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

Assessment of hematology laboratory performance in the total testing process using quality indicators and sigma metrics in the northwest of Ethiopia: A cross-sectional study

Background and Aims

Assuring laboratory quality by minimizing the magnitude of errors is essential. Therefore, this study aimed to assess hematology laboratory performance in the total testing process using quality indicators and sigma metrics.

Methods

A cross-sectional study was conducted from April to June 2022. The study included a total of 13,546 samples. Data on included variables were collected using a checklist. Descriptive statistics were used to present the overall distribution of errors. Binary logistic regression models were applied. Furthermore, using a Sigma scale, the percentage of errors was converted to defects per million opportunities to assess laboratory performance. Finally, the defect per million opportunities was converted to a sigma value using a sigma calculator.

Results

Of the 13,546 samples and corresponding requests, the overall error rate was 123,296/474,234 (26%): 93,412/47,234 (19.7%) pre-analytical, 2364/474,234 (0.5%) analytical, and 27,520/474,234 (5.8%) post-analytical. Of the overall errors, 93,412/123,296 (75.8%), 2364/123,296 (1.9%), and 27,520/123,296 (22.3%) were pre-analytical, analytical, and post-analytical errors, respectively. The overall sigma value of the laboratory was 2.2. The sigma values of the pre-analytical, analytical, and post-analytical phases were 2.4, 4.1, and 3.1, respectively. The sample from the inpatient department and collected without adherence to the standard operating procedures (SOPs) had a significantly higher (p < 0.05) rejection rate as compared to the outpatient department and collected with adherence to SOPs, respectively. In addition, an association between prolonged turnaround times and manual recording, inpatient departments, and morning work shifts was observed.

Conclusion

The current study found that the overall performance of the laboratory was very poor (less than three sigma). Therefore, the hospital leadership should change the manual system of ordering tests and release of results to a computerized system and give need-based training for all professionals involved in hematology laboratory sample collection and processing.

Preanalytical Errors in Clinical Biochemistry Laboratory and Relationship With Hospital Departments and Staff: A Record-Based Study

OBJECTIVE

Despite many efforts to improve the overall quality of clinical laboratory service, errors that compromise patient safety and increase healthcare costs continue to occur even infrequently. We aimed to determine the causes of preanalytical errors and related factors by evaluating the laboratory records of a tertiary hospital.

METHODS

In this retrospective study, 7,762,981 requests that were registered in the biochemistry laboratory records of Ondokuz Mayıs University Health Practice and Research Center during 2019 were examined. All rejected samples were analyzed according to the department where they were collected and the reasons for rejection.

RESULTS

Of the total sample rejections, 99,561 (74.8%) were preanalytical and 33,474 (25.2%) belonged to the analytical phase. The preanalytical rejection rate was 1.28%, with the highest rejection rate in the inpatients (2.26%) and the lowest in the outpatients (0.02%). Insufficient sample (43.7%), clotted sample (35.1%), and inappropriate sample (11.1%) were the first 3 rows of rejection reasons. It was determined that sample rejection rates were low during routine working hours and high during nonworking hours.

CONCLUSIONS

Preanalytical errors were most common in inpatient wards and were most likely due to incorrect phlebotomy techniques. Education of health personnel on good laboratory practices, systematic monitoring of errors, and the development of quality indicators will play an important role in reducing the vulnerability of the preanalytical phase.

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.

An Overview of Complete Blood Count Sample Rejection Rates in a Clinical Hematology Laboratory Due to Various Preanalytical Errors

Introduction The Chughtai Laboratory collects blood samples for complete blood counts from various hospitals, emergency departments, ICUs, and through home sampling services all across the country. The preanalytical phase is an integral component of laboratory medicine. A laboratory report has a key role in patient treatment and the clinician's decision in the management of the disease. Preanalytical errors are most frequently caused by the absence of a sample and/or inappropriate understanding of a test request, mislabeling, contamination from the sampling site, hemolyzed, clotted, insufficient samples, storage issues, and inappropriate blood to anticoagulant proportion or inappropriate choice of anticoagulant. Objective To identify the cause of rejection rates of the complete blood count samples and reduce the rejection rates by improving the accuracy of the results and lowering pre-analytical errors. Methods This cross-sectional study was done in the Hematology Department of Chughtai Laboratory's head office in Lahore between 19-06-2021 and 19-10-2021. Simple random sampling was applied to collect the data. About 3 ml of each blood sample was received in an ethylenediaminetetraacetic acid (EDTA) vial, inspected visually, run on Sysmex XN-9000 (Sysmex Corporation, Kobe, Hyogo, Japan), and was reviewed on peripheral smears. Results Out of 231,008 blood samples, 11,897 (5.15%) samples were rejected. The most common pre-analytical mistake was storage issues due to transportation delay (19.45%) followed by wrong medical records (19.16%), diluted samples (16.35%), incorrect tubes (16.01%), hemolyzed samples (15.13%), unlabeled samples (10.01%), and clotted sample (3.88%). Conclusion In the hematology department, the total rejection rate observed during the study period was 5.15%. Recognition of preanalytical errors and avoiding them will help us lower the sample rejection rate and raise the overall quality of laboratory management.

Hematology and coagulation preanalytics for clinical chemists: Factors intrinsic to the sample and extrinsic to the patient

In hematology and coagulation, diligence in the preanalytical phase of testing is of critical importance to obtaining reliable test results. If the sample used for testing is unsuitable, even outstanding analytical procedures and technology cannot produce a clinically-reliable result. Therefore, the intent of this manuscript is to review preanalytical factors intrinsic to the sample that affect the hematology and coagulation testing. Factors intrinsic to the sample (excluding in vivo anomalies) can be controlled, theoretically, by phlebotomists (including nurses) and laboratorians in the preanalytical phase of testing. Furthermore, the management and prevention of such factors is highlighted. Erroneous control of preanalytical factors can produce laboratory 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.

Challenges in Preanalytical Phase of Laboratory Medicine: Rate of Blood Sample Nonconformity in a Tertiary Care Hospital

OBJECTIVE

To evaluate the major causes of preanalytical errors in medical laboratory of a tertiary care hospital.

METHODS

It was a retrospective study in which we analyzed the sample rejection data of hematology and chemical pathology sections from January to December 2018. Number of rejected samples, reason for rejection and type of test ordered on monthly basis were recorded on a platform.

RESULTS

A total of 113,817 samples were received during the study period. Preanalytical errors were found in 1,688 samples, which constitute approximately 1.48% of the total number of samples received.

CONCLUSION

Our study highlights the magnitude of preanalytical errors in our setup. Preanalytical errors can lead to loss of patient trust in diagnostic services, can dent the laboratory's reputation, and lead to an increase in the overall operating expenses, both for laboratories as well as the hospitals. Compliance with good laboratory practices can significantly reduce the frequency of pre analytical errors.

Reduction of pre-analytical errors in the clinical laboratory at the University Hospital of Korea through quality improvement activities

BACKGROUND

The clinical laboratory is responsible for reporting accurate and expeditious results. However, the pre-analytical phase is directly related to the procedure of specimen collection and is mostly out of the direct control of the laboratory; further, most pre-analytical errors are related to human factors. Therefore, education and training programs for the phlebotomy teams are considered the most significant and necessary measures to reduce these errors.

METHODS

A cross-sectional study was conducted to investigate the types and frequencies of pre-analytical errors in the hospital laboratory. Pre-analytical errors were categorized into four main categories: rejected sample, error related to test ordering, misidentification, and others. Several activities were performed for quality improvement in order to reduce the rates of these errors. The data were analyzed by comparing the pre-intervention and post-intervention results along with the results of questionnaires to assess knowledge to investigate the effects of the activities.

RESULTS

The rates of pre-analytical errors decreased from 0.42% in the pre-intervention period to 0.32% in the post-intervention period. The rejected sample category accounted for the highest rates in the pre- and post-intervention periods. In the questionnaires, the overall average score after the intervention was 71.5, which was a significant increase from 46.0 in the pre-intervention period.

CONCLUSIONS

Each clinical laboratory has various types of pre-analytical errors due to the complexity of the healthcare environment. Therefore, targeted intervention including a quality improvement program and its continuous maintenance should be conducted to reduce pre-analytical errors and to improve patient safety.