Evidence map›Paper›PMID 39672671›Full record

ArticleClinical chemistry and laboratory medicine2025

Evaluation of performance in preanalytical phase EQA: can laboratories mitigate common pitfalls?

Anna Linko-Parvinen, Jonna Pelanti, Tanja Vanhelo, Pia Eloranta, Hanna-Mari Pallari

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Article in Clinical chemistry and laboratory medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

5 authors.

Anna Linko-ParvinenTyks Laboratories, Clinical Chemistry, Turku University Hospital, Turku, Finland.ORCID 0000-0002-0679-4724
Jonna PelantiDepartment of Clinical Chemistry, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.ORCID 0000-0001-8900-7775
Tanja VanheloLabquality Ltd, Helsinki, Finland.
Pia ElorantaLabquality Ltd, Helsinki, Finland.
Hanna-Mari PallariTyks Laboratories, Clinical Chemistry, Turku University Hospital, Turku, Finland.ORCID 0009-0005-7742-3946

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesPreanalytical phase is an elemental part of laboratory diagnostics, but is prone to humane errors. The aim of this study was to evaluate performance in preanalytical phase external quality assessment (EQA) cases. We also suggest preventive actions for risk mitigation.

methodsWe included 12 EQA rounds (Labquality Ltd.) with three patient cases (36 cases, 54-111 participants, 7-15 countries) published in 2018-2023. We graded performance according to percentage of correct responses in each case as ≥900 % excellent, 70-89 % good, 50-69 % satisfactory, 30-49 % fair and <30 % poor. Performance was simultaneously failed with ≥10 % of responses leading to harmful events.

resultsOverall performance was excellent in 7, good in 12, satisfactory in 10, fair in 4 and poor in 3 cases. Additionally, 7 cases showed failed performance. Routine requests with incorrect sample tubes or incorrect sample handling were detected with good performance. Lower performance was seen with sudden abnormal results, with rare requests, with false patient identification (never-events) and with incorrect test requests. Information technology (IT) solutions (preanalytical checklists, autoverification rules and patient specific notifications) could have prevented 33 of 36 preanalytical errors.

conclusionsWhile most common errors were detected with good performance, samples with rare requests or those requiring individualised consideration are vulnerable to human misinterpretation. In many instances, samples with preanalytical errors should have been identified and rejected before reaching the laboratory or being directed to analysis. Optimising IT solutions to effectively detect these preanalytical errors allows for focus on infrequent events demanding accessible professional consultation. EQA preanalytical cases may help in education of correct actions in these occasions.

Indexed as

Laboratories, ClinicalPre-Analytical PhaseQuality Assurance, Health CareDiagnostic ErrorsHumansQuality ControlSpecimen Handlingexternal quality assessmentlaboratory diagnosticspreanalytical phase

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.