6. Understanding Bias in Diagnostic Research

  1. Jesse M. Pines1,2,
  2. Christopher R. Carpenter3,4,
  3. Ali S. Raja5,
  4. Jeremiah D. Schuur5

Published Online: 8 NOV 2012

DOI: 10.1002/9781118482117.ch6

Book Title

Evidence-Based Emergency Care: Diagnostic Testing and Clinical Decision Rules, Second Edition

Evidence-Based Emergency Care: Diagnostic Testing and Clinical Decision Rules, Second Edition

Additional Information

How to Cite

Pines, J. M., Carpenter, C. R., Raja, A. S. and Schuur, J. D. (2012) Understanding Bias in Diagnostic Research, in Evidence-Based Emergency Care: Diagnostic Testing and Clinical Decision Rules, Second Edition, John Wiley & Sons, Ltd, Chichester, UK. doi: 10.1002/9781118482117.ch6

Author Information

  1. 1

    Center for Healthcare Quality, George Washington University, Washington, DC, USA

  2. 2

    Emergency Medicine and Health Policy, George Washington University, Washington, DC, USA

  3. 3

    Evidence Based Medicine, Washington University, St. Louis, MO, USA

  4. 4

    Division of Emergency Medicine, Barnes Jewish Hospital, Washington University, St. Louis, MO, USA

  5. 5

    Department of Emergency Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA

Publication History

  1. Published Online: 8 NOV 2012
  2. Published Print: 7 NOV 2012

ISBN Information

Print ISBN: 9780470657836

Online ISBN: 9781118482117

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CHAPTER TOOLS

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Keywords:

  • understanding bias in diagnostic research;
  • STARD criteria, a systematic approach in diagnostic research;
  • STARD, a 25-item checklist of considerations;
  • QUADAS methods, assessing four domains of bias;
  • MOOSE statement, structural framework for systematic reviews;
  • diagnostic research, vulnerable to forms of bias;
  • context bias problematic, double criterion bias and variables;
  • cutoff bias in studies, using variable/undefined thresholds;
  • moving beyond bias to effectiveness;
  • hierarchical outcomes-based to diagnostic research

Summary

This chapter contains sections titled:

  • Types of bias

  • Moving Beyond Bias to Effectiveness

  • References

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