Preanalytical Phase Errors: Experience of a Central Laboratory

Preanalytical Errors in Hematology: Insights From a Tertiary Care Hospital

Introduction Errors occur in the laboratory at any level of the testing process. Recognizing these errors may cause patient distress by delaying diagnosis and management until results are released. This study aims to assess preanalytical errors in the laboratory and suggests methods to prevent them to improve accuracy and efficiency in the hematology department of a tertiary care hospital. The background emphasizes the critical role of preanalytical procedures in ensuring accurate hematological diagnoses and highlights the frequent mistakes that occur during specimen collection, handling, and transportation. Staff training, process standardization, using suitable collecting and transport equipment, putting quality control measures in place, and using automation technologies are some strategies for reducing errors and speeding up turnaround times. To increase diagnostic accuracy, patient care outcomes, and laboratory efficiency, hematology laboratories should address preanalytical mistakes and employ fostering methods. Aims and objectives The objective of this research is to evaluate the frequency and characteristics of preanalytical errors within the hematology laboratory of a tertiary care hospital. The study seeks to gauge the scope of the problem, identify key factors contributing to these errors, such as issues in specimen collection, handling, and transportation, and highlight areas where improvements can be made. Also, it intends to assess how preanalytical errors affect hematological accuracy and turnaround times, with a focus on patient care outcomes, and recommend techniques to reduce preanalytical errors and improve the accuracy of hematological results.  Materials and methods This study was conducted at the hematology laboratory of our hospital from January 2023 to June 2024 after getting proper approval from the Institutional Review Board (IRB approval number 294/08/2024/PG/SRB/SMCH). It is a retrospective analytical study, and the study population comprised samples of patients from the emergency, inpatient, and outpatient departments, which included 51,155 complete blood count (CBC) and 5,449 peripheral smear (PS) samples. The study included only test samples sent specifically for hematological analysis, while those sent for cytological, biochemical, or microbiological testing were excluded. The distribution frequency of the samples and the number of rejected samples were analyzed, and the results were then compared and correlated. Results During the study period, a total of 56,604 samples were processed in the hematology laboratory. Of these, 886 samples (1.3%) were rejected due to preanalytical errors. The most frequent error was submitting an insufficient sample (54.17%), while the least frequent was the use of an empty or defective tube (0.4%). In the emergency department, the primary issues were insufficient and clotted samples, while in pediatric cases, errors were mainly due to inadequate or diluted samples. Conclusion Preanalytical errors in hematology laboratories, though often overlooked, can significantly impact diagnostic accuracy and patient care. Our study highlights that a substantial portion of errors arise from inadequate sample collection and handling, particularly in emergency and pediatric cases. Adherence to standard laboratory techniques can dramatically reduce preanalytical errors.

The rise in preanalytical errors during COVID-19 pandemic

Introduction

The COVID-19 pandemic has posed several challenges to clinical laboratories across the globe. Amidst the outbreak, errors occurring in the preanalytical phase of sample collection, transport and processing, can further lead to undesirable clinical consequences. Thus, this study was designed with the following objectives: (i) to determine and compare the blood specimen rejection rate of a clinical laboratory and (ii) to characterise and compare the types of preanalytical errors between the pre-pandemic and the pandemic phases.

Materials and methods

This retrospective study was carried out in a trauma-care hospital, presently converted to COVID-19 care centre. Data was collected from (i) pre-pandemic phase: 1^st October 2019 to 23^rd March 2020 and (ii) pandemic phase: 24^th March to 31^st October 2020. Blood specimen rejection rate was calculated as the proportion of blood collection tubes with preanalytical errors out of the total number received, expressed as percentage.

Results

Total of 107,716 blood specimens were screened of which 43,396 (40.3%) were received during the pandemic. The blood specimen rejection rate during the pandemic was significantly higher than the pre-pandemic phase (3.0% versus 1.1%; P < 0.001). Clotted samples were the commonest source of preanalytical errors in both phases. There was a significant increase in the improperly labelled samples (P < 0.001) and samples with insufficient volume (P < 0.001), whereas, a significant decline in samples with inadequate sample-anticoagulant ratio and haemolysed samples (P < 0.001).

Conclusion

In the ongoing pandemic, preanalytical errors and resultant blood specimen rejection rate in the clinical laboratory have significantly increased due to changed logistics. The study highlights the need for corrective steps at various levels to reduce preanalytical errors in order to optimise patient care and resource utilisation.

Error Evaluation in the Laboratory Testing Process and Laboratory Information Systems

Introduction: The laboratory testing process consists of five analysis phases featuring the total testing process framework. Activities in laboratory process, including those of testing, are error-prone and affect the use of laboratory information systems. This study seeks to identify error factors related to system use and the first and last phases of the laboratory testing process using a proposed framework known as total testing process-laboratory information systems. Materials and Methods: We conducted a qualitative case study in two private hospitals and a medical laboratory. We collected data using interviews, observations, and document analysis methods involving physicians, nurses, an information technology officer, and the laboratory staff. We employed the proposed framework and Lean problem-solving tools namely Value Stream Mapping and A3 for data analysis. Results: Errors in laboratory information systems and the laboratory testing process were attributed to failure to fulfill user requirements, poor cooperation between the information technology unit and laboratory, the inconsistency of software design in system integration, errors during inter-system data transmission, and lack of motivation in system use. The error factors are related to system development elements, namely, latent failures that considerably affected the information quality and system use. Errors in system development were also attributed to poor service quality. Conclusion: Complex laboratory testing process and laboratory information systems require rigorous evaluation in minimizing errors and ensuring patient safety. The proposed framework and Lean approach are applicable for evaluating the laboratory testing process and laboratory information systems in a rigorous, comprehensive, and structured manner.