Introduction

A diagnostic medical laboratory providing accurate and timely results is crucial for optimal patient management as 70% of clinical diagnosis is established through support of investigation results. (1) Among the three phases comprising a lab workflow namely, pre-analytical, analytical, and post-analytical phases, pre-analytical phase is the most crucial as it contributes to bulk of the laboratory results errors (46%-70%). (2) Pre analytical phase is the seismic area as errors in this phase are not under the direct control of the laboratory. (3)

Quality assurance is now a global norm in healthcare to maintain standards of an organization including laboratories. Quality indicators (QIs) are a fundamental tool for quality laboratory services that can be measured to assess each step of the total testing process. (4-6) Sample rejection is the most important quality indicator in the preanalytical phase, with many global regulatory bodies mandating tracking sample rejection rates to maintain laboratory standards. (1,7-8) A few common causes of rejection are - errors in requesting test (e.g-incomplete form), misidentification of patient or sample, improper sample collection leading to clotted and hemolyzed samples, improper handling and transportation. Not only do the rejected specimens lead to inconvenience and discomfort of repeated specimen collection coupled with added usage of manpower and resources but also come with an accompanying delay in reporting results leading to delayed clinical care, especially when parameters are critical. (1-2,8-9)

Our laboratory is the only one in the district to be accredited by National Accreditation Board for testing and Calibration of Laboratories (NABL). Monitoring our practices is a mandate not only for continued accreditation but also because we cater to a large population. As a part of an internal quality improvement this study was an initiative to analyze main causes of blood sample rejections and identify lacunas in phlebotomy technique at all areas of collection. Additionally, training is a very important integral component to maintain quality in a diagnostic laboratory. Many regulatory and accreditation bodies mandate continual training as part of Total Quality Management. Training can be either formal or informal. Formal training involves specific hours of either online/ classroom/ bedside training sessions which are prescheduled. Informal training is usually through the more experienced peer group and can be on as and when basis, without any fixed schedule. While both have their own advantages and disadvantages, informally done targeted training is ideal to close the skill gap of both existing and new employees.

Materials and Methods:

The study was a prospective analytical cross-sectional study conducted in a central diagnostic laboratory of a tertiary care medical institute. The study duration was from January 2023 to March 2024. Objectives were to estimate the sample rejection rates with risk stratification of rejection by area of collection, to determine reasons of rejection and in addition analyze impact of targeted training on blood sample rejection rates.

Methodology: Blood samples collected from inpatients and outpatients for clinical biochemistry and hematology tests were monitored for rejections and recorded with relevant details. For each rejected specimen, the following information was recorded: patient details, specimen type, laboratory testing section, rejection reason and place of sample collection. The study was divided into three phases as shown in Fig 1.

Fig.1: Phases of the study

In Phase I, rejection rates were monitored without any targeted training. In phase II, nursing staff and phlebotomists were given targeted training i.e. training at intervals on best phlebotomy practices and standardized methods of sample transport. The focus was mainly on areas of high rejections based on results of Phase I. In phase III, targeted training was discontinued to determine the effect of the same, but routine pre scheduled formal training sessions continued. An evaluation of efficacy of educational training interventions was performed by comparing overall specimen rejection rates and patterns across phases. The trend was observed for sample rejections before and after intervention over a period of nine months. Ethics committee clearance for the study was obtained from the Institutional Ethics Committee (IEC) vide letter - CDSIMER/MR/0068/IEC/2022 dated 22.05.2023

Statistical Analysis: The data was collected and analysed using the statistical software, SPSS version 29.0. Qualitative data was expressed as numbers and percentages. Mean values between groups were compared using one-way ANOVA and Students T test. A two-tailed p-value <0.05 was considered statistically significant.

Results:

A total of 2,00,500 samples were submitted to the laboratory during the study period. Out of these, 874 samples were rejected accounting for an overall rejection rate of 0.43%. The phase-wise rejections (Phase I- 348/63849, phase II-259/66909 and phase III- 267/69742) during the study period are depicted in Fig. 2.

Fig.2: Comparison of sample rejection rates during three phases

Overall, there was a significant difference in blood sample rejection rates among three phases. (P-value 0.009 with 95% CI). The most significant difference in blood sample rejection rate was between phase I and II (Table 1). In phase III (no targeted training) though rejection rates had reduced, difference was not statistically significant.

Reasons and areas of sample rejection are listed in Table 2 and Table 3 respectively.

Hemolyzed samples and clotted samples comprised the vast majority (64.65 % in phase I, 68.72 % in second phase and 69.28% in the third phase) of total rejections.

Rejected specimens were seen from all clinical locations of blood sample collection in hospital. The commonest location for having specimen rejected were general wards in all phases followed by MICU (Medical Intensive Care Unit) and Casualty.

Discussion:

Quality in laboratory has huge impact on diagnosis and patient management as a large extent of clinical diagnosis and patient management is based on investigation results. In addition, investigation parameters generated from labs also provide health authorities with statistical data needed to develop, implement and evaluate national health policies. It is mandatory to put in place an effective system of quality assurance in laboratories compare it with desired standards and make corrections to reach an optimal health services delivery process with available resources Monitoring of quality indicators covers critical areas of pre-analytical, analytical and post-analytical phases and has significant impact on performance of a laboratory.(10) The International Organization for Standardization (ISO) 15189: 2022 for laboratory accreditation recognizes the need to evaluate, monitor and improve all procedures and processes especially in the preanalytical phase of testing cycle and also stresses importance of implementing checks to reduce risk to patients.

A study by American College of Pathologists observed that most common reason for errors in the preanalytical setting is human error at about 82.6%. In pre-analytical phase sample rejection leads to increased rate of recollection causing discomfort of repeated pricks in affected patients coupled with consumption of extra resources. (8) Additionally, monitoring sample rejection plays a critical role in calculation of risk priority number (RPN) evaluated by Failure Mode effect analysis (FMEA) as a part of risk management, necessitating a planned and systematic approach to mitigate these errors. (11) The challenge for laboratories is to reduce these errors and deliver quality results which is possible through training of individuals involved in the processes. (3,12) It is also equally important to evaluate efficacy of these training methods and initiate corrective measures periodically to assess subsequent improvement. (12) In the current study overall sample rejection rate was 0.43% and there was a significant difference in rates amongst three phases of the study (P-value 0.009 with 95% CI). The most significant difference in blood sample rejection rate was between phase I and II (before and during the active targeted training of nurses and phlebotomists) The leading cause of sample rejection in the present study was hemolyzed samples (35.58%) followed by clotted samples (31.69%) and insufficient volume/ underfilled tubes (0.52%).

When targeted training was given in second phase, there was a reduction in number of clotted samples (29.88% to 23.59%), underfilled samples (12.35% to 5.99%), barcode mismatch (7.18% to 5.61%) and wrong vacutainers (2.29% to 1.12%). However, no reduction was seen in the proportion of hemolyzed samples. Most of the sample rejections were from general wards (43.47%) followed by Medical intensive care unit (MICU) (22.08%), Causality (17.84%) and Post op ICU/wards (0.07%). Effect of training in the form of reduced rejection rates was noted in causality, Post op ICU/ wards and MICU , however no such reduction was seen in the number of sample rejections from general wards even after training. A possible reason for this trend could be the floating population of nurses in general wards in contrast to fixed dedicated team of nurses who work in the Causality, MICU and Post operative wards and ICU at our set up.

An overall sample rejection rate of 0.43% in the current study was comparable to studies by Noordin et al (0.6%), Chawla et al (1.54%), Tasneem et al (0.67%) and much lesser than the findings in studies by Alavi et al (1.48%), Agarwal et al (4.91%) and Noor et al (5.15%). (1,10,13-16) Prospective analysis by Karcher et al across 78 institutions with a total of 2,054,702 specimen accessions revealed an overall specimen rejection rate of 0.2% . A meta-analysis study including a total of 26 articles with 16,118,499 blood sample requests showed that the pooled prevalence of blood specimen rejection in the clinical laboratory was 1.99%. (2)

In the current study clotted and haemolyzed specimens comprised 67.27 % of total rejected samples. Out of this, maximum rejections were due to haemolysed samples (35.58 %), followed by clotted samples (31.69%) which is in concordance with the study by Chavan et al, Chawla et al Chaudri et al. (12-13,17) Haemolysis is usually the result of vigorous mixing of blood with anticoagulants in the tube, forceful withdrawal and dispensing of blood into collection tubes. Noordin et al also showed that the most frequent cause of rejection was haemolysis (49.6%) followed by clotted samples (32.8%) and insuf­ficient sample volume (6.1%). (1) A study by Tasneem et al showed a rejection rate of 0.67%, with 41.6% of samples displaying haemolysis, 22.5% exhibiting clotting and (12.6%) having an insufficient volume. (14) This contrasts with findings in the study by Gowsami et al in which highest cause of rejection was in terms of clotted samples (78.57%).(7) A meta-analysis done by Getawa et al inferred that the leading causes of blood specimen rejection in clinical laboratories were clotted specimens (32.23%) , hemolysis (22.87%) insufficient volume (22.81%) and labelling errors (7.31%).(2) Rates for other types of preanalytical errors, including mislabelling and insufficient volume at our institution were low, a finding which is in line with the study by Rooper et al.(8) In terms of sites of sample rejections, in our study maximum rejections were from general wards, which is in concordance with a study by Goswami et al where maximum rejections were from general wards. .(6) The proportion of sample rejections was higher in routine as opposed to emergency samples in our study which is similar to findings of Gaur et al.(18)

Active intervention in the form of targeted training of phlebotomists helped reduce sample rejection rates in our study. These findings corroborate findings of the study by Preethi et al where in the period from 2013 to 2017, samples rejection rates dropped significantly. (12) Training is one of the mainstays of interventions required to reduce errors at preanalytical stage. Success of training programs depends on translation of knowledge and skills by trainees to their day‑to‑day activities. Studies recording changes in performance of staff after training have shown that immediate benefits of training were transferred by trainees to their jobs up to an extent of 40% only. Moreover, over a period of six months this degree of transfer reduces to 25% and to 15% by the end of a year. To avoid this fall in productivity and repetition of errors it is essential that retraining must be a continuous activity.(12) While we experienced an immediate and significant decrease in rejection rates following targeted training sessions in phase II, once the same stopped and shifted to routine formal training in phase III , decrease in sample rejects was to a lesser degree compared to phase II .Continued monitoring of rejection rates for a longer period is required to confirm a sustained significant decrease in rejection rates. This approach could be expanded to other areas as well to ensure optimisation of Quality standards.

Limitations of the study: The sustainability of the effect of targeted training on areas with higher sample rejection rates was monitored for a relatively shorter duration. However, as the laboratory is NABL accredited, routine periodic training sessions are being conducted as a part of the annual training calendar immaterial to the rejection rates.

Conclusion:

The outcome of this study has reaffirmed that reviewing and redesigning the processes of training has an impact on decreasing the sample rejection rates. Targeted training used in addition to formal training had tremendous effect on the number and percentage wise improvement in sample rejection rates - one of the key quality indicators in Pre-examination phase. However, challenge lies in putting the training to practice and maintaining sustainability of reduced rejection rates.

Acknowledgement:

We thank and acknowledge the role of Ms. Akshita our lab reception area coordinator, Laboratory Manager Mr. Mahesh, and support of the entire team of faculty, technicians, and quality team of our Central Diagnostics.

Conflict Of Interest: The authors declare no conflicts of interest.

Ethics approval: Ethics committee clearance for the study was obtained from the Institutional Ethics Committee (IEC) (CDSIMER/MR/0068/IEC/2022) dated 22.05.2023

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