Analysis of Preanalytical Errors in Clinical Biochemistry Laboratory of a Tertiary Care Hospital: A Retrospective Study

Introduction: Pre-analytical phase of laboratory testing is the most susceptible phase, as errors in this phase leads to more than 50% of erroneous results and often breaches the trust of the stakeholders on the quality of the laboratory results. Many pre-analytical errors occur during the pre-analytical phase, encompassing sample collection, labelling and transportationfactors often beyond the laboratory’s direct control. Aim: To determine the type and frequency of pre-analytical errors leading to sample rejection in clinical biochemistry laboratory. Materials and Methods: Being a retrospective descriptive study, convenient sampling was used to analyse sample rejection due to pre-analytical errors in clinical biochemistry laboratory of a tertiary care teaching hospital- PSG Institute of Medical Sciences and Research, Coimbatore, Tamil Nadu, India for a period of six months from May 2023 to October 2023. All the cases/blood samples from Outpatient Department (OPD) and Inpatient Department (IPD), received and rejected during this period were included under study. The data collection and analysis was done over a period of five months using the sample rejection and resample description from Laboratory Information System (LIS). Using Statistical Package for the Social Sciences (SPSS) version 28.0, data were summarised using descriptive statistics such as numbers and percentages. Results: During the six months period out of the total of 667454 samples, 1505 (0.23%) samples were rejected due to pre-analytical errors. The majority of the samples which were rejected were from IPD than OPD. Among the pre-analytical errors, haemolysis accounted for 806 (53.6%), clotted samples 256 (17%), delta check 217 (14.4%), insufficient sample 129 (8.6%), contamination 74 (4.9%), identification error 14 (0.9%), sample without request form 3 (0.2%) while missing samples, billing error, inappropriate tube, delay in transport and wrong test selection accounted for <3 (0.1%). Conclusion: Haemolysis and clotted samples were the most common pre-analytical causes for sample rejection in the laboratory. The samples from IPD were rejected more often than OPD due to incorrect phlebotomy techniques. This accentuates the need for proper hands-on phlebotomy training sessions for novice nurses following their recruitment, as their competency will be instrumental in bringing down the errors in pre-analytical phase.

Authors

Publication Details

Journal
JOURNAL OF CLINICAL AND DIAGNOSTIC RESEARCH
Published
2024-12-01
DOI
https://doi.org/10.7860/jcdr/2024/73364.20384
Citations
2
Primary Topic
Clinical Laboratory Practices and Quality Control
Type
article
Field-Weighted Citation Impact
0.65
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Analysis of Preanalytical Errors in Clinical Biochemistry Laboratory of a Tertiary Care Hospital: A Retrospective Study

Kathiravan Rajendran, Mukhyaprana M. Prabhu, Dhanalakshmi Balasundararaj, S Thilagarajan
2 citations
JOURNAL OF CLINICAL AND DIAGNOSTIC RESEARCH
Clinical Laboratory Practices and Quality Control
0.65
article

Analysis of Preanalytical Errors in Clinical Biochemistry Laboratory of a Tertiary Care Hospital: A Retrospective Study

Kathiravan Rajendran, Mukhyaprana M. Prabhu, Dhanalakshmi Balasundararaj, S Thilagarajan
article en
2 citations

Abstract

Introduction: Pre-analytical phase of laboratory testing is the most susceptible phase, as errors in this phase leads to more than 50% of erroneous results and often breaches the trust of the stakeholders on the quality of the laboratory results. Many pre-analytical errors occur during the pre-analytical phase, encompassing sample collection, labelling and transportationfactors often beyond the laboratory’s direct control. Aim: To determine the type and frequency of pre-analytical errors leading to sample rejection in clinical biochemistry laboratory. Materials and Methods: Being a retrospective descriptive study, convenient sampling was used to analyse sample rejection due to pre-analytical errors in clinical biochemistry laboratory of a tertiary care teaching hospital- PSG Institute of Medical Sciences and Research, Coimbatore, Tamil Nadu, India for a period of six months from May 2023 to October 2023. All the cases/blood samples from Outpatient Department (OPD) and Inpatient Department (IPD), received and rejected during this period were included under study. The data collection and analysis was done over a period of five months using the sample rejection and resample description from Laboratory Information System (LIS). Using Statistical Package for the Social Sciences (SPSS) version 28.0, data were summarised using descriptive statistics such as numbers and percentages. Results: During the six months period out of the total of 667454 samples, 1505 (0.23%) samples were rejected due to pre-analytical errors. The majority of the samples which were rejected were from IPD than OPD. Among the pre-analytical errors, haemolysis accounted for 806 (53.6%), clotted samples 256 (17%), delta check 217 (14.4%), insufficient sample 129 (8.6%), contamination 74 (4.9%), identification error 14 (0.9%), sample without request form 3 (0.2%) while missing samples, billing error, inappropriate tube, delay in transport and wrong test selection accounted for <3 (0.1%). Conclusion: Haemolysis and clotted samples were the most common pre-analytical causes for sample rejection in the laboratory. The samples from IPD were rejected more often than OPD due to incorrect phlebotomy techniques. This accentuates the need for proper hands-on phlebotomy training sessions for novice nurses following their recruitment, as their competency will be instrumental in bringing down the errors in pre-analytical phase.

JOURNAL OF CLINICAL AND DIAGNOSTIC RESEARCH
Openalex Percentile: Top 27%
Clinical Laboratory Practices and Quality Control
0.65
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.