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GBZ43280-2023: Medical laboratories - Practical guidance for the estimation of measurement uncertainty
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Basic data | Standard ID | GB/Z 43280-2023 (GB/Z43280-2023) | | Description (Translated English) | Medical laboratories - Practical guidance for the estimation of measurement uncertainty | | Sector / Industry | National Standard | | Classification of Chinese Standard | C30 | | Classification of International Standard | 11.100 | | Word Count Estimation | 66,690 | | Date of Issue | 2023-11-27 | | Date of Implementation | 2024-06-01 | | Issuing agency(ies) | State Administration for Market Regulation, China National Standardization Administration | GBZ43280-2023: Medical laboratories - Practical guidance for the estimation of measurement uncertainty
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GB /Z 43280-2023: Guidelines for the evaluation of measurement uncertainty in medical laboratories
ICS 11:100
CCSC30
National Standardization Guiding Technical Documents of the People's Republic of China
Guidelines for Evaluating Uncertainty of Measurement in Medical Laboratories
Medicallaboratories-
(ISO /T S20914:2019,IDT)
Published on 2023-11-27
2024-06-01 Implementation
State Administration for Market Regulation
Released by the National Standardization Administration Committee
Table of contents
Preface III
Introduction IV
1 Scope 1
2 Normative references 1
3 Terms and Definitions 1
4 symbols 10
5 Measurement uncertainty for use in medical laboratories10
5:1 Concept of measurement uncertainty10
5:2 Maximum allowable measurement uncertainty12
5:3 Sources of measurement uncertainty12
5:4 Expression of measurement uncertainty13
5:5 Calculating Uncertainty Estimates Using Relative Standard Uncertainty 15
5:6 Reporting measurement uncertainty15
6 Uncertainty evaluation steps of measured values 15
6:1 Definition of measurand 15
6:2 Measurement precision16
6:3 The impact of changes in batch numbers of reagents and indoor quality control materials on uncertainty assessment17
6:4 The laboratory uses multiple measurement systems for the same measured object17
6:5 Uncertainty of end-user calibration values (ucal) 18
6:6 Measurement bias18
6:7 Overview of the evaluation process of measurement uncertainty18
6:8 Re-evaluation of measurement uncertainty19
6:9 Qualitative results based on numerical values 19
6:10 Uncertainty in entity counting19
6:11 Limitations of measurement uncertainty assessment values 20
Appendix A (Informative) Examples of Evaluating Measurement Uncertainty 21
A:1 Introduction 21
A:2 Basic calculations 22
A:3 Measurement uncertainty including measurement uncertainty when measurement conditions change27
A:4 Combined average standard uncertainty of several identical measurement systems at different IQC averages29
A:5 Calculation of uncertainty in the anion gap using internal quality control data30
A:6 Uncertainty assessment of glomerular filtration rate results31
A:7 Expanded uncertainty assessment of white blood cell counts in whole blood 34
A:8 Evaluate the uncertainty of the amount and concentration of serum/plasma albumin substances---use relative uncertainty and standard uncertainty
Degree comparison 36
A:9 Calculation of %Urel 39 of the International Normalized Ratio
A:10 Uncertainty in Human Immunodeficiency Virus Type 1 Viral Load Measurement 41
A:11 Uncertainty of measuring BCR-ABL1 using the same batch of indoor quality control materials 42
A:12 Uncertainty in measurement of rubella virus IgG antibodies43
A:13 Uncertainty in Hepatitis B Surface Antigen Measurement 44
A:14 Uncertainty of manual method for detecting the concentration of red blood cells and the total number of white blood cells in urine 46
Appendix B (informative) Examples of application of measurement uncertainty to interpretation of results 48
Appendix C (informative) Supplementary information on some aspects of uncertainty50
C:1 GUM and measurement uncertainty for medical laboratories50
C:2 Practical approach to measurement uncertainty in medical laboratories50
C:3 Measured quantity 50
C:4 Uncertainty in end-user calibration assignments (ucal) 51
C:5 Evaluation of bias correction uncertainty (ubias) 52
C:6 Example of bias correction (ubias) 54
C:7 Example of direct calculation of relative uncertainty assessment57
Reference 59
Foreword
This document complies with the provisions of GB/T 1:1-2020 "Standardization Work Guidelines Part 1: Structure and Drafting Rules of Standardization Documents"
Drafting:
This document is equivalent to ISO /T S20914:2019 "Guidelines for the Evaluation of Uncertainty in Measurement in Medical Laboratories": The file type is determined by ISO :
The technical specifications were adjusted into my country's national standardization guiding technical documents:
Please note that some content in this document may be subject to patents: The publisher of this document assumes no responsibility for identifying patents:
This document is proposed by the National Medical Products Administration:
This document is under the jurisdiction of the National Standardization Technical Committee for Medical Clinical Laboratory and In Vitro Diagnostic Systems (SAC/TC136):
This document was drafted by: National Health Commission Clinical Laboratory Center, China Institute of Metrology, Beijing Hospital, China National Institute of Conformity Assessment
National Accreditation Center, Beijing Institute of Medical Device Inspection (Beijing Medical Biological Protection Equipment Inspection and Research Center), Beijing Jinyu Medical Inspection
Laboratory Co:, Ltd:, Second Xiangya Hospital of Central South University, Sysmex Medical Electronics (Shanghai) Co:, Ltd:, Beckman Coulter Trading (China)
Ltd:
The main drafters of this document: Peng Mingting, Wu Liqing, Chen Wenxiang, Hu Dongmei, Zou Yingshu, Chen Baorong, Hu Min, Li Qin, Lou Pingping, Maya Ting,
Dai Leiying:
Introduction
In a global economy where patients and healthcare professionals are increasingly mobile within and between healthcare delivery systems, global healthcare
Improvements in standardization and consistency of academic laboratory practices would benefit society: To help achieve the goals of medical laboratory standardization improvement,
ISO 15189 focuses on the application of quality system methods in medical laboratories: Since the publication of ISO 15189:2003, as a recommendation
Medical laboratory quality system standards (sometimes mandatory) have been increasingly adopted globally:
To ensure that measurement results are useful and reliable in medical practice and to be able to limit medical decisions to similar results previously measured for the same individual
To make meaningful comparisons, medical laboratories need to estimate the overall variability in reported results from measurement procedures: For this purpose, ISO 15189:2012
Requirement 5:5:1:4 in "(Medical laboratories) shall evaluate the measurement accuracy of each measurement procedure used to report measured quantities of patient samples in the test:"
Certainty”: Furthermore, “on request, laboratories shall provide to their users an estimate of the uncertainty of measurement”:
For medical laboratories and medical personnel, estimates of measurement uncertainty (MU):
---Indicates that multiple results may be obtained for a given measurement;
---Prove that the term "the 'true value' of a quantity" is a theoretical concept;
--- Quantified the quality of the results to determine their applicability in medical decision-making;
---Assume that known medically significant biases are eliminated;
--- Helps identify technical steps to reduce MU;
---Allows synthesis with uncertainty from other sources;
---Used to determine whether medically acceptable analytical performance specifications can be achieved;
---Support interpretation of patient results near medical decision limits:
In order to be able to meet the requirements of ISO 15189 for measurement uncertainty assessment, it is necessary to provide techniques for medical laboratories to evaluate MU:
Provide consistent, standardized best practices using language, principles, and statistical methods: JCGM100:2008 "Measurement Data Evaluation Measurement Inaccuracy"
The Guide to the Expression of Qualitative Measurements (GUM) is the authoritative reference document on measurement uncertainty, providing in-depth mathematical and metrological information for
It is used to conduct a detailed evaluation of the factors to be considered when evaluating the measurement uncertainty of a measurement system, covering many fields such as science and engineering:
Subject: GUM states in the scope section (1:2) that “This document is intended primarily for the measurement uncertainty of physical quantities that are well defined by unique values:
express: "GUM also states in the scope section (1:4), "GUM provides general principles for the evaluation and expression of measurement uncertainty, rather than detailed
specific technical instructions: GUM does not discuss how the uncertainty of a particular measurement result can be used for different purposes after being evaluated:
for example, to conclude whether the result is compatible with other similar results, to determine the tolerance limits of a manufacturing process, or to decide whether it can be safely
Take some measures all over the world: Therefore, it is necessary to develop special standards based on GUM to solve problems or instructions unique to certain measurement fields:
Various ways of quantifying uncertainty: These standards may be simplified versions of the GUM, but should include
Details of accuracy and complexity: "
This document therefore deals with methods for the assessment of measurement uncertainty in results obtained from measuring procedures in medical laboratories which are expected to
Used to measure various biological species: These measurands usually exist in complex biological fluids and tissue matrices, and the measured results provide medical
Provide medical diagnostic information to service personnel: In contemporary medical laboratories, the vast majority of measurements are performed using commercial equipment, including automated
Chemical instruments and packaged test kits: Characterization of the performance of these measurement procedures in end-user laboratories is usually limited to the use
Collect empirical performance data using surrogate quality control samples that simulate intended patient samples: These data are often referred to as indoor quality control
(IQC) data describing the repeatability and long-term imprecision of a given measurement procedure: For a given measurement procedure, the manufacturer should provide more
Information about the uncertainty of high-level elements in the calibration chain and which should be taken into account by medical laboratories in the assessment of measurement uncertainty
Inside: Therefore, the GUM top-down method is suitable: See Chapter 6 for specific application examples of this method in medical laboratories:
Guidelines for Evaluating Uncertainty of Measurement in Medical Laboratories
1 Scope
This document provides guidance on the evaluation and expression of measurement uncertainty (MU) for quantitative results in medical laboratories and is also applicable to point-of-care testing:
Evaluation of quantitative results obtained by (POCT) systems that are close to medical determination limits: This document also applies to qualitative methods that include measurement steps
Evaluation of the measurement uncertainty of the (named) results obtained: In daily testing, it is not recommended to compare the measurement uncertainty assessment results with patient testing:
Results are reported together but should be made available upon request:
Note: See Appendix B for application examples of measurement uncertainty:
2 Normative reference documents
This document has no normative references:
3 Terms and definitions
The following terms and definitions apply to this document:
Standardized terminology database maintained by ISO and IEC at the following address:
---ISO online browsing platform: https://www:iso:org/obp;
3:1
analyteanalyte
The component represented in the name of the measurand:
Example: In the measurand (measurement quantity) of "24h urine total protein mass", "total protein" is the analyte ("mass" is the characteristic): In "Plasma Glucose Substances"
In "quantity concentration", "glucose" is the analyte ("quantity concentration of substance" is the characteristic):
Note 1: Sample components with measurable properties:
Note 2: 5:4 in JCGM200:2012 states that “the primary measurement standard is processed by dissolving a known amount of a chemical component in a known volume of solution:”
[Source: GB/T 29791:1-2013, 3:3, with modifications]
3:2
Calibration
A set of operations under specified conditions, the first step of which is to determine the quantity provided by a measuring standard (calibrator) with an associated measurement uncertainty
The relationship between the value and the corresponding indication value: The second step is to use this relationship to determine the measurement result based on the indication value (unknown sample):
Note 1: Calibration is expressed in the form of text description, calibration function, calibration diagram, calibration curve or calibration table: In some cases, the inclusion of data with associated measurements does not
Additive or multiplicative correction of the indication value of the degree of certainty:
Note 2: It is more appropriate that calibration should not be confused with the adjustment of the measurement system (often erroneously called "self-calibration"), nor with calibration verification:
Note 3: Usually, only the first step in the above definition is considered calibration:
[Source: JCGM200:2012,2:39, modified]
3:3
calibrator
Measurement standards used for calibration:
Note 1: In this document, calibrator and calibration substance are synonymous:
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