option B) preserves the original source data integrity while enabling centralized or automated unit conversion later during data cleaning or statistical processing.

Option B also supports compliance withICH E6 (R2) Good Clinical Practice (GCP), which mandates that transcribed data must remain consistent with the source documents. Attempting to derive units automatically (Option A) can lead to logical errors, while forcing sites to manually convert units (Option D) introduces unnecessary complexity and increases the risk of miscalculation or inconsistent conversions. Printing only standard units on the CRF (Option C) ignores local lab practices and can lead to discrepancies between CRF entries and source records, triggering numerous data queries.

TheGCDMPemphasizes that CRF design must account for local variations in measurement systems and ensure thatunit selection is structured (dropdowns, controlled lists)rather than free-text to prevent typographical errors and facilitate standardization during data transformation.

Therefore, OptionB—“Allow values to be entered as they are in the source and the selection of units on the data collection form”—is the most compliant, accurate, and efficient strategy for minimizing transcription errors in international lab data collection.

Reference (CCDM-Verified Sources):

Society for Clinical Data Management (SCDM), Good Clinical Data Management Practices (GCDMP), Chapter: CRF Design and Data Collection, Section 5.4 – Laboratory Data Management and Unit Handling

ICH E6 (R2) Good Clinical Practice, Section 5.18 – Data Handling and Record Retention

CDISC SDTM Implementation Guide, Section 6.3 – Handling of Laboratory Data and Standardized Units

FDA Guidance for Industry: Computerized Systems Used in Clinical Investigations, Section 6 – Source Data and Accuracy of Data Entry

The section of theClinical Study Report (CSR)most useful for aData Manageris thedescription of how data were processed.

According to theGCDMP (Chapter: Data Quality Assurance and Control), this section details thedata handling methodology— includingdata cleaning, coding, transformation, and derivation procedures— all of which are core responsibilities of data management. Reviewing this section ensures that the data processing methods documented in the CSR align with theData Management Plan (DMP),Data Validation Plan (DVP), anddatabase specifications.

Thestatistical methods section (option A)is primarily for biostatistics, and therationale for study design (option B)pertains to clinical and regulatory affairs.Clinical narratives (option D)are used by medical reviewers, not data managers.

By reviewing how data were processed, the Data Manager verifies that the study data lifecycle—from collection to analysis—was conducted in compliance with regulatory and GCDMP standards.

Reference (CCDM-Verified Sources):

SCDM Good Clinical Data Management Practices (GCDMP), Chapter: Data Quality Assurance and Control, Section 6.3 – Documentation of Data Processing in Clinical Study Reports

ICH E3 – Structure and Content of Clinical Study Reports, Section 11.3 – Data Handling and Processing

FDA Guidance for Industry: Clinical Study Reports and Data Submission – Data Traceability and Handling Documentation

In the context ofdatabase design and external data management, atest data transfer(or trial data load) is performed to ensure the proper configuration, structure, and integrity of data imported from an external vendor or system. Thesecond test transferis specifically useful to confirm thatdata structures and formatsare consistently aligned between the sending and receiving systems after initial adjustments have been made from the first test.

According to theGood Clinical Data Management Practices (GCDMP), thefile format— including variables, data types, field lengths, delimiters, and encoding — must be validated during test transfers to confirm compatibility and ensure accurate loading into the target database. Once the initial test identifies and corrects errors (e.g., mismatched variable names or data types), the second transfer verifies that the corrections have been implemented correctly and that the file structure functions as intended.

Testing change management (A) involves procedural controls, not data transfers. Thetransfer method (C)andtransfer frequency (D)are validated during initial process setup, not during subsequent test transfers.

Therefore,option B (File format)is correct, as the second test transfer verifies the technical integrity of the file structure before live production transfers begin.

Reference (CCDM-Verified Sources):

SCDM Good Clinical Data Management Practices (GCDMP), Chapter: External Data Transfers and Data Integration, Section 5.2 – Test Transfers and File Validation

FDA Guidance for Industry: Computerized Systems Used in Clinical Investigations, Section 6.3 – Data Import and Validation Controls

Case Report Form Completion Guidelines (CCGs)are essential study documents that instruct site staff on how to complete each field of the CRF correctly. Aminimum requirementfor CCGs, according toGood Clinical Data Management Practices (GCDMP, Chapter: CRF Design and Data Collection), is that they must includeversion 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 implementedbefore 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