DAQCORD – Data Access Quality & Curation for Observational Research Designs

Sharing “big, complex data” has enormous potential to enhance and accelerate biomedical research and knowledge. However, it also comes with risks, as reflected in the still commonly heard phrase “Garbage in, garbage out”. Rather than assume that data is “good” or “bad”, we propose to develop a practical self-assessment and reporting method for clinical research studies. The goal is to capture key information about data acquisition, quality control measures, and curation in a tool that is linked to the dataset so that potential research collaborators can determine if the data meets their needs and expectations. While the impetus for the consensus conference came out of the International Traumatic Brain Injury Research (InTBIR) initiative, we believe that the DAQCORD reporting system will be relevant to many brain diseases and disorders.


The following proposal was submitted to the CTSA Program Committee.
2019 Spring CTSA Program Group Meetings
March 4 – 8, Marriott Wardman Park Hotel, 2660 Woodley Rd NW, Washington, DC 20008

Session Title: Data Acquisition, Quality and Curation in Observational Research Designs
Moderator: Christopher Lindsell, PhD, Vanderbilt University Medical Center
Presentation: Practical Steps for High Quality Data: the DAQCORD Tool , Ari Ercole, MD/PhD, Cambridge University
Discussant: DAQCORD in the Broader Context of the Clinical and Translational Research, Leah J. Welty, PhD, Northwestern University

Description: Data quality matters but is often under-appreciated and there are serious hidden dangers in designing large studies. But how should we evaluate and promote best practices in data management to ensure high quality? The Data Acquisition, Quality & Curation for Observational Studies (DAQCORD) project has developed a minimal list of data quality indicators that serve as 1) a guide for designing studies; and 2) a self-assessment tool and standardized report.  DAQCORD grew from lessons learned in the International Traumatic Brain Injury Research initiative (InTBIR), and has grown to include experts across a range of disciplines to ensure that it simple tool is useful for anyone designing observational research.  Future considerations include DAQCORD’s relevance and generalizability to electronic health record (EHR) data. This session will give an overview of the DAQCORD project and provide practical steps researchers can take to ensure their data has the quality they expect. We will also consider how DAQCORD can inform data quality more broadly in clinical and translational research.