Applied Nursing Research
Volume 18, Issue 1 , Pages 50-54, February 2005

Pragmatic strategies that enhance the reliability of data abstracted from medical records☆

  • Clara Eder, EdD, MPH, RD

      Affiliations

    • Center for Health Professional Education and Training, San Diego State University, San Diego, CA 92120, USA
    • Corresponding Author InformationCorresponding author. Tel.: +1 619 594 5849; fax: +1 619 594 6963.
    • ,
  • Judith Fullerton, PhD, CNM, FACNM

      Affiliations

    • Center for Health Professional Education and Training, Project Concern International, San Diego, CA 92123, USA
    • ,
  • Robert Benroth, MHA

      Affiliations

    • Center for Health Professional Education and Training, San Diego State University, San Diego, CA 92120, USA
    • ,
  • Suzanne P. Lindsay, PhD, MSW, MPH

      Affiliations

    • Center for Health Professional Education and Training, San Diego State University, San Diego, CA 92120, USA

Received 20 February 2004; received in revised form 22 April 2004; accepted 30 April 2004.

Abstract 

The processes and procedures used to promote interrater reliability in the abstraction of data from medical records are described. Several proactive strategies that serve the purpose of leading to standard interpretations of clinical data are discussed. These include (a) establishment of priorities for the sources of information; (b) creation of orders of value for the likeliness of validity of recorded data; (c) standardization of terminology; and (d) reaffirmation of decisions, based on an evolving body of evidence. Lessons learned from this project can assist nurse researchers to develop high-quality information retrieval methods, when multiple observers (or abstractors) are used during a medical record abstraction data collection process.

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☆ Supported in part by funds received from the State of California, Department of Health Services, Cancer Detection Section. All analysis, interpretations, and conclusions presented in this article are those of the authors and not the State of California. There are no known biases in the data presented that would affect the results.

PII: S0897-1897(04)00118-1

doi:10.1016/j.apnr.2004.04.005

Applied Nursing Research
Volume 18, Issue 1 , Pages 50-54, February 2005

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