Sabrina Connaughton, Data Standard Analyst
Clinical research relies on data. As the backbone of drug and device development, data indicates the safety and efficacy of drugs and devices throughout the trial process. So who manages it? At Medpace, our Biometrics team is critical in caring for data from processing, cleaning, storage, and more.
Follow along in this month’s edition of Monthly Role Spotlight as Sabrina Connaughton sheds light on her role as a Data Standard Analyst and the imperative functions her team serves at Medpace.
Why is the role of a Data Standard Analyst important in clinical research?
The role of a Data Standard Analyst is critically important in clinical research because data standardization and data cleaning directly impact the quality, comparability, regulatory compliance, and reliability of clinical trial data. Clinical research data must comply with regulatory standards such as Clinical Data Interchange Standards Consortium (CDISC) including Study Data Tabulation Model (SDTM). Data Standard Analysts ensure that all collected and reported data conform to these regulatory standards, which is a mandatory requirement for submissions to authorities.
How would you describe your role to someone outside of the clinical research industry?
As a Data Standard Analyst (DSA), my day-to-day mostly consists of programming. I standardize clinical research data based on industry standards into SDTM data and assist with identifying data discrepancies that occur in the data. In the beginning, and throughout a study, the Data Management team reaches out to the DSA team to create edit check programs based on specifications. This is used to assist in identifying data discrepancies. The output of these edit check programs is used by Data Management and help to identify potential data issues that could affect analyses and should be updated at the source. The clinical research data is also used by DSA team to create annotated Case Report Forms (CRFs), mapping specifications, and SDTM data per CDISC standards for collected study-level source data. The SDTM data is then given to the Biostatistics team for them to use for statistical analysis.
Why should someone consider a career as a Data Standard Analyst?
A career as a Data Standard Analyst can be highly rewarding, particularly for individuals who are detail-oriented, enjoy working with data, and are interested in ensuring consistency and quality across data systems. This role allows you to help define and maintain data standards while also encouraging cross-functional collaboration between different groups within the Medpace Biometrics team. It’s exciting to get to work on studies and then see the impact your work has, knowing the drugs/devices we helped get through clinical trials are essential to others and possibly save lives.
What are three key job responsibilities?
Some key responsibilities for the Data Standard Analyst role are as follows:
- Implement edit check specifications into SAS programs used to assist in identifying data discrepancies in clinical research data
- Create annotated CRFs, mapping specifications, and SDTM data via SAS programming per CDISC standards for collected study clinical research data
- Maintaining an open communication between the different groups that work on the study so programming and the later on analysis move forward efficiently and without issue.
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