How to Ensure Conformance

Determining whether a product faithfully implements a standard or specification is essential to creating robust, interoperable solutions.

Standards for Data Collection

The following guidelines should be followed to ensure implementation of CDASH compliant CRFs

Guideline		Description
1	Core designations must be followed.	All Highly Recommended and applicable Recommended/Conditional fields must be present in the CRF and/or operational database. Match language in metadata description
2	CDISC Controlled Terminology must be used.	Specified controlled terminology must be used to collect the data in the CRF. All codelists displayed in the CRF must use or directly map to the current published CDISC CT submission values, when it is available. Subsets of published CT, such as those provided in CDASH terminology, can be used.
3	Best practices for CRF design must be followed.	The design of the CRF must follow guidance in Section 4.1, Best Practices for Creating Data Collection Instruments, and Section 4.2, CRF Design Best Practices. Update links
4	The wording of CRF questions should be standardized.	Specified Question Text or Prompts must be used to ask the question per associated guidance.
5	Variable naming conventions should be used in the operational database.
6	Data output by the operational database into an SDTMIG variable should require no additional processing if the CDASHIG and SDTMIG variable names are the same.	An SDTM data programmer should be able to assume that data in an SDTMIG variable is SDTMIG-compliant. Minimal processing (e.g., changing case) does not affect conformance. This helps to ensure a quality deliverable, even if the programmer is unfamiliar with data capture practices.
7	Validated questionnaires, ratings, or scales must present the questions and reply choices in the manner in which these were validated.	his must be followed to maintain the validity of a validated instrument. (See Section 8.3.12, QRS - Questionnaires, Ratings, and Scales). In some cases, this may result in CRFs that do not conform to CDASH best practices; however, restructuring these questionnaires should not be done because it could invalidate them. The use of such questionnaires in their native format should not be considered to affect conformance to CDASH.

Implementers must determine what additional data fields to add to address study-specific and therapeutic area requirements, and applicable regulatory and business practices. See Section 3.4, How to Create New Data Collection Fields When No CDASHIG Field Has Been Defined, for more information on how to create data collection fields that have not already been described in this implementation guide.

Data Tabulation

From SDTMIG

Conformance with the SDTMIG domain models is minimally indicated by:

Following the complete metadata structure for data domains
Following SDTMIG domain models wherever applicable
Using SDTM-specified standard domain names and prefixes where applicable
Using SDTM-specified standard variable names
Using SDTM-specified data types for all variables
Following SDTM-specified controlled terminology and format guidelines for variables, when provided
Including all collected and relevant derived data in one of the standard domains, special-purpose datasets, or general observation class structures
Including all Required and Expected variables as columns in standard domains, and ensuring that all Required variables are populated
Ensuring that each record in a dataset includes the appropriate Identifier and Timing variables, as well as a Topic variable
Conforming to all business rules described in the CDISC Notes column and general and domain-specific assumptions

Conformance with the SENDIG domain models is minimally indicated by:

Following the complete metadata structure for data domains
Following SENDIG domain models wherever applicable
Using SENDIG-specified standard domain names and prefixes per controlled terminology
Using SENDIG-specified standard variable names
Using SENDIG-defined variable labels for all standard domains
Using SDTM-specified data types for all variables
Following SDTM/SEND-specified controlled terminology and format guidelines for variables when provided
Including all collected and relevant derived data in one of the standard domains, special-purpose datasets, or general-observation class structures
Including all required and expected variables as columns in standard domains, and ensuring that all required variables are populated
Ensuring that each record in a dataset includes the appropriate identifier and timing variables as well as a topic variable
Conforming to all business rules described in the CDISC Notes column and general and domain-specific assumptions
Ensuring that the datasets are in SAS v5 transport file format or other transport file format required by a regulatory agency

Data Analysis

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How to Ensure Conformance