Moving average quality control of routine chemistry and hematology parameters - a toolbox for implementation

Time-of-day dependence of running averages for some components of metabolic panels at our hospital: Relation to strategy for patient-based quality control

BACKGROUND AND OBJECTIVES

We assessed properties of running averages for our hospital's most common chemistry analytes, for use in real-time patient-based quality control (PBQC). We determined whether there was dependence of any running averages on 24-h clock time (time-of-day, TOD).

MATERIALS AND METHODS

We analyzed 3-months' data for measurements of 13 metabolic panel components. Running averages for 20 consecutive results (20-mers) were computed for data restricted to results within reference intervals. This produced an overall mean (X) and standard-deviation (SD) of 20-mers for each analyte. We then computed the average 20-mer result (Y) reported within 1-h bins across 24-hour clock time (t). Y(t) was regarded as having TOD-dependence if either nadir or apex values for |Y-X| exceeded 0.5 SD, occurring within a contiguous series of at least 4 Y(t) values on one side of the mean.

RESULTS

Seven analytes (albumin, aspartate aminotransferase, calcium, chloride, CO2, potassium, total protein) demonstrated TOD-dependence of running means for 20-mers.

CONCLUSIONS

At our hospital, TOD-dependence of running means was identified for 7 of 13 metabolic panel analytes. TOD-dependence is likely to be hospital-specific. Utilization of TOD-dependent targets for PBQC, rather than fixed targets, would be appropriate in these cases.

Development and Evaluation of "The Delta Plus-Minus Even Distribution Check": A Novel Patient-Based Real-Time Quality Control Method for Laboratory Tests

BACKGROUND

Laboratory testing of large sample numbers necessitates high-volume rapid processing, and these test results require immediate validation and a high level of quality assurance. Therefore, real-time quality control including delta checking is an important issue. Delta checking is a process of identifying errors in individual patient results by reviewing differences from previous results of the same patient (Δ value). Under stable analytical conditions, Δ values are equally positively and negatively distributed.

METHODS

The previous 20 Δ values from 3 tests (cholesterol, albumin, and urea nitrogen) were analyzed by calculating the R-value: "the positive Δ value ratio minus 0.5." This method of monitoring optimized R-values is referred to as the even-check method (ECM) and was compared with quality control (QC) testing in terms of error detection.

RESULTS

Bias was observed on 4 of the 120 days for the 3 analytes measured. When QC detected errors, the ECM captured the same systematic errors and more rapidly. In contrast, the ECM did not generate an alarm for the one random error that occurred in QC. While QC did not detect any errors, the percentage of R-values exceeding the acceptable range was under 2%, the number of days generating alarms was between 16 and 21 days, with short alarm periods, and a median number of samples per alarm period between 7 and 9 samples.

CONCLUSIONS

The ECM is a practical real-time QC method, controlled by setting R-value conditions, that quickly detects bias values.

Advances in internal quality control

Quality control practices in the modern laboratory are the result of significant advances over the many years of the profession. Major advance in conventional internal quality control has undergone a philosophical shift from a focus solely on the statistical assessment of the probability of error identification to more recent thinking on the capability of the measurement procedure (e.g. sigma metrics), and most recently, the risk of harm to the patient (the probability of patient results being affected by an error or the number of patient results with unacceptable analytical quality). Nonetheless, conventional internal quality control strategies still face significant limitations, such as the lack of (proven) commutability of the material with patient samples, the frequency of episodic testing, and the impact of operational and financial costs, that cannot be overcome by statistical advances. In contrast, patient-based quality control has seen significant developments including algorithms that improve the detection of specific errors, parameter optimization approaches, systematic validation protocols, and advanced algorithms that require very low numbers of patient results while retaining sensitive error detection. Patient-based quality control will continue to improve with the development of new algorithms that reduce biological noise and improve analytical error detection. Patient-based quality control provides continuous and commutable information about the measurement procedure that cannot be easily replicated by conventional internal quality control. Most importantly, the use of patient-based quality control helps laboratories to improve their appreciation of the clinical impact of the laboratory results produced, bringing them closer to the patients.Laboratories are encouraged to implement patient-based quality control processes to overcome the limitations of conventional internal quality control practices. Regulatory changes to recognize the capability of patient-based quality approaches, as well as laboratory informatics advances, are required for this tool to be adopted more widely.

Rules for mass spectrometry applications in the clinical laboratory

MS-based analytical methods now play an important role in medical laboratory analysis. Predominantly triple-stage mass spectrometry is used for the quantification of small molecule biomarkers and xenobiotics in blood and urine. The spectrum of applications ranges from completely in-house developed analytical methods, to industrially manufactured kit solutions used on generic equipment, to the first closed MS-based analysis systems. It is to be expected that the weights will shift in the coming years. Thus, operation and evaluation for most applications will remain very challenging and very different from the far more user-friendly and fully automated systems - mainly photometry-based - which are commonly used in clinical laboratories. General regulatory requirements for medical analysis differ significantly between countries globally. General requirements for in-house developed assay methods are valid in some countries, but concrete and methodology-specific rules for operation and quantification when using MS methods in the medical diagnostic laboratory are not applied. This differs significantly from other bio-analytical areas such as food monitoring, pharmaceutical research, or forensics, where legally binding, detailed rules exist in some cases, e.g., for substance identification. Internationally used relevant and helpful general standards with regard to mass spectrometric examination procedures in the clinical laboratory are in particular CLSI 62A and ISO 15189, while the IVDR in the EU primarily regulates the manufacture of diagnostic articles and not their application. In addition, from many years of application experience, some general advice can be recommended as rules that can contribute to robustness and patient safety in the clinical application of MS procedures; with emphasis on: reasonable method description, batch release, competence management, maintenance, and continuity management. This article also proposes some procedural basic requirements for the application of MS procedures in the clinical laboratory.

Lot-to-lot variation and verification

Lot-to-lot verification is an integral component for monitoring the long-term stability of a measurement procedure. The practice is challenged by the resource requirements as well as uncertainty surrounding experimental design and statistical analysis that is optimal for individual laboratories, although guidance is becoming increasingly available. Collaborative verification efforts as well as application of patient-based monitoring are likely to further improve identification of any differences in performance in a relatively timely manner. Appropriate follow up actions of failed lot-to-lot verification is required and must balance potential disruptions to clinical services provided by the laboratory. Manufacturers need to increase transparency surrounding release criteria and work closer with laboratory professionals to ensure acceptable reagent lots are released to end users. A tripartite collaboration between regulatory bodies, manufacturers, and laboratory medicine professional bodies is key to developing a balanced system where regulatory, manufacturing, and clinical requirements of laboratory testing are met, to minimize differences between reagent lots and ensure patient safety. Clinical Chemistry and Laboratory Medicine has served as a fertile platform for advancing the discussion and practice of lot-to-lot verification in the past 60 years and will continue to be an advocate of this important topic for many more years to come.