Preanalytical Quality in Clinical Chemistry Laboratory (original) (raw)
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Haemolysis index – an estimate of preanalytical quality in primary health care
Clinical Chemistry and Laboratory Medicine, 2000
Background: Haemolysis is usually caused by inadequate specimen collection or preanalytical handling, and is suggested to be a suitable indicator of preanalytical quality. We investigated the prevalence of detectable haemolysis in all routine venous blood samples to identify differences in preanalytical quality. Methods: Haemolysis index (HI) values were obtained from a Vitros 5,1 in the routine clinical chemistry laboratory for samples collected in primary health care centres (PHCs), nursing homes, and a hospital emergency department (ED). Haemolysis was defined as a HI G15 (detection limit). Results: Samples from the PHC with the highest prevalence of haemolysis were 6.1 times (95% confidence interval (CI) 4.0-9.2) more often haemolysed compared to the centre with the lowest prevalence. Of the samples collected in primary health care, 10.4% were haemolysed compared to 31.1% in the ED (p-0.001). A notable difference in haemolysed samples was found between the ED section staffed by emergency medicine physicians and the section staffed by primary health care physicians (34.8% vs. 11.3%, p-0.001). Conclusions: The significant variation in haemolysis indices among the investigated units is likely to reflect varying preanalytical conditions. The HI is a valuable tool for estimation and follow-up of preanalytical quality in primary health care. Clin Chem Lab Med 2009;47:940-4.
Haemolysis: an overview of the leading cause of unsuitable specimens in clinical laboratories
Clinical Chemistry and Laboratory Medicine, 2008
Prevention of medical errors is a major goal of healthcare, though healthcare workers themselves have not yet fully accepted or implemented reliable models of system error, and neither has the public. While there is widespread perception that most medical errors arise from an inappropriate or delayed clinical management, the issue of laboratory errors is receiving a great deal of attention due to their impact on the quality and efficiency of laboratory performances and patient safety. Haemolytic specimens are a frequent occurrence in clinical laboratories, and prevalence can be as high as 3.3% of all of the routine samples, accounting for up to 40%-70% of all unsuitable specimens identified, nearly five times higher than other causes, such as insufficient, incorrect and clotted samples. This article focuses on this challenging
Evaluation of Types of Pre-Analytical Errors in Clinical Chemistry Laboratory
Journal of Evolution of Medical and Dental Sciences, 2016
Evaluation of leading causes of pre-analytical errors in Clinical Biochemistry Laboratory. MATERIALS AND METHODS Samples were obtained from the OPD and indoor admitted patients and analysis of the results obtained from clinical chemistry laboratory obtained during one year of study period was done retrospectively. Data was summarised regarding the frequency of factors affecting the pre-analytical quality of results. Laboratory personnel were asked to register all the rejected samples and reasons for rejections. RESULTS Out of 62541 inpatient samples collected and screened over period, pre-analytical errors were observed in 4611 samples, which is approximately 3.75% of the total blood samples received. Insufficient volume of samples accounted for rejection of 2428 samples, which is 1.9% of total samples received during this period. Haemolysis accounted for rejection of 1.1% of samples and gross lipaemia was responsible for rejection of 0.4% samples. 0.26% of samples were rejected for having wrong/incomplete patient information. Out of 60244 samples collected total from OPD, 5552 samples were rejected for the presence of pre-analytical errors. This accounted for rejection of 4.5% of total samples received during this period. 2.7% of samples were rejected for the presence of visible haemolysis after centrifugation. Samples rejected for insufficient volume accounted to 1.9%. 0.3% of samples were rejected for having gross lipaemia. 800 samples were rejected for having wrong/incomplete patient information, which accounted for rejection of 0.8%. CONCLUSION The overall rate of rejection of samples is 8.52%, which is very high. Haemolysis was major reason for rejection of samples collected from OPD and error due to insufficient sample volume was found to be equal in both type of samples collected from OPD and indoor patients.
Multicenter evaluation of the hemolysis index in automated clinical chemistry systems
Clinical Chemistry and Laboratory Medicine, 2000
In vitro hemolysis, the prevailing cause of preanalytical error in routine laboratory diagnostics, might influence the reliability of several tests, affect the quality of the total testing process and jeopardize patient safety. Although laboratory instrumentation is now routinely equipped with systems capable of automatically testing and eventually correcting for hemolysis interference, to our knowledge there are no reports that have compared the efficiency of different analytical platforms for identifying and classifying specimens with hemolysis. Methods: Serum from a healthy volunteer was spiked with varying amounts of hemolyzed blood from the same volunteer, providing a serum free hemoglobin concentration ranging from 0.0 g/L to 2.0 g/L as measured by the reference cyanmethemoglobin assay. The spiked serum samples were shipped to seven sepa-*Corresponding author: Prof.
Journal of Laboratory Medicine, 2019
Background Visual inspection is the most widespread method for evaluating sample hemolysis in hemostasis laboratories. The hemolysis index (HI) was determined visually (visual index, VI) and measured on an ACL TOP 750 (IL Werfen) system with a hemolysis-icterus-lipemia index (HIL) module. These values were compared with those measured on clinical chemistry systems Unicel DXC600 and AU680 and with quantitation of free-hemoglobin (Hb) performed by a spectrophotometric measurement method (SMM). Methods The HI was measured in 356 sodium citrate plasma samples, 306 of which were visibly hemolyzed to varying degrees and 50 were not hemolyzed. The analytical performance of each method was evaluated. Results Linear regression analysis, calculated between SMM and the other systems in the study, returned coefficients of determination r2 = 0.853 (AU680), r2 = 0.893 (DXC600) and r2 = 0.917 (ACL TOP 750). An r2 = 0.648 was obtained for linear regression analysis between VI and ACL TOP 750. In ad...
Clinical Chemistry and Laboratory Medicine (CCLM), 2015
Laboratory diagnostics develop through different phases that span from test ordering (pre-preanalytical phase), collection of diagnostic specimens (preanalytical phase), sample analysis (analytical phase), results reporting (postanalytical phase) and interpretation (post-postanalytical phase). Although laboratory medicine seems less vulnerable than other clinical and diagnostic areas, the chance of errors is not negligible and may adversely impact on quality of testing and patient safety. This article, which continues a biennial tradition of collective papers on preanalytical quality improvement, is aimed to provide further contributions for pursuing quality and harmony in the preanalytical phase, and is a synopsis of lectures of the third European Federation of Clinical Chemistry and Laboratory Medicine (EFLM)-Becton Dickinson (BD) European Conference on Preanalytical Phase meeting entitled ‘Preanalytical quality improvement. In pursuit of harmony’ (Porto, 20–21 March 2015). The le...
Biochemia medica, 2019
Introduction: Compared to other activities of the testing process, the preanalytical phase is plagued by a lower degree of standardization, which makes it more vulnerable to errors. With the aim of providing guidelines and recommendations, the EFLM WG-PRE issued a survey across European medical laboratories, to gather information on local preanalytical practices. This is part one of two coherent articles, which covers all practices on monitoring preanalytical quality except haemolysis, icterus and lipemia (HIL). Materials and methods: An online survey, containing 39 questions dealing with a broad spectrum of preanalytical issues, was disseminated to EFLM member countries. The survey included questions on willingness of laboratories to engage in preanalytical issues. Results: Overall, 1405 valid responses were received from 37 countries. 1265 (94%) responders declared to monitor preanalytical errors. Assessment, documentation and further use of this information varied widely among re...