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Gap Analysis Tool CLSI’s new Gap Analysis Tool can help personnel quickly and easily assess whether their laboratory is in compliance with QMS requirements and can track progress toward achieving complete compliance.
Method Navigator CLSI’s new Method Navigator subscription pulls together specific guidance from CLSI documents that will help laboratories fulfill FDA, CLIA, ISO, and other requirements, quickly and easily. Learn to identify, understand, and meet requirements and gain guidance to help document your efforts. Applicable to any test developer, including manufacturers, laboratories, research labs, and manufacturers of medical devices for humans.
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Meeting regulatory requirements
Guidance This Way Identify, understand, and meet regulatory requirements with CLSI’s new resource, Method Navigator.
Implementation Guides Our new Implementation Guides are intended for laboratory scientists to learn how to use CLSI’s Evaluation Protocol Standards. Customers can properly implement our EP standards ensuring quality test results, regulatory requirement readiness, and preparedness for accreditation.
Improving Participation
User Verification of Precision Implementation Guide
Implementation Guide EP15-Ed3-IG1
A New Way to Vote and Comment This year we introduced a new voting and commenting platform for volunteers. This new system allows users to make edits directly within the document and collaborate to vote on documents, streamlining the development process and speeding up the voting and commenting process for volunteers.
Evaluation of Detection Capability Implementation Guide Implementation Guide EP17-Ed2-IG
User Verification of Bias (Trueness) Implementation Guide Implementation Guide EP15-Ed3-IG2
Introduction This implementation guide describes the minimum procedures necessary for a medical laboratory to verify a manufacturer’s or laboratory-developed test’s precision claims. For additional information on verifying precision, see CLSI document EP15. 1 NOTE: The study described in this implementation guide for verifying precision can also be used to estimate bias (trueness). See CLSI document EP15-Ed3-IG2. 2 IMPORTANT NOTE: The study described in CLSI document EP15 1 is not intended for use by a test developer to establish precision for a new commercial or laboratory-developed test. Instead, test developers should use CLSI document EP05 3 for guidance on establishing or validating precision. Laboratories and commercial manufacturers are collectively referred to as “developers” in this implementation guide. Accuracy: A Combination of Precision and Bias It is important that measurement procedures provide accurate results. In order to do so, they must both be precise and have low bias as shown in the figure below.
Introduction This implementation guide describes the minimum procedures necessary for a medical laboratory to verify that a measurement procedure’s detection capability is consistent with the claims established by the developer. Detection capability includes (as shown in the figure below): • Upper boundary on blank sample measurements (ie, limit of blank [LoB]) • “Yes/no” detection of measurand presence (ie, limit of detection [LoD]) • Minimum amount of measurand that can be quantitated reliably with respect to a defined accuracy goal (ie, limit of quantitation [LoQ]) These values are especially critical to detecting extremely small amounts of a measurand. It is always the case that LoB < LoD ≤ LoQ. Knowledge of the detection capability helps determine the lower limit of the measuring interval, which is the lowest measurand concentration at which all defined performance characteristics of the measurement procedure are met (eg, acceptable bias, imprecision, linearity). Each measurement procedure also has an upper limit of quantitation, but determining this value is not within the scope of CLSI document EP17. 1
Introduction This implementation guide describes the minimum procedures necessary for a medical laboratory to estimate bias (trueness) of a laboratory measurement procedure. For additional information on estimating bias, see CLSI document EP15. 1 NOTE: The study described in this implementation guide uses the data and statistics generated from the precision study described in CLSI document EP15. 1 The instructions provided in CLSI document EP15-Ed3-IG1 2 should be used for running the precision study. IMPORTANT NOTE: The study described in CLSI document EP15 1 is not intended for use by a test developer to establish or validate bias claims for a new commercial or laboratory-developed test. Instead, test developers should use CLSI document EP09 3 for guidance on establishing bias claims. Laboratories and commercial manufacturers are collectively referred to as “developers” in this implementation guide. Accuracy: A Combination of Precision and Bias It is important that measurement procedures provide accurate results. In order to do so, they must both be precise and have low bias as shown in the figure below.
Risk Management Techniques to Identify and Control Laboratory Error Sources Implementation Guide Implementation Guide EP18-Ed2-IG
Evaluation of Total Analytical Error for Quantitative Medical Laboratory Measurement Procedures Implementation Guide
EP21-Ed2-IG
Introduction This implementation guide describes the minimum procedures necessary for a medical laboratory to determine total analytical error (TAE) for quantitative measurement procedures. For additional information on evaluating TAE, see CLSI document EP21. 1 Several terms and abbreviations used in this implementation guide—and other CLSI documents—deserve careful attention and understanding because of their similarity and the way in which they are represented in other sources. They include: • Total analytical error (TAE): a measured and calculated quantity that includes errors associated with the examination (analytical) phase of testing. • Allowable total error (ATE): an error goal set by the laboratory. In other publications, ATE might be abbreviated as TEa (ie, total error allowable). • Total error (TE): includes errors from preexamination, examination, and postexamination sources. NOTE: Laboratories and commercial manufacturers are collectively referred to as “developers” in this implementation guide. What Is Total Analytical Error? TAE is an estimate of error in the results for patient samples, including imprecision, bias, nonlinearity, interferences, matrix differences, and other sources of analytical testing error. TAE can be measured over the entire analytical measuring interval (AMI) or at specific subintervals. The TAE calculation is compared with user-selected limits based on clinical need. Knowledge of the TAE is important when the laboratory is deciding whether differences in results for a patient are meaningful, as well as in answering the questions “How accurate are these results?” or “Does the measurement procedure meet clinical performance needs?” Accuracy: A Combination of Precision, Bias, and Other Sources of Error It is important that measurement procedures provide accurate results. In order to do so, they must both be precise and have low bias as shown in the figure below. Less bias, more precise
Introduction This implementation guide describes the minimum procedures necessary for a medical laboratory to identify and control laboratory error sources using risk management techniques. These instructions focus on the failure modes and effects analysis (FMEA) technique. Other options are included in CLSI documents EP18 1 and EP23™. 2 IMPORTANT NOTE: This implementation guide is not intended for use by a test developer to determine error sources for a new commercial or laboratory-developed test. Instead, test developers should use CLSI document EP18 1 for guidance on determining error sources. Laboratories and commercial manufacturers are collectively referred to as “developers” in this implementation guide. Overview of the Risk Management Process Diagnostic devices are extremely diverse in their technology, design, and function. Every test system is subject to hazards or hazardous situations during the preexamination, examination, and postexamination testing stages. The relative importance and likelihood of these failures vary with the device, the sample, the user, and the environment. In addition, a high level of variability exists in terms of skill and knowledge level among end users. The number of potential and observed failures can be large, making it important to prioritize efforts to reduce risk. Some failures are almost certain to cause patient harm, whereas a result that must be repeated but is not time sensitive only raises cost. With the classification of severity of harm and probability (or frequency) of occurrence, the importance of failures can be prioritized. The risk management process can help identify possible failures, their severity, and the likelihood they will occur. With this information, their importance can be prioritized, and measures to reduce the risk can be implemented. The risk management process asks the following questions: ULoQ N
Concentration
0
Reportable Interval
Analytical Measuring Interval
Less bias, more precise
More bias, more precise
Less bias, less precise
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LoQ
While CLSI document EP15 1 contains instructions for studying both precision and bias, this implementation guide focuses only on precision. CLSI document EP15-Ed3-IG2 2 focuses on bias.
Abbreviations: LoB, limit of blank; LoD, limit of detection; LoQ, limit of quantitation; ULoQ, upper limit of quantitation.
More bias, more precise
Less bias, less precise
NOTE: For additional information, see CLSI document EP17. 1 IMPORTANT NOTE: The study outlined in this implementation guide is not intended for use by a test developer to establish or validate detection capability for a new commercial or laboratory-developed test. Instead, test developers should use CLSI document EP17 1 for guidance on establishing or validating detection capability. Laboratories and commercial manufacturers are collectively referred to as “developers” in this implementation guide.
New Online Courses High precision (low coefficient of variation expressed as a percentage [% CV]) means that when a sample is run repeatedly, the results are very close to each other. Precision can be broken into various components. When the precision of a single run is considered, it is called “within-run precision.” “Repeatability” is measured when all components are held essentially the same (single run, operator, lot, calibration, etc.). “Reproducibility” is measured when all components are varied (multiple runs, days, operators, lots, etc.).
While CLSI document EP15 1 contains instructions for studying both precision and bias, this implementation guide focuses only on bias. CLSI document EP15-Ed3-IG1 2 focuses on precision. Having low or no bias means that when a sample is run, its results are very close to the true value (actual concentration or activity) for the sample.
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