Standard Document
First Edition
Method Evaluation

CLSI EP29

Expression of Measurement Uncertainty in Laboratory Medicine

This guideline presents a practical approach to help clinical laboratories develop and calculate useful estimates of measurement uncertainty. It also demonstrates how to apply these estimates to maintain and improve the quality of measured values used in patient care.

 

January 31, 2012
Anders Kallner, MD, PhD

{{FormatPrice(currentPrice)}}

Free

{{FormatPrice(nonMemberPrice)}} List Price
This is your member pricing.
Notify Me About New Editions
Abstract

Clinical and Laboratory Standards Institute document EP29-A—Expression of Measurement Uncertainty in Laboratory Medicine; Approved Guideline describes the principles of estimating measurement uncertainty and provides guidance to clinical laboratories and in vitro diagnostic device manufacturers on the specific issues to be considered for implementation of the concept in laboratory medicine. This document illustrates the assessment of measurement uncertainty with both bottom-up and top-down approaches. The bottom-up approach suggests that all possible sources of uncertainty are identified and quantified in an uncertainty budget. A combined uncertainty is calculated using statistical propagation rules. The top-down approach directly estimates the measurement uncertainty results produced by a measuring system. Methods to estimate the imprecision and bias are presented theoretically and in worked examples.

Scope

This guideline explains the concept, estimation, and application of measurement uncertainty in the field of clinical laboratory medicine. The recommendations provided are consistent with the Guide to the expression of uncertainty in measurement (GUM) and with the International Organization for Standardization (ISO) standards concerned with laboratory accreditation. 

This guideline briefly discusses, but does not fully address, the following nonmeasurement sources of uncertainty of a measurement result: 

• Biological variation of the measurand 

• Pre- and postmeasurement processes 

The guideline discusses the definition of what is intended to be measured, lists sources of measurement uncertainty, describes the generation of statistical estimates of uncertainties and their combination, and discusses the use of uncertainty estimates. The guideline applies only to quantitative measurements. In measurement procedures that are reported in qualitative terms based on a quantitative measurement, the uncertainty at the threshold(s) for a qualitative interpretation should be considered when making the qualitative assessment. 

This guideline is intended for clinical laboratories and in vitro diagnostic (IVD) device manufacturers.

Product Details
EP29AE
1-56238-787-1
Additional Details

This document is available in electronic format only.

This archived document is no longer being reviewed through the CLSI Consensus Document Development Process. However, this document is technically valid and because of its value to the laboratory community, it is being retained in CLSI’s library.

Authors
Anders Kallner, MD, PhD
Stanley F. Lo, PhD, DABCC, FACB
James C. Boyd, MD
Gene Pennello, PhD
David L. Duewer, PhD
David Sogin, PhD
Claude Giroud, PhD
Daniel W. Tholen, MS
Aristides T. Hatjimihail, MD, PhD
Blaza Toman, PhD
George G. Klee, MD, PhD
Graham H. White, PhD
Abstract

Clinical and Laboratory Standards Institute document EP29-A—Expression of Measurement Uncertainty in Laboratory Medicine; Approved Guideline describes the principles of estimating measurement uncertainty and provides guidance to clinical laboratories and in vitro diagnostic device manufacturers on the specific issues to be considered for implementation of the concept in laboratory medicine. This document illustrates the assessment of measurement uncertainty with both bottom-up and top-down approaches. The bottom-up approach suggests that all possible sources of uncertainty are identified and quantified in an uncertainty budget. A combined uncertainty is calculated using statistical propagation rules. The top-down approach directly estimates the measurement uncertainty results produced by a measuring system. Methods to estimate the imprecision and bias are presented theoretically and in worked examples.

Scope

This guideline explains the concept, estimation, and application of measurement uncertainty in the field of clinical laboratory medicine. The recommendations provided are consistent with the Guide to the expression of uncertainty in measurement (GUM) and with the International Organization for Standardization (ISO) standards concerned with laboratory accreditation. 

This guideline briefly discusses, but does not fully address, the following nonmeasurement sources of uncertainty of a measurement result: 

• Biological variation of the measurand 

• Pre- and postmeasurement processes 

The guideline discusses the definition of what is intended to be measured, lists sources of measurement uncertainty, describes the generation of statistical estimates of uncertainties and their combination, and discusses the use of uncertainty estimates. The guideline applies only to quantitative measurements. In measurement procedures that are reported in qualitative terms based on a quantitative measurement, the uncertainty at the threshold(s) for a qualitative interpretation should be considered when making the qualitative assessment. 

This guideline is intended for clinical laboratories and in vitro diagnostic (IVD) device manufacturers.

Additional Details

This document is available in electronic format only.

This archived document is no longer being reviewed through the CLSI Consensus Document Development Process. However, this document is technically valid and because of its value to the laboratory community, it is being retained in CLSI’s library.

Authors
Anders Kallner, MD, PhD
Stanley F. Lo, PhD, DABCC, FACB
James C. Boyd, MD
Gene Pennello, PhD
David L. Duewer, PhD
David Sogin, PhD
Claude Giroud, PhD
Daniel W. Tholen, MS
Aristides T. Hatjimihail, MD, PhD
Blaza Toman, PhD
George G. Klee, MD, PhD
Graham H. White, PhD