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Data management in clinical investigations - Part 1: Study variables

cro data management

The high quality of clinical investigation data is critical for demonstrating the performance and safety of a medical device. Variable listing in a structured, human and machine-readable variable specification that supports customized programmatic data quality controls during the study. Labquality offers data management services as part of the wider CRO clinical investigations offering.


To fully execute the statistical analysis plan (SAP) and to meet the investigation objectives as defined in the clinical investigation plan (CIP) all data intended to be collected must be actually collected in the eCRF and collected data must be accurate, complete, consistent and auditable. Additionally, data not identified in the clinical investigation plan and study data privacy policy must not be collected. Study design can easily include hundreds of variables, several data sources and regulations, which makes variable management a risk if not done systematically.

Variable listing is a structured, human and machine-readable document that collects and lists all data items/ variables in the study. It is a master listing of data to be collected and contains for each data item/ variable structured attributes such as unique variable identifier, data type, valid value ranges, valid value rules (edit checks), data source, eCRF question, database table and column etc.

Machine readability enables the building of automated real-time and batch analysis to test that the data collected conforms to its specifications at all times. This provides data quality visibility to the trial management team, supports risk-based monitoring and prepares for database locking reviews.

This post was written by Labquality's Data Manager Markus Vattulainen.

You can contact him for more information:

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