From errors to excellence: the pre-analytical journey to improved quality in diagnostics. A scoping review DOI Creative Commons
George John, Emmanuel J. Favaloro,

S. Bryn Austin

и другие.

Clinical Chemistry and Laboratory Medicine (CCLM), Год журнала: 2025, Номер unknown

Опубликована: Янв. 27, 2025

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

Язык: Английский

From errors to excellence: the pre-analytical journey to improved quality in diagnostics. A scoping review DOI Creative Commons
George John, Emmanuel J. Favaloro,

S. Bryn Austin

и другие.

Clinical Chemistry and Laboratory Medicine (CCLM), Год журнала: 2025, Номер unknown

Опубликована: Янв. 27, 2025

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

Язык: Английский

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