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Data Quality in Clinical Research

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Clinical Research Informatics

Part of the book series: Health Informatics ((HI))

Abstract

Every scientist knows that research results are only as good as the data upon which the conclusions were formed. However, most scientists receive no training in methods for achieving, assessing, or controlling the quality of research data—topics central to clinical research informatics. This chapter covers the basics of collect and process research data given the available data sources, systems, and people. Data quality dimensions specific to the clinical research context are used, and a framework for data quality practice and planning is developed. Available research is summarized, providing estimates of data quality capability for common clinical research data collection and processing methods. This chapter provides researchers, informaticists, and clinical research data managers basic tools to plan, achieve, and control the quality of research data.

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Author information

Authors and Affiliations

  1. Informatics, Duke Translational Medicine Institute, Duke University, 2424 Erwin Road, Durham, NC, 27705, USA

    Meredith Nahm Ph.D.

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  1. Meredith Nahm Ph.D.
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Correspondence to Meredith Nahm Ph.D. .

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Editors and Affiliations

  1. College of Medicine, University of South Florida, Bruce B. Downs Blvd. 12901, Tampa, 33612-4799, Florida, USA

    Rachel L. Richesson

  2. College of Medicine, University of South Florida, Bruce B. Downs Blvd. 12901, Tampa, 33612-4799, Florida, USA

    James E. Andrews

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Nahm, M. (2012). Data Quality in Clinical Research. In: Richesson, R., Andrews, J. (eds) Clinical Research Informatics. Health Informatics. Springer, London. https://doi.org/10.1007/978-1-84882-448-5_10

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  • DOI: https://doi.org/10.1007/978-1-84882-448-5_10

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