Background:

Pre-analytical errors remain the leading source of laboratory testing failures and significantly influence patient safety, cost, and turnaround time. Specimen rejection rate is a recognized laboratory quality indicator.

Methods:

A retrospective analytical study evaluated all rejected specimens received between January and December 2024. Rejection rates were calculated using total test volumes. Statistical methods

Pareto analysis, statistical process control (p-chart), and performance benchmarking.

Results:

Out of 1,675,329 laboratory tests performed, 1,186 specimens were rejected, corresponding to an overall rejection rate of 0.071% (95% CI: 0.067–0.075%). Haemolysis was the dominant cause. Rejection distribution differed significantly across clinical areas (p < 0.001), with Emergency/ICU contributing the highest burden. Monthly rates ranged from 0.021% to 0.115%, demonstrating stable performance without special-cause variation.

Conclusion:

Specimen rejection was uncommon and statistically stable over time. High-acuity clinical settings represent priority targets for focused quality improvement initiatives included descriptive statistics, confidence coefficient of variation, time-series intervals, chi-square

Laboratory diagnostics influence a substantial proportion of clinical decisions. The reliability of laboratory results depends on the integrity of the total testing process, particularly the pre-analytical phase. This phase includes specimen collection, identification, transport, and handling prior to analysis. Errors at this stage frequently result in specimen rejection, leading to delays, repeat sampling, and increased healthcare costs Haemolysis, clotting, insufficient volume, and labelling errors are among the most commonly reported causes of rejection. High-acuity environments such as emergency departments and intensive care units present additional challenges, including difficult venous access and urgent testing demands. Monitoring rejection rates is recommended under international accreditation standards as part of laboratory quality assurance. This study provides a comprehensive analytical evaluation of rejection patterns in a high-volume tertiary care setting. 

Design: Retrospective analytical observational study

Period: January–December 2024

Setting: Central laboratory of a 900-bed tertiary care hospital Clinical Classification:

•  Emergency/ICU

•  Ward (all inpatient units combined)

•  Outpatient services 

Statistical Methods:

•  Proportion and rate calculation

•  95% binomial confidence interval

•  Chi-square test

•  Coefficient of variation

•  Time-series evaluation

•  Pareto analysis

•  p-chart (SPC)

•  Funnel plot benchmark comparison

Significance level: p < 0>

Results

Materials and Methods

Table 2. Cause Distribution

1️.Overall Rejection Rate

Table 1: Overall Laboratory Performance

The narrow confidence interval reflects high statistical precision due to the large denominator.

2. Monthly Trend Analysis

Table 2: Monthly Rejection Rates

Mean Monthly Rate: 0.071% Standard Deviation: ≈ 0.028% Coefficient of Variation: ≈ 39%

Figure 1: Monthly Rejection Trend

Interpretation

Although moderate variability was observed, no consistent upward or downward trajectory was identified, suggesting operational fluctuation rather than systemic instability.

3.Causes of Rejection (Pareto Analysis)

Table 3: Distribution of Rejection Causes

Figure 2: Cause Distribution

Interpretation

Hemolysis accounted for the majority of rejection events, supporting the principle that targeted improvement in specimen collection technique may yield significant reductions in overall rejection.

4.Clinical Area Distribution

Table 3: Clinical Area Distribution

Figure 3: Clinical Area Comparison

Table 4: Rejection Burden by Clinical Area

Chi-square test demonstrated significant association (p < 0>

5. Statistical Process Control

Figure 4: Statistical Process Control (p-Chart)

Table 5: Process Stability Indicators

Interpretation

All monthly observations fell within control limits, confirming statistical stability and predominance of common-cause variation.

6. Benchmark Comparison

Figure 5: Funnel Plot Benchmark Comparison

Table 6: Benchmark Evaluation

Performance was at the favourable end of reported ranges.

The present analytical evaluation demonstrates that specimen rejection in this high-volume laboratory is rare and statistically stable. The overall rejection rate of 0.071% is considerably lower than many reported international values.

Temporal analysis revealed moderate fluctuation without sustained deterioration. Control chart evaluation confirmed process stability, indicating that observed variability was attributable to routine operational factors.

Haemolysis was the leading cause of rejection, consistent with global evidence identifying mechanical trauma during venipuncture and handling as major contributors. Interventions targeting collection technique, transport conditions, and staff training may further reduce rejection events.

Significant variation across clinical areas reflects the influence of patient acuity and procedural complexity. Emergency and ICU settings demonstrated the highest burden, likely due to urgent sampling conditions and difficult venous access. Outpatient services showed the lowest rates due to controlled sampling environments.

Overall findings highlight effective laboratory quality management while identifying specific opportunities for targeted improvement.

Strengths and Limitations

Strengths

•  Large dataset ensuring high precision

•  Multi-method statistical evaluation

•  Inclusion of process-control techniques

•  Real-world clinical applicability

Limitations

•  Retrospective design

•  Absence of patient-level predictors

• Single-center study

Specimen rejection in this tertiary care laboratory was infrequent, statistically stable, and strongly influenced by clinical context. High-acuity environments remain priority areas for quality improvement. Overall laboratory performance was favourable compared with typical published benchmarks.

Disclosure Of Interest

No potential competing interest was reported by the authors

Funding

No funding was received

Data Availability

Data available on request due to privacy/ethical restrictions The data are not publicly available due to restrictions to share the patient’s data, that could compromise the privacy of research participants.