Termination of Repeat Testing in Chemical Laboratories Based on Practice Guidelines: Examining the Effect of Rule-Based Repeat Testing in a Transplantation Center

Abstract

Background. Although the automation of instruments has reduced the variability of results and errors of analysis, in some laboratories, repeating a test to confirm its accuracy is still performed for critical and noncritical results. However, the importance of repeat testing is not well established yet, and there are no clear criteria for repeating a test. Materials and Methods. In this cross-sectional study, all repeated tests for 26 biochemical analytes (i.e., albumin, alkaline phosphatase (ALP), alanine aminotransferase (ALT), amylase, aspartate aminotransferase (AST), bilirubin total (BT), bilirubin direct (BD), blood urea nitrogen (BUN), calcium, chloride (Cl), cholesterol total (CholT), creatine kinase (CK), creatinine (Cr), glucose, gamma-glutamyl transferase (GGT), high-density lipoprotein-cholesterol (HDL-c), iron, lactate dehydrogenase (LDH), LDL-c, lipase, magnesium (Mg), phosphorus (Ph), protein total (ProtT), total iron binding capacity (TIBC), triglyceride (TG), and uric acid) were assessed in both critical and noncritical ranges over two consecutive months (routine subjective test repeats in the first month and rule-based repeats in the second month). To determine the usefulness of test repeats, differences between the initial and verified results were compared with the allowable bias, and repeat testing was considered necessary if it exceeded the allowable bias range. All causes of repeat testing, including linearity flags, delta checks, clinically significant values, and critical values, were also documented. All data, including the cause of repeats, initial and verified results, time, and costs in the two consecutive months, were transferred to Microsoft Excel for analysis. For comparison of data between the months, Student’s t-test was used. Results. A total of 7714 repeat tests were performed over two consecutive months. Although a significant decline (38%) was found in repeated tests in the second month ( P < 0.001), there was no significant change in the percentage of unnecessary repeats (77% in the first month and 74% in the second month). In both consecutive months, AST and ALT were the most commonly repeated tests, and delta check was the most common cause of repeat testing. Mg, ALP, AST, and lipase showed the highest rates of necessary repeats, respectively (the least stable tests), while albumin, LDL, and CholT tests showed the highest rates of unnecessary repeats, respectively (the most stable tests). The total cost and delay in turnaround time (TAT) due to repeated testing decreased by 32% and 36%, respectively. Conclusion. Although repeat testing has been shown to be unnecessary in most cases, having a strict policy for repeat testing appears to be more valuable than avoiding it completely. Each laboratory is advised to establish its own protocol for repeat testing based on its own practice.

Reducing the need for repeating urine drug testing with the gray zone determined by the measurement uncertainty

“…The logic of the retest rules is that the repeat test result can correct an analytical error that is revealed by the first test. However, with technological progress, analytical errors are becoming less and less common [20] [21] . If the performance of the analyzers has been checked beforehand, repeat testing to verify their accuracy increases laboratory costs [22] [20] .…”

“…In this study, only 211 tests needed to be repeated instead of 754. Each laboratory is advised to create its own protocol for repeat testing based on its own practice, significantly reducing cost [21] .…”

Comparison of Point-of-Care and Highly Sensitive Laboratory Troponin Testing in Patients Suspicious of Acute Myocardial Infarction and Its Efficacy in Clinical Outcome

“…At this time, none of these processes has been proven to be the primary cause of troponin increase and/or myocardial injury in COVID-19 patients [ 13 ]. The causes of false-positive troponin results, including heterophilic antibodies, human antianimal antibodies, autoantibodies, fibrin, rheumatoid factor, endogenous blood products, such as bilirubin, hemoglobin, and lipidemia, and analytical equipment errors, which are observed in immunoassays, were not identified in the studied cases [ 15 ].…”

Hiding in Plain Sight: The Issue of Hidden Variables

“…Thus, several journals now have elaborate checklists for ensuring that replicates be clearly defined in terms of being technical vis-à-vis biological, that the definition of “biological” be confirmed, that correct statistical tests be applied, etc. Although the application of such rigor can be a drain on time and resources, − these considerations lead to a simple, objective set of standards to attain: all data must be repeated a certain number of times, and an appropriate statistical test must show differences (or not as the case may be) at an appropriate confidence level. There is elbow room: it is possible to stack the odds in favor of the intended outcome, and the rigor of the statistical test/data handling can also be varied .…”