Errors in comprehensive testing regime of a clinical biochemistry research facility

INTRODUCTION

A comprehensive testing regime in a biochemistry research facility is composed of three aspects: Analytical, pre-analytical, and post-analytical. The fallacy in these parts can lead to wrong outcomes and, hence, compromise the management of the sick. A high-standard laboratory facility means precise, accurate, and timely delivery of outcome. This requires following a standard practice at all steps.^[1,2] Quality indicators (QIs)/Quality index (QI) are used to quantify laboratory performance.^[3-5] Automation has reduced analytical error by tenfold. While pre-analytical and post-analytical mistakes happen due to physicians, staff nurses, and phlebotomists, they can still be controlled.^[6,7]

MATERIAL AND METHODS

RESULTS

Out of 22320 samples observed during the period of study, the total number of fallacies was 132, out of which 99 were in the pre-testing stage, 11 in the assay-related stage, and 22 in the post-analytical stage.

The varied types of fallacies and their prevalence observed during the study period are given in Tables 1-4.

DISCUSSION

The present study used QIs to find the rejection rates/fallacies in the clinical research facility.^[8-10] The accuracy of reports is essential to prevent incorrect interpretation or management of the patients. Hence, the standard protocol of performance should be followed and kept under vigilance using the quality indicators.^[11,12]

The Sigma concept can be used to describe flaw rates. Sigma (σ) is a Greek alphabet letter. The performance of a process is at its best when functioning at a sigma score of 6.^[13] The 6 Sigma means no more than 3.4 defects per million opportunities. The sigma scale runs from 0 to 6 [Table 5].

Hemolysis (QI-10) was found to be the most frequent pre-analytical flaw, resulting in 22.7% (30 out of 132) of the total error rates, and similar results were reported by Vishwanath et al.^[4] and Bhutani et al.^[8] In vitro hemolysis results in the release of contents of hemolyzed red blood cells into plasma, causing inaccurate outcomes.^[1] Few parameters, such as lactate dehydrogenase, potassium, and aspartate transaminase are overestimated in a hemolyzed sample whereas other parameters, such as alkaline phosphatase, albumin, gamma-glutamyl-transferase, chloride, glucose, sodium, are underestimated. Various causes for hemolysis are when venipuncture site is not allowed to dry appropriately (at least 30 s) after cleaning the site with alcohol, using fine needle syringes, shaking the vacutainers vigorously, and centrifuging the sample before completion of clotting.^[7,9] Any phlebotomist, nurse, or doctor should know the proper technique of phlebotomy to prevent hemolysis. Laboratory personnel must ask for new specimens when hemolysis is detected.^[14]

The second common flaw seen was inadequate sample (QI-12), accounting for 17.4% (23 out of 132) sample rejection which is similar to the reports found in studies done by Vishwanath et al.^[4] and Sushma and Shrikant.^[7] A specified amount of serum/plasma is required for each analytical process. These tubes are marked to collect a fixed volume of blood so as to obtain the correct blood-to-additive ratio. Inaccurate results may occur because of an inappropriate blood-to-additive ratio. The main reasons behind this error are complications in sampling in patients having thin veins, chronic diseases, pediatric cases, and the phlebotomist not reading the test requisition form properly about the number of examinations requested in the requisition form.^[15]

Inadequately labeled samples (QI-15) contributed 13.6% (18/132) of rejection rates. Patient recognition is the most important step in sample processing. Mislabeled, unlabeled, or incompletely labeled specimens results in wrong patient management. This can occur in an environment of heavy workload where thousands of specimens are handled in a similar way.^[14]

Lipemic samples resulted in 7.5% of rejections. Lipemic samples arise due to post-meal sampling and a patient suffering from hyperlipoproteinemia. This can be corrected by an overnight fasting sample. In case a patient is diagnosed with hyprlipoproteinemias, it is the responsibility of the doctor to intimate it to the research facility.^[8,16]

Other errors were the damaged sample tube (5.3%) during transportation or centrifugating without proper balancing, inappropriate temperature condition/sample not on the ice (3.8%), usually when relatives of the patients were sent from wards to laboratories for delivering the samples in the absence of laboratory attendants, sample drawn from the IV area (3.8%) usually by new untrained interns and nurses and missing samples (1%) which could be due to excessive workload (large number of patients) or sampling done by untrained workforce.

Analytical errors^[17] were 8.3% of total rejection rates. These were due to equipment failure (2.2%), calibration out (2.2%), Quality control (QC) out of range (1.5%), and non-linear results released without retesting (1.5%).

TAT (QI-21) was exceeded in total of 9 samples (6.8%). Protesting and sample handling mistakes may lead to performance redundancies and loss of precious time hence resulting in prolonged TAT. Automated robotic workstations in the pre-testing phase helps to prevent the human error during sorting and labeling of samples. Repeating critical outcomes is not recommended unless delta check fails.^[8]

4.5% errors due to 6 reports with critical values being not conveyed immediately to the physician (QI-22). The total testing process is not merely the generation of the reports but is actively involved in conveying critical outcomes to clinicians so that management can be initiated at the earliest.

Transcriptional errors constituted 3.8% of fallacies (calculation mistakes for lipids and globulin fractions). These are due to the erroneous entry of the outcomes that may be eliminated by research facility information system, use of barcodes as well as digitalization. 1.5% of rejection rates were contributed due to reporting with wrong units (cerebrospinal fluid protein in g/dL led to rejection twice).

The sigma metric is more meaningful than the number of defects alone in the evaluation of laboratory fallacies. It is possible to assess the quality of research facility testing processes.^[18]

Attainment of Six Sigma performance represents 3.4 defects per million opportunities (DPMO) and the achievement of 3 sigma values is the minimum acceptable quality for a process to be applied.^[19]

All the three phases of analysis have the sigma score of 5 [Table 6]. The highest performance sigma score is 6.

CONCLUSION

The scaling down of these fallacies can be attained by carrying out repeated trainings and education programs. This can be accompanied by annual proficiency and competency assessments. Easily understandable policies can be formulated. Standard operating procedures can be implemented for phlebotomy, which includes proper method for specimen collection, universal precautions to be taken for disposal of syringes, needles, and other materials.