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Read about DAQCORD on EQUATOR (Enhancing the QUAlity and Transparency Of health Research) Network

The EQUATOR (Enhancing the QUAlity and Transparency Of health Research) Network is an international initiative that seeks to improve the reliability and value of published health research literature by promoting transparent and accurate reporting and wider use of robust reporting guidelines.

Guidelines for the design, reporting and data quality assessment for large observational clinical data collection


Meeting notes - Consensus Conference on Data Acquisition, Quality & Curation for Observational Research Designs (DAQCORD) Sept. 18 – 19, 2018

Experts in clinical research design, bioinformatics, data management, biomarker and therapy development, and other relevant fields were invited to participate in a consensus conference. A modified Delphi process was used to reach agreement on the items and structure for the DAQCORD self-assessment and reporting tool. Prior to the meeting, participants received preparatory information by email and webinars to complete a pre-meeting survey (Round 1). During the meeting, participants reviewed, discussed and refined the survey in an iterative process (Rounds 2 and 3), and also developed a plan for implementation. 

Read the detailed meeting notes

2019 Spring Clinical and Translational Science Awards (CTSA) Program Group Meetings

The following proposal was submitted to the Clinical and Translational Science Awards (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.

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