Evidence map›Paper›PMID 40092879›Full record

ArticleBioinformation2024

Evaluation of pre-analytical errors using six sigma metrics towards quality of laboratory performance in an Indian tertiary care hospital.

Shruti Seth, Narendra Kumar Sah, Neha Rajwal

Abstract read
In one paragraph

Article in Bioinformation, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

3 authors.

Shruti SethDepartment of Biochemistry, Shri Mata Vaishno Devi Institute of Medical Excellence and Associated Hospital, Shri Mata Vaishno Devi University, Kakryal, Katra, Jammu and Kashmir 182320, India.
Narendra Kumar SahDepartment of Biochemistry, Maharishi Markandeshwar Medical College and Hospital, Lado, Kumarhatti - Solan 173229 India.
Neha RajwalLaboratory Medicine, Shri Mata Vaishno Devi Narayana, Superspeciality Hospital, Kakryal, Katra, Jammu and Kashmir, 182320, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Six Sigma methodologies is one of the standard management system adopted to check the quality and improve laboratory performance continuously by assessing the laboratory process using six sigma metrics. A one-year prospective study from January 2019 to December 2019 was conducted at the laboratory of medicine department in a tertiary care hospital. A total of 162974 samples were received from both inpatient and outpatient departments and total laboratory errors were found to be 1144, with the maximum errors identified in the pre-analytical phase coming out to be 978 (0.6%). The types of errors in the pre-analytical phase after being identified and categorized were hemolyzed samples, clotted samples, phlebotomy errors, etc. The most typical error identified was clotted sample error (0.29%) followed by haemolysed sample error (0.20%). After calculating the error rate or defects per million error samples on a Sigma calculator, the value obtained was between 4 and 5 which an average class quality. Thus, we show that continuous and repeated recognition of errors and evaluating them using Six Sigma metrics can help achieve overall laboratory procedure quality and better clinical diagnosis.

Indexed as

laboratory errorslaboratory qualityPre-analytical errorsquality indicatorssix sigma metricstotal laboratory testing

Identifiers

PMID40092879
PMCPMC11904151

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