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Clinical Data Acceptance Testing Procedure
Selected as Best Practices Technique for Data Cleaning in the Pharmaceutical Industry by Information Impact: 
Sunil Gupta, Sunil.Gupta@Quintiles.com
- CDISC for Medical Device Team (Industry Expert)
- Subject Matter Expert for Edit Check Design Principles Chapter in Good Clinical Data Management Practices (GCDMP)
View Presentation Now: Practice Makes Perfect: Training and Performing in the Pharmaceutical Industry
SAS Global Forum, March 2009 
- Now available on demand, anytime:
- "Best Practices in SAS Statistical Programming for Regulatory Submission: Understanding and Applying the QC Plan to Validate Summary Tables" 
- "Best Practices in SAS Statistical Programming for Regulatory Submission: Creating Publication-Quality Summary Tables" 
- "Effective Clinical Data Acceptance Testing" 
These courses are offered through The Center for Professional Advancement, an organization which is CEU accredited.
More classes, articles and books by Sunil Gupta.
In the pharmaceutical industry, there is a regulatory responsibility, 21 CFR Part 11, to analyze only the clinical data that has passed data acceptance testing or is considered ‘clean data’ after a database lock. Clinical data acceptance testing procedure involves confirming the validity of critical data variables. These critical data variables might need to be non-missing, consist only of valid values, be within a range, or be consistent with other variables. If incorrect clinical data is analyzed, then invalid study conclusions can be drawn about the drug’s safety and efficacy.
In 2001, the Data Warehousing Institute conducted a survey of over 600 business professionals. Across all industries, the survey results estimate that data quality problems cost U.S. corporations more than $ 600 billion per year. Proactive steps need to be taken to identify, isolate and report clinical data issues using a system that is flexible, easy to update and facilitates good communication with the Clinical Data Management (CDM) department to help resolve these data quality problems.
This paper will review an effective method to implement a clinical data acceptance testing procedure using edit check macros for creating an RTF file with minimum SAS® expertise and maintenance. In addition, because all clinical studies have common issues, the edit check macros developed could easily be used to check similar data issues across other clinical studies.
Quotes from SAS Users
"Nice to learn more about ODS and I am glad to receive the downloads for the Clinical presentation also. Thank you for these excellent learning materials!!! Glad I got a chance to attend your informative sessions."
Margaret Burgess, NESUG 2008
Download SAS Paper
- Download all 20 Sunil Gupta's SAS papers 
More information on popular SAS clinical class: Best Practices in SAS Statistical Programming for Regulatory Submission.