From errors to excellence: the pre-analytical journey to improved quality in diagnostics. A scoping review

John G.K.; Favaloro E.J.; Austin S.; Islam Z.; Santhakumar A.B.

doi:https://doi.org/10.17116/labs20251403146

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Abstract:

This scoping review focuses on the evolution of pre-analytical errors (PAEs) in medical laboratories, a critical area with significant implications for patient care, healthcare costs, hospital length of stay, and operational efficiency. The Covidence Review tool was used to formulate the keywords, and then a comprehensive literature search was performed using several databases, importing the search results directly into Covidence (n=379). Title, abstract screening, duplicate removal, and full-text screening were done. The retrieved studies (n=232) were scanned for eligibility (n=228) and included in the review (n=83), and the results were summarised in a PRISMA flow chart. The review highlights the role of healthcare professionals in preventing PAEs in specimen collection and processing, as well as analyses. The review also discusses the use and advancements of artificial intelligence (AI) and machine learning in reducing PAEs and identifies inadequacies in standard definitions, measurement units, and education strategies. It demonstrates the need for further research to ensure model validation, address the regulatory validation of Risk Probability Indexation (RPI) models and consider regulatory, safety, and privacy concerns. The review suggests that comprehensive studies on the effectiveness of AI and software platforms in real-world settings and their implementation in healthcare are lacking, presenting opportunities for further research to advance patient care and improve the management of PAEs.

Keywords:

pre-analytical error (PAE)

artificial intelligence (AI)

machine learning

error reduction

quality indicators

technological solutions

Authors:

John G.K.

School of Dentistry and Medical Science

Favaloro E.J.

School of Dentistry and Medical Science;
Sydney Centres for Thrombosis and Haemostasis — Institute of Clinical Pathology and Medical Research (ICPMR) — Westmead Hospital

Austin S.

Pathwest Laboratory Medicine

Islam Z.

School of Computing, Mathematics and Engineering — Charles Sturt University

Santhakumar A.B.

School of Dentistry and Medical Science

Received:

01.08.2025

Accepted:

01.09.2025

Close metadata

References:

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