SCDM CCDM Exam Dumps - Actual Questions Answers

When initially assessingdata cleanlinessin preparation for aninterim analysis, the focus should be onoutstanding issuesthat could affect data completeness and reliability.

According to theGCDMP (Chapter: Data Quality Assurance and Control), key indicators of readiness include:

TheCRF data entry statusof received pages (option A) to confirm completeness.

Identification ofmissing pages or visits(option B) to verify subject-level completeness.

A listing ofoutstanding discrepancies and their aging(option D) to assess unresolved data issues.

Counting the number ofdiscrepancies resolved to date (option C), however, does not reflect data quality or current data readiness—it indicates past actions rather than current unresolved risks. Therefore, it isnot a valid measurefor assessing interim data cleanliness.

Reference (CCDM-Verified Sources):

SCDM Good Clinical Data Management Practices (GCDMP), Chapter: Data Quality Assurance and Control, Section 6.1 – Data Readiness Assessments for Analysis

ICH E6 (R2) GCP, Section 5.18.4 – Ongoing Data Quality Review

FDA Guidance for Industry: Oversight of Clinical Investigations – Risk-Based Monitoring, Section 7 – Data Quality Indicators

In aSQL (Structured Query Language)database, theSELECTstatement specifies which columns to display from a table. In this query, only three columns —Pt_ID,MRN, andSSN— are being selected from thepatienttable.

This means the resulting dataset will contain:

The same number ofrows (records)as the original table (assuming noWHEREfilter), and

Fewer columnsthan the full table.

In database terminology:

“Wider” refers to more columns (fields).

“Narrower” refers to fewer columns (fields).

Since this query retrieves only 3 columns (out of potentially many in the original table), the result set isnarrower than the patient table, makingoption Dcorrect.

Reference (CCDM-Verified Sources):

SCDM GCDMP, Chapter: Database Design and Build, Section 5.1 – Relational Databases and Query Logic

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

FDA Guidance for Industry: Computerized Systems Used in Clinical Investigations, Section 6.4 – Database Query Controls

The described process isBlind Verification, also known asdouble data entry with blind verification. In this method, two independent operators enter the same data. The second operator isblindedto the first entry to avoid bias. When discrepancies arise, the system flags them for review, and the second entry (or an adjudicated value) is retained as the correct one.

According toGCDMP (Chapter: Data Entry and Data Tracking), blind double data entry is used primarily inpaper-based studiesto minimize transcription errors and ensure data accuracy.

Single entry (D):Only one operator enters data.

Manual review (B):Involves post-entry checking, not during entry.

Third-party compare (C):Used for reconciling external data sources, not CRF data.

Hence,option A (Blind verification)is the correct and CCDM-defined process.

Reference (CCDM-Verified Sources):

SCDM GCDMP, Chapter: Data Entry and Data Tracking, Section 5.1 – Double Data Entry and Verification Methods

ICH E6(R2) GCP, Section 5.5.3 – Data Entry and Verification Controls

FDA Guidance for Industry: Computerized Systems Used in Clinical Investigations, Section 6.2 – Data Accuracy and Verification