The effect of ratios upon improving patient-based real-time quality control (PBRTQC) performance.

OBJECTIVES: Large biological variation hinders application of patient-based real-time quality control (PBRTQC). The effect of analyte ratios on the ability of PBRTQC to improve error detection was investigated. METHODS: Four single analyte-ratio pairs (alanine aminotransferase [ALT] vs. ALT to aspartate aminotransferase ratio [RALT]; creatinine [Cr] vs. Cr to cystatin C ratio [RCr]; lactate dehydrogenase [LDH] vs. LDH to hydroxybutyrate dehydrogenase ratio [RLDH]; total bilirubin [TB] vs. TB to direct bilirubin ratio [RTB]) were chosen for comparison. Various procedures, including four conventional algorithms (moving average [MA], moving median [MM], exponentially weighted moving average [EWMA] and moving standard deviation [MSD]) were assessed. A new algorithm that monitors the number of defect reports per analytical run (NDR) was also evaluated. RESULTS: When a single analyte and calculated ratio used the same PBRTQC parameters, fewer samples were needed to detect systematic errors (SE) by taking ratios (p<0.05). Application of ratios in MA, MM and EWMA significantly enhanced their ability to detect SE. The influence of ratio on random error (RE) detection depended upon the analytes and PBRTQC parameters, as consistent advantage was not demonstrated. The NDR method performed well when appropriate parameters were used, but was only effective for unilateral SE. Rearrangement of sample order led to a significant deterioration of conventional algorithms' performance, while NDR remained almost unaffected. CONCLUSIONS: For analytes with large variation and poor PBRTQC performance, using ratios as PBRTQC indexes may significantly improve performance and achieve better anti-interference ability, providing a new class of monitoring indicators for PBRTQC.

Comparison and optimization of various moving patient-based real-time quality control procedures for serum sodium.

BACKGROUND: Patient-based real-time quality control (PBRTQC) is a valuable tool for monitoring the performance of testing processes. We aimed to compare and optimize various PBRTQC procedures for serum sodium. METHODS: In a computer simulation, artificial errors were added to 680,000 real patients' results. The characteristics of error detection of various algorithms-moving average, moving median, moving SD and moving proportion of normal results including different control limits (CLs)-were assessed on their ability to detect critical errors early. RESULTS: The moving average and moving median were sensitive to system error, and the moving SD tended to detect random error. P3SD (moving proportion of normal results, CLs based on mean and SD of proportion of normal results) demonstrated excellent performance for both system error and random error. The increase of block sizes (N) leads to the delay of error detection and the decrease of false rejection, except for QC procedures with minimum and maximum as CLs. CLs calculation with "0.1% false alarm rate" had more effective performance than that set false alarm to zero (minimum and maximum as CLs). The impact of truncation on QC performance depended on truncation limits, algorithms and the types of error. The significant improvement in QC performance due to truncation was only found in moving SD. CONCLUSION: "P3SD ,N = 50, without truncation" and "moving SD, N = 25, set 0.1% false alarm as CLs and set 1% outliers exclusion as truncation limits" were recommended as the optimized procedures for serum sodium to monitor system error and random error, respectively.

Digital Filtering Techniques for Performance Improvement of Golay Coded TDM-FBG Sensor.

For almost a half-decade, the unique autocorrelation properties of Golay complementary pairs (GCP) have added a significant value to the key performance of conventional time-domain multiplexed fiber Bragg grating sensors (TDM-FBGs). However, the employment of the unipolar form of Golay coded TDM-FBG has suffered from several performance flaws, such as limited improvement of the signal-to-noise ratio (SNIR), noisy backgrounds, and distorted signals. Therefore, we propose and experimentally implement several digital filtering techniques to mitigate such limitations. Moving averages (MA), Savitzky-Golay (SG), and moving median (MM) filters were deployed to process the signals from two low reflectance FBG sensors located after around 16 km of fiber. The first part of the experiment discussed the sole deployment of Golay codes from 4 bits to 256 bits in the TDM-FBG sensor. As a result, the total SNIR of around 8.8 dB was experimentally confirmed for the longest 256-bit code. Furthermore, the individual deployment of MA, MM, and SG filters within the mentioned decoded sequences secured a further significant increase in SNIR of around 4, 3.5, and 3 dB, respectively. Thus, the deployment of the filtering technique alone resulted in at least four times faster measurement time (equivalent to 3 dB SNIR). Overall, the experimental analysis confirmed that MM outperformed the other two techniques in better signal shape, fastest signal transition time, comparable SNIR, and capability to maintain high spatial resolution.

Impact of combining data from multiple instruments on performance of patient-based real-time quality control.

INTRODUCTION: It is unclear what is the best strategy for applying patient-based real-time quality control (PBRTQC) algorithm in the presence of multiple instruments. This simulation study compared the error detection capability of applying PBRTQC algorithms for instruments individually and in combination using serum sodium as an example. MATERIALS AND METHODS: Four sets of random serum sodium measurements were generated with differing means and standard deviations to represent four simulated instruments. Moving median with winsorization was selected as the PBRTQC algorithm. The PBRTQC parameters (block size and control limits) were optimized and applied to the four simulated laboratory data sets individually and in combination. RESULTS: When the PBRTQC algorithm were individually optimized and applied to the data of the individual simulated instruments, it was able to detect bias several folds faster than when they were combined. Similarly, the individually applied algorithms had perfect error detection rates across different magnitudes of bias, whereas the error detection rates of the algorithm applied on the combined data missed smaller biases. The performance of the individually applied PBRTQC algorithm performed more consistently among the simulated instruments compared to when the data were combined. DISCUSSION: While combining data from different instruments can increase the data stream and hence, increase the speed of error detection, it may widen the control limits and compromising the probability of error detection. The presence of multiple instruments in the data stream may dilute the effect of the error when it only affects a selected instrument.

Recommendation for performance verification of patient-based real-time quality control.

Patient-based real-time quality control (PBRTQC) is a laboratory tool for monitoring the performance of the testing process. It includes well-established procedures like Bull's algorithm, average of nomals, moving median, moving average (MA) and exponentially (weighted) MAs. Following the setup and optimization processes, a key step prior to the routine implementation of PBRTQC is the verification and documentation of the performance of the PBRTQC as part of the laboratory quality system. This verification process should provide a realistic representation of the performance of the PBRTQC in the environment it is being implemented in, to allow proper risk assessment by laboratory practitioners. This document focuses on the recommendation on performance verification of PBRTQC prior to implementation.

Monitoring laboratory data across manufacturers and laboratories--A prerequisite to make "Big Data" work.

BACKGROUND: "The Percentiler" project provides quasi real-time access to patient medians across laboratories and manufacturers. This data can serve as "clearinghouse" for electronic health record applications, e.g., use of laboratory data for global health-care research. METHODS: Participants send their daily outpatient medians to the Percentiler application. After 6 to 8weeks, the laboratory receives its login information, which gives access to the user interface. Data is assessed by peer group, i.e., 10 or more laboratories using the same test system. Participation is free of charge. RESULTS: Participation is global with, to date, >120 laboratories and >250 instruments. Up to now, several reports have been produced that address i) the general features of the project, ii) peer group observations; iii) synergisms between "The Percentiler" and dedicated external quality assessment surveys. Reasons for long-term instability and bias (calibration- or lot-effects) have been observed for the individual laboratory and manufacturers. CONCLUSIONS: "The Percentiler" project has the potential to build a continuous, global evidence base on in vitro diagnostic test comparability and stability. As such, it may be beneficial for all stakeholders and, in particular, the patient. The medical laboratory is empowered for contributing to the development, implementation, and management of global health-care policies.

Changing the paradigm of laboratory quality control through implementation of real-time test results monitoring: For patients by patients.

OBJECTIVES: To develop and implement a quality control protocol using real-time patient data with immediate failure analysis and prevention of releasing results that exceed the allowable total error. DESIGN AND METHODS: Patient data are analyzed in real time using algorithms that incorporate moving medians and moving means for selected chemistry analytes. Simulation software was developed to determine optimal algorithms, establish error limits, and number of patient results for calculation of a single cumulative datum point. Algorithms for moving median (MovMed) and mean (MovMen) were chosen and validated for each analyte. Error limits (TEa) were established using biological and analytical variation with a goal of greater than 90% error detection rate during simulation runs. Middleware software was developed to prohibit the release of patient results upon error detection. RESULTS: A block size of 50 was determined to be the optimal number of patient results used in cumulative calculations. The application of MovMed and MovMen algorithms achieved 0% false rejection for 24 out of 28 tests (85.7%) during the simulation phase. Four tests had a false rejection rate ranging from 0.2 to 1.0%. Error detection rates of 100% were achieved for 16 out of 28 tests (57.1%). Twelve tests had error detection rates ranging from 94.5 to 99.8%. Traditional QC material utilization was reduced by approximately 75-85% and repeat analysis was reduced by approximately 50%. CONCLUSIONS: We successfully developed and implemented a real-time quality control protocol using patient results with true error detection and without release of erroneous results.