What information on measurement uncertainty should be communicated to clinicians, and how?

Clin Biochem. 2018 Jul:57:18-22. doi: 10.1016/j.clinbiochem.2018.01.017. Epub 2018 Feb 2.

Abstract

The communication of laboratory results to physicians and the quality of reports represent fundamental requirements of the post-analytical phase in order to assure the right interpretation and utilization of laboratory information. Accordingly, the International Standard for clinical laboratories accreditation (ISO 15189) requires that "laboratory reports shall include the information necessary for the interpretation of the examination results". Measurement uncertainty (MU) is an inherent property of any quantitative measurement result which express the lack of knowledge of the true value and quantify the uncertainty of a result, incorporating the factors known to influence it. Even if the MU is not included in the report attributes of ISO 15189 and cannot be considered a post-analytical requirement, it is suggested as an information which should facilitate an appropriate interpretation of quantitative results (quantity values). Therefore, MU has two intended uses: for laboratory professionals, it gives information about the quality of measurements, providing evidence of the compliance with analytical performance characteristics; for physicians (and patients) it may help in interpretation of measurement results, especially when values are compared with reference intervals or clinical decision limits, providing objective information. Here we describe the way that MU should be added to laboratory reports in order to facilitate the interpretation of laboratory results and connecting efforts performed within laboratory to provide more accurate and reliable results with a more objective tool for their interpretation by physicians.

Keywords: Laboratory results interpretation; Measurement uncertainty; Reference change value; Total error.

Publication types

  • Review

MeSH terms

  • Clinical Decision-Making*
  • Clinical Laboratory Techniques / standards*
  • Data Interpretation, Statistical
  • Humans
  • Interdisciplinary Communication*
  • Laboratory Personnel
  • Physicians*
  • Quality Control
  • Reference Values
  • Uncertainty*