Influence of method of specimen collection on various preanalytical sample quality indicators in EDTA blood collected for cell counting

Preanalytical Errors in a Hematology Laboratory: An Experience from a Tertiary Care Center

BACKGROUND

Laboratory errors arise at any stage of testing. Detecting these inaccuracies before results are revealed might delay diagnosis and treatment, causing patient distress. Here, we studied the preanalytical errors in a hematology laboratory.

METHODS

This one-year retrospective analysis was conducted at the laboratory of a tertiary care hospital and included information on blood samples that were taken for hematology tests from both outpatients and inpatients. Laboratory records included sample collection and rejection information. The type and frequency of preanalytical errors were expressed as a proportion of total errors and sample number. Microsoft Excel was utilized to enter data. The results were presented in the form of frequency tables.

RESULTS

This research included 67,892 hematology samples. For preanalytical errors, 886 samples (1.3%) were discarded. The most common preanalytical error was insufficient sample (54.17%), and the least common was an empty/damaged tube (0.4%). Erroneous samples in the emergency department were mostly insufficient and clotted, whereas pediatric sample errors were caused by insufficient and diluted samples.

CONCLUSION

Inadequate samples and clotted samples account for the vast majority of preanalytical factors. Insufficiency and dilutional errors were most frequent from pediatric patients. Adherence to best laboratory practices can drastically cut down on preanalytical errors.

Prevalence and types of preanalytical error in hematology laboratory of a tertiary care hospital in South India

BACKGROUND

An important component of laboratory medicine is preanalytical phase. Since laboratory report plays a major role in patient management, more importance should be given to the quality of laboratory tests.

AIM

The present study was undertaken to find the prevalence and types of preanalytical errors at a tertiary care hospital in South India.

MATERIALS AND METHODS

In this cross-sectional study, a total of 118,732 samples ([62,474 outpatient department [OPD] and 56,258 inpatient department [IPD]) were received in hematology laboratory. These samples were analyzed for preanalytical errors such as misidentification, incorrect vials, inadequate samples, clotted samples, diluted samples, and hemolyzed samples.

RESULTS

The overall prevalence of preanalytical errors found was 513 samples, which is 0.43% of the total number of samples received. The most common preanalytical error observed was inadequate samples followed by clotted samples. Overall frequencies (both OPD and IPD) of preanalytical errors such as misidentification, incorrect vials, inadequate samples, clotted samples, diluted samples, and hemolyzed samples were 0.02%, 0.05%, 0.2%, 0.12%, 0.02%, and 0.03%, respectively.

CONCLUSION

The present study concluded that incorrect phlebotomy techniques due to lack of awareness is the main reason for preanalytical errors. This can be avoided by proper communication and coordination between laboratory and wards, proper training and continuing medical education programs for laboratory and paramedical staffs, and knowledge of the intervening factors that can influence laboratory results.

Estaciones automatizadas preanalíticas en el laboratorio de hemostasia. Estudio observacional descriptivo prospectivo, realizado en un hospital universitario de referencia entre el 15 de abril y 15 de julio de 2017

Introducción: los errores del proceso de análisis de las muestras del laboratorio clínico, impactan negativamente a la práctica médica, la seguridad del paciente e incrementan los costos de atención en la salud. El uso de estaciones automatizadas demostró una disminución de los errores en los laboratorios clínicos de inmunoquímica y hematología. Se propone comparar las primeras estaciones automatizadas de hemostasia con el método manual para determinar los interferentes en las muestras de cinco servicios del hospital durante tres meses.Métodos: estudio observacional descriptivo prospectivo de corte trasversal. Las muestras que ingresaron al laboratorio clínico fueron analizadas por la estación automatizada y el método manual. Las interferentes bilirrubinas, hemoglobina, lipemia, volumen de llenado del tubo y obstrucción fluídica-coágulo se estudiaron con ambos métodos. Se realizó el análisis estadístico y se calculó el índice kappa para determinar la fuerza de la concordancia entre los métodos.Resultados: de 8.970 muestras analizadas, 29 % provinieron del servicio de urgencias. Las muestras aportadas por la unidad de cuidado intensivo reportaron más interferentes con ambos métodos; la estación automatizada reportó más interferentes que el método manual, con un índice kappa 0,52; la bilirrubina fue el interferente más detectado por ambos métodos. El método manual no evidenció el interferente volumen de llenado del tubo ni obstrucción fluídica-coágulo, los cuales fueron detectados por la estación automatizada.Conclusiones: la estación automatizada detectó más interferentes en comparación con el método manual. Los interferentes son errores preanalíticos en el laboratorio de hemostasia y son detectados con poca frecuencia de forma visual, especialmente los interferentes volúmenes de llenado del tubo y obstrucción fluídica-coágulo.

The economic impact of poor sample quality in clinical chemistry laboratories: results from a global survey

Background Despite advances in clinical chemistry testing, poor blood sample quality continues to impact laboratory operations and the quality of results. While previous studies have identified the preanalytical causes of lower sample quality, few studies have examined the economic impact of poor sample quality on the laboratory. Specifically, the costs associated with workarounds related to fibrin and gel contaminants remain largely unexplored. Methods A quantitative survey of clinical chemistry laboratory stakeholders across 10 international regions, including countries in North America, Europe and Oceania, was conducted to examine current blood sample testing practices, sample quality issues and practices to remediate poor sample quality. Survey data were used to estimate costs incurred by laboratories to mitigate sample quality issues. Results Responses from 164 participants were included in the analysis, which was focused on three specific issues: fibrin strands, fibrin masses and gel globules. Fibrin strands were the most commonly reported issue, with an overall incidence rate of ∼3%. Further, 65% of respondents indicated that these issues contribute to analyzer probe clogging, and the majority of laboratories had visual inspection and manual remediation practices in place to address fibrin- and gel-related quality problems (55% and 70%, respectively). Probe maintenance/replacement, visual inspection and manual remediation were estimated to carry significant costs for the laboratories surveyed. Annual cost associated with lower sample quality and remediation related to fibrin and/or gel globules for an average US laboratory was estimated to be $100,247. Conclusions Measures to improve blood sample quality present an important step towards improved laboratory operations.

Preanalytical Errors in Hematology Laboratory- an Avoidable Incompetence

BACKGROUND

Quality assurance in the hematology laboratory is a must to ensure laboratory users of reliable test results with high degree of precision and accuracy. Even after so many advances in hematology laboratory practice, pre-analytical errors remain a challenge for practicing pathologists. This study was undertaken with an objective to evaluate the types and frequency of preanalytical errors in hematology laboratory of our center.

METHODS

All the samples received in the Hematology Laboratory of Dayanand Medical College and Hospital, Ludhiana, India over a period of one year (July 2013-July 2014) were included in the study and preanalytical variables like clotted samples, quantity not sufficient, wrong sample, without label, wrong label were studied.

RESULTS

Of 471,006 samples received in the laboratory, preanalytical errors, as per the above mentioned categories was found in 1802 samples. The most common error was clotted samples (1332 samples, 0.28% of the total samples) followed by quantity not sufficient (328 sample, 0.06%), wrong sample (96 samples, 0.02%), without label (24 samples, 0.005%) and wrong label (22 samples, 0.005%).

CONCLUSION

Preanalytical errors are frequent in laboratories and can be corrected by regular analysis of the variables involved. Rectification can be done by regular education of the staff.

Types and frequency of preanalytical errors in haematology lab

AIM

This study was conducted to evaluate the frequency of the preanalytical errors occurring in a haematology laboratory.

MATERIAL AND METHODS

A retrospective study was conducted by collecting and analyzing data in duration of one year in the haematology section of the laboratory. Data for all the preanalytical variables according to the predefined categories were scanned. Both IPD and OPD patients were segregated.

RESULT

A total of 135808 samples were received in haematology lab during this period, out of which in 1339 samples, preanalytical errors were found, which approximately constituted 1 % of all samples.

CONCLUSION

Highest number of samples were rejected due to misidentification, that is 0.35 % and least number were rejected due to dilution of the samples, that is 0.04 %.