WQC GLOSSARY

Glossary of Terms Definitions of important terms are obtained from documents of professional societies and organizations such as the International Federation of Clinical Chemistry [IFCC], the American Society for Quality [ASQ], and the National Committee for Clinical Laboratory Standards [NCCLS], or, in some cases, are based on the use of these terms in the context of the approach to analytical quality management that is being recommended in these lessons.

• RE. A term that describes a change in random error from the stable imprecision of the method (s_meas). A value of 2.0 indicates a doubling of the original method standard deviation, whereas a value of 1.0 represents the original stable standard deviation. Used in our quality planning models or error budget equations to indicate the increase in random error that can be detected by a control procedure. RE_crit is a special case that represents the increase in random error that needs to be detected to maintain a defined quality requirement.
• SE. A term that describes a change in systematic error in multiples of the standard deviation (s_meas) observed for the method under stable conditions. A value of 2.0 would indicate a systematic shift equivalent to two times s_meas. Used in our quality planning models or error budget equations to indicate the size of systematic error that can be detected by a control procedure. SE_crit is a special case that represents the systematic shift that needs to be detected to maintain a defined quality requirement.
• Accuracy. "Agreement between the best estimate of a quantity and its true value. It has no numerical value. See inaccuracy" [IFCC].
• Allowable total error, TE_a. An analytical quality requirement that sets a limit for both the imprecision and inaccuracy that are tolerable in a single measurement or single test result.
• Analyte. The substance to be measured.
• Analytical error. "Difference between the estimated value of a quantity and its true value. This difference (positive or negative) may be expressed either in the units in which the quantity is measured, or as a percentage of the true value" [IFCC]. Used here to mean the difference between a patient's test result produced by the analytical process and the true or correct value for that sample.
• Analytical quality assurance (AQA). Used with charts of operating specifications (OPSpecs charts) to indicate the level of assurance for detecting critical sized errors. For example, 90% AQA(SE) means there will be at least a 90% chance of detecting the critical systematic error when operating within the allowed limits for imprecision and inaccuracy for the given control rules and total number of control measurements (N).
• Analytical quality requirement. Used here to refer to a quality requirement in the form of an allowable total error (TE_a). Often defined on the basis of proficiency testing criteria for acceptable performance, such as the CLIA requirements for regulated analytes.
• Analytical run. Defined by CLIA as an interval within which the accuracy and precision of a testing system is expected to be stable. Cannot be longer than 24 hours. This definition is based on that given in NCCLS document C24A that defines a run as an interval, period of time, or number of specimen, for which the precision and accuracy of the method is expected to remain stable; between which events may occur that could cause errors that are important to detect.
• Assayed control material. A control solution or control material for which the manufacturer defines the results expected for different tests and different methods. These "bottle values" are summarized on assay sheets and are useful for selecting control materials, however, they should not generally be used for setting the control limits because they values usually include a between-laboratory component of variation that makes the control limits too wide for use in an individual laboratory.
• Bias. A systematic difference between an observed value and some measure of the truth. Generally used to describe the inaccuracy of a method relative to a comparative method in method evaluation or to a comparative group in proficiency testing.
• Bias_meas. Used here to represent the bias of a measurement procedure relative to a comparative method or a comparative group in proficiency testing.
• Clinical quality requirement. Used here for a quality requirement that states the medically important change in a test result or describes the gray zone or decision interval for interpreting a test result.
• Coefficient of variation, CV. The relative standard deviation, i.e., the standard deviation expressed as a percentage of the mean [CV=100(s/x)].
• Control chart. "A graphical method for evaluating whether a process is or is not in a 'state of statistical control.' The determinations are made through comparison of the values of some statistical measure(s) for an ordered series of samples, or subgroups, with control limits" [ASQ]. In healthcare laboratories, the Levey-Jennings chart is commonly used to plot the result observed for a stable control material versus time, usually the day or run number.
• Control limits. "Limits on a control chart which are used as criteria for signalling the need for action, or for judging whether a set of data does or does not indicate a 'state of control'" [ASQ]. Used here to refer to the defined limits or ranges of results expected due to the random error of the method, and beyond which some course of action should be taken. It is common in clinical laboratories to use Levey-Jennings control charts with limits set as either the mean plus or minus 2 standard deviations, or the mean plus or minus 3 standard deviations.
• Control material, control product. A control solution that is available, often commercially, liquid or lyophilized, and packaged in aliquots that can be prepared and used individually.
• Control measurements, control observations. The analytical results obtained for control solutions or control materials (that are analyzed for purposes of quality control).
• Control procedure, QC procedure. The protocol and materials that are necessary for an analyst to assess whether the method is working properly and patient test results can be reported - that part of an analytical process that is concerned with testing the quality of the analytical results, in contrast to the measurement procedure, which produces the result. A control procedure can be described by the number of control measurements and the decision criteria (control rules) used for judging the acceptability of the analytical results.
• Control rule. A decision criterion for interpreting control data and making a judgement on the control status of an analytical run. Symbolized here by A_L, where A is the abbreviation for a particular statistic or states the number of control measurements, and L is the control limit. An analytical run is rejected when the control measurements fulfill the stated conditions, i.e., when a certain statistic or number of control measurements exceeds the specified control limits.
• Criteria for acceptability. CLIA's term for the decision criteria applied to assess the validity of an analytical run. Another name for QC procedure, with emphasis on definition of the decision criteria or control rules for interpreting control measurements.
• Critical-error graph. A power function graph on which is imposed the critical-error that needs to be detected. Facilitates the estimation and comparison of the probability for error detection by different QC procedures.
• Critical random error, RE_crit. The size of random error that causes a 5% maximum defect rate for the analytical process. Calculated as (TE_a- bias_meas)/1.65s_meas, where TE_a is the allowable total error, bias_meas is the inaccuracy, and s_meas is the imprecision (standard deviation) of the measurement procedure.
• Critical systematic error, SE_crit. The size of the systematic error that needs to be detected to maintain a defined quality requirement. Calculated as [(TE_a - bias_meas)/s_meas] - 1.65, where TE_a is the allowable total error, bias_meas is the inaccuracy, and s_meas is the imprecision (standard deviation) of the measurement procedure.
• Cumulative control limits. Control limits calculated from estimates of the mean and standard deviation that represent a time period longer than a month. Common practice is for laboratories to calculate monthly control statistics. Cumulative statistics can be easily calculated from monthly statistics that tabulate the sum of the individual values and the sum of the squares of those values. See the lesson QC - The Calculations for more detailed discussion, equations, and examples.
• Decision Interval, D_int. Used here to represent the gray zone, or interval of uncertainty, in interpreting a test result. An example is the NCEP (National Cholesterol Education Program) guidelines that indicate a cholesterol of less than or equal to 200 mg/dL is okay and that a value of more than or equal to 240 should have followup testing, which defines a gray zone of 40 mg/dL between 200 to 240, which is 20% at a decision level of 200 mg/dL. D_int can also be defined more generally by the change in a test result that is judged to be medically significant.
• Decision level for critical interpretation (X_c). See medical decision level.
• Distribution. Refers to the spread and shape of a frequency curve of some variable. A histogram is one way to graphically display the distribution of test results by showing the frequency of observations on the y-axis versus the magnitude on the x-axis. The normal or gaussian curve is one form of a distribution.
• Error detection. See probability for error detection.
• False rejection. See probability for false rejection.
• Frequency of errors, frequency of occurrence of analytical errors, f. A performance characteristic of a measurement procedure that describes how frequently analytical errors are expected to occur. Related to the stability of the measurement procedure.
• Gaussian curve. Gaussian distribution. Normal curve. Normal distribution. Refers to a symmetrical bell-shaped distribution whose shape is given by a specific equation (called the normal equation) in which the mean and standard deviation are variables. It is commonly assumed that the random error of an analytical method fits the Gaussian distribution and therefore can be characterized by calculating the standard deviation. The standard deviation is not a valid statistic if a distribution is not Gaussian.
• High complexity tests. A CLIA category of tests that has the most demanding QC requirements. Includes any tests developed by the laboratory, modified by the laboratory, or manufacturer's tests that have been classified as high complexity.
• Imprecision. "Standard deviation or coefficient of variation of the results in a set of replicate measurements. The mean value and number of replicates must be stated, and the design used must be described in such a way that other workers can repeat it. This is particularly important whenever a specific term is used to denote a particular type of imprecsion, such as between-laboratory, within-day, or between day" [IFCC]. We use the term smeas to represent a measurement procedure's standard deviation and express it as a percent, or coefficient of variation, on OPSpecs charts.
• Inaccuracy. "Numerical difference between the mean of a set of replicate measurements and the true value. This difference (positive or negative) may be expressed in the units in which the quantity is measured, or as a percentage of the true value" [IFCC]. We use the term biasmeas to describe the average systematic difference between a measurement procedure and a comparative method and express it in percent on OPSpecs charts..
• Inherent imprecision, inherent random error. The standard deviation or coefficient of variation of the results in a set of replicate measurements obtained when the measurement procedure is operating under stable conditions.
• Levey-Jennings control chart. A commonly used control chart in which individual control measurements are plotted directly on a control chart with limit lines drawn either as mean ± 2s or mean ± 3s. Time is displayed on the x-axis usually in terms of days or runs.
• Matrix. Refers to the physical and chemical nature of the specimen, the substances present, and their concentrations. The matrix of a control material is an important consideration in selecting and implementing a QC procedure. In this context, the matrix refers to the substances and base from which the control material is prepared, in addition to all the additives such as spiking materials, preservatives, etc., necessary to make the product useful.
• Mean. The arithmetic average of a set of values. A measure of central tendency of the distribution of a set of replicate results. Often abbreviated by an x with a bar over it.
• Medical decision level, decision level, X_c. A concentration of analyte where medical interpretation is critical for patient care. There may be several different medical decision levels for a particular analyte. X_c should provide guidance for selecting relevant estimates of stable imprecision, stable inaccuracy, and matrix inaccuracy. This is analogous to identifying a critical Target Value (TV) for assessing test performance and validating QC design.
• Medically important errors. Used here to indicate errors that, when added to the inherent imprecision and inaccuracy of a measurement procedure, cause the quality requirement to be exceeded. Medically important random errors are those increases in the standard deviation of the measurement procedure that cause the error distribution to exceed the quality requirement (see critical random errors). Medically important systematic errors are those shifts in the mean of the error distribution that cause the error distribution to exceed the quality requirement (see critical systematic error).
• Method validation. The process of testing a measurement procedure to assess its performance and to validate that performance is acceptable. The magnitudes of the analytical errors are experimentally determined and their acceptability for the application of the method is judged versus defined requirements for quality in the form of maximum allowable errors.
• Model. A mathematical equation that describes the behavior of a process as a function of its important characteristics.
• Moderate complexity tests. A CLIA category of tests that includes about 75% of all tests performed by healthcare laboratories, including most automated analytical systems. This category has more stringent QC requirements than for "waived tests" or "provider performed microscopy."
• Multi-rule quality-control procedure. A control procedure that uses two or more control rules for testing control measurements and determining control status. At least one rule is chosen for its ability to detect random errors and one to detect systematic errors.
• Number of control measurements, N. Used here to indicate the total number of control measurements available for use in assessing the quality of an analytical run. We consider N to be the total number of control measurements available for inspection when using common Levey-Jennings type QC charts or multirule type QC procedures where it is possible to combine the measurements from different materials to accumulate a higher N (and higher error detection) for evaluating control status. These measurements may be replicates on one level or material, individual measurements on two or more materials, or replicate measurements on two or more materials. For example, if you assay a single material and make two measurements on that material, N is 2. If you assay two materials (as required by US CLIA regulations) and make single measurements on each, N is 2. If you assay two materials and make duplicate measurements on each, N is 4. If you assay three materials and make single measurements on each, N is 3. If you assay three materials and make duplicate measurements on each, N is 6. With the use of mean/range or cusum type of QC procedures where it is more difficult to combine the measurements from different control materials, N is more likely to be the number of replicates on an individual material.
• Operating specifications (OPSpecs). Used here to describe the imprecision and inaccuracy that are allowable and the QC that is necessary to assure, at a stated level, that a defined quality requirement will be achieved in routine operation.
• OPSpecs chart. A plot of the inaccuracy (on the y-axis) and the imprecision (on the x-axis) that are allowable for different QC procedures. The chart is prepared for a defined quality requirement and for a stated level of analytical quality assurance (AQA). Readily available in workbook format in the OPSpecs Manual and also easily prepared by the QC Validator computer program.
• Performance characteristics. Those properties that describe how well a procedure performs. For a control procedure, the performance characteristics are the probabilities for error detection and false rejection, or the average run lengths for rejectable and acceptable quality. For a measurement procedure, the performance characteristics include analytical range, precision, accuracy, interference, recovery, and also the frequency and duration of analytical errors.
• Power curve. A line on a power function graph that describes the performance of a certain control rule and N.
• Power-function graph. A graphical presentation of the performance characteristics of QC procedures that describes the probability for rejection (on the y-axis) versus the size of analytical error occurring (on the x-axis) for stated control rules and numbers of control measurements.
• Precision. "The agreement between replicate measurements. It has no numerical value" [IFCC, NCCLS]. See also Imprecision.
• Preventive maintenance. The renewing or refurbishing or critical parts of a method on a regular basis to prevent malfunctions.
• Primary standard material. "Substance of known chemical composition and sufficient purity to be used in preparing a primary standard solution" [IFCC].
• Primary standard solution. "Solution used as calibration standard in which the concentration is determined solely by dissolving a weighed amount of primary standard material in an appropriate solvent, and making a stated volume or weight" [IFCC].
• Probability, p. The likelihood an event will occur, usually stated as a decimal fraction between 0 and 1, 0 meaning that the event will never occur and 1 meaning that the event will always occur. For example, p=0.05 means there is a 5% chance that an event will occur. Commonly used in quality control to describe the chance that a run will be rejected.
• Probability for error detection, P_ed. A performance characteristic of a QC procedure that describes how often an analytical run will be rejected when results contain errors in addition to the inherent imprecision of the measurement procedure. Ideally, P_ed should be 1.00 for errors that are medically significant. In practice, we generally aim for a P_ed of 0.90 when selecting and designing QC procedures.
• Probability for false rejection, P_fr. A performance characteristic of a QC procedure that describes how often an analytical run will be rejected when there are no errors occurring, except for the inherent imprecision of the measurement procedure. Ideally, P_fr should be 0.00. In practice, we generally aim for a P_fr of 0.05 or less.
• Process capability. An industrial term used to describe how the inherent variability of a production process under stable operation compared to the allowable variation. SE_crit is an index of process capability for an analytical testing process.
• Process stability. Used here to characterize the performance of the measurement procedure in terms of the frequency of analytic runs having medically important errors (f) that invalidate the medical usefulness.
• Proficiency testing, PT. Used in the US to describe a program of external quality assessment whereby specimens are submitted to laboratories for their analysis with the purpose of grading the performance of the laboratory.
• Proficiency testing criteria for acceptable performance, PT criteria. Defined limits about a target value (TV) that are used to classify analytical performance as acceptable or not. CLIA defines PT criteria for about 80 regulated analytes, using a format of TV ± a stated %, TV ± a fixed concentration, or TV ± 3 SD, where the SD is usually a group standard deviation from a PT survey. These PT criteria should be interpreted as total error criteria because only single measurements can be made on PT specimens and the test result is subject to both random and systematic errors.
• Provider performed microscopy, PPM. A special subset of moderately complex tests that may be performed by physicians, dentists, nurse practioners and midwives, and physician assistants as part of a patient examination.
• QC acceptability criteria. The term used by CLIA to indicate the decision criteria or control rules used to monitor test performance during a run of patient specimens.
• QC planning process, quality planning process. The steps to be followed to select control rules, N, and a Total QC strategy that are appropriate for the quality needed and the imprecision and inaccuracy observed for a laboratory test.
• Quality planning model. Term used to describe an equation that shows the additive effects of different factors that influence the variation of a test result. The analytical model relates the imprecision and inaccuracy of the measurement procedure and the sensitivity of the control procedure to the total analytical error that is allowable. The clinical model includes the analytical components plus pre-analytical components, such as within-subject biological variation, etc., and relates them to the clinical decision interval or gray zone for interpreting a test result.
• Random error, RE. An error that can be either positive or negative, the direction and exact magnitude of which cannot be exactly predicted. In contrast, systematic errors are always in one direction.
• Run. See analytical run.
• Sample. "The appropriate representative part of a specimen which is used in the analysis." [IFCC]
• Specimen. "Material available for analysis." [IFCC]
• Standard. "Material or solution with which the sample is compared in order to determine the concentration or other quantity. The compound term calibration standard should be used whenever needed to avoid confusion with other technical or colloquial meanings of the word standard." [IFCC]
• Standard deviation, s. A statistic that describes the dispersion or spread of a set of measurements about the mean value of a gaussian or normal distribution. Calculated from the equation:
  
  where n is the number of measurements, and x_i is an individual measurement.
• Standard deviation index, SDI. Generally used in reports from proficiency testing (PT) survey to describe how far a PT result is from the target value (TV). An SDI of +2.0 means that the laboratory's reported result is 2 standard deviations of the group above the target value or mean of the group.
• Statistical quality control. Those aspects of quality control in which statistics are applied, in contrast to the broader scope of quality control which includes many other procedures, such as preventive maintenance, instrument function checks, and performance validation tests. Statistical QC procedures are often used to monitor routine performance of a method and to alert the laboratory when the performance of a method changes.
• Statistical control limits. As used with Levey-Jennings and Westgard multirule types of QC procedures, these are the lines drawn on control charts to define the range of results expected due to the random error of the method. The limits are often obtained from a group of 20 or more measurements on a particular control material by calculating the mean and standard deviation, then using multiples such as the mean plus/minus 3s, 2s, or 1s to establish rejection limits for different control rules.
• Statistical process control. A general term used to describe those aspects of a control system in which statistics are applied to determine whether observed measurements fall within the range expected due to the random variation of the process. Industrial process control procedures provided the basis for introduction of statistical control in healthcare laboratories, however, industrial process control procedures often use the mean and range of a group of control measurements (e.g., Shewhart mean and range charts), whereas healthcare applications tend towards the use individual measurements or individual-value control charts, such as the Levey-Jennings chart.
• Systematic error, SE. An error that is always in one direction and is predictable, in contrast to random errors that may be either positive or negative and whose direction cannot be predicted.
• Test complexity. Refers to the CLIA system of classifying tests into categories on the basis of the difficulty of measurement and interpretation. Categories include waived, provider performed microscopy, moderate complexity, and high complexity.
• Total error, TE. The net or combined effect of random and systematic errors.
• Total error requirement. See allowable total error.
• Total imprecision. The random error observable over a period of many runs and many days.
• Total QC strategy. The balance of the efforts expended on statistical QC, preventive maintenance, instrument function checks, method performance tests, and quality improvement.
• True value. Generally used to indicate that this is the correct analytical concentration or result.
• Variable. A quantity of interest, whose value or magnitude fluctuates or changes.
• Variance. The standard deviation squared. If there are independent sources of errors, the variance of the total error is the sum of the variances due to the individual sources of error.
• Waived tests. A specific category of tests defined by CLIA, such as dipstick tests, fecal occult blood, urine pregnancy tests, erythrocyte sedimentation rates, blood glucose monitoring devices, etc., which are subject to the lowest level of regulation. The main requirement for QC is to follow the manufacturer's directions.
• Westgard rules, Westgard multi-rule control procedure. A control procedure that uses a series of control rules to test the control measurements. A 1_2s rule is used as a warning, followed by use of 1_3s, 2_2s, R_4s, 4_1s, and 10_x as rejection rules.
• Within-run imprecision. The random error observable within the time period of a single analytical run.
• z-score, z-value. A calculated number that tells how many standard deviations a control result is from its mean value, e.g., a control result of 112 on a material having a mean of 100 and a standard deviation of 5 has a z-score of +2.4, i.e., it is 2.4 standard deviations above its mean.