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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Резюме / Abstract:

Представленный литературный обзор уделяет основное внимание эволюции исследований об ошибках преаналитического этапа (ОПЭ) в медицинских лабораториях. ОПЭ влекут последствия в выборе тактики курации пациентов, дополнительные расходы на здравоохранение, увеличение продолжительности пребывания в больнице. Для формулирования ключевых слов был использован инструмент Covidence Review, затем был проведен комплексный поиск литературы с использованием нескольких баз данных с последующим внесением результатов поиска непосредственно в Covidence (n=379). Был проведен скрининг по названиям, аннотации, удаление дубликатов и полнотекстовый скрининг статьей. Исследования (n=232) были просмотрены на соответствие критериям отбора (n=228) и включены в обзор (n=83), а результаты обобщены в блок-схеме PRISMA. В обзоре подчеркивается роль медицинских работников в предотвращении ОПЭ как при сборе и обработке образцов, так и при анализе. В обзоре также обсуждается использование и развитие искусственного интеллекта (ИИ) и машинного обучения в сокращении ОПЭ и выявляются недостатки в стандартных определениях и стратегиях образования. В статье подчеркивается необходимость дальнейших исследований для обеспечения эффективности моделей управления, решения вопросов нормативной валидации моделей индексации вероятности риска (RPI) и рассмотрения вопросов регулирования, безопасности и конфиденциальности. Обзор демонстрирует, что всесторонние исследование эффективности ИИ и программных платформ в реальных условиях и их внедрение в здравоохранение на сегодняшний день отсутствуют, что открывает возможности для дальнейших исследований с целью улучшения управления ОПЭ и повышения качества оказания медицинской помощи.

Ключевые слова / Keywords:

ошибки преаналитического этапа (ОПЭ)

искусственный интеллект (ИИ)

машинное обучение

уменьшение ошибок

индикаторы качества

технологические решения

Авторы / Authors:

Джон Дж.К.

Школа стоматологии и медицинских наук — Университет Чарльза Стерта

Фавалоро Э.Дж.

Школа стоматологии и медицинских наук — Университет Чарльза Стерта;
Сиднейские центры тромбоза и гемостаза — Институт клинической патологии и медицинских исследований (ICPMR) — Госпиталь Уэстмид

Остин С.

Лабораторная медицина Pathwest

Ислам З.

Школа вычислительной техники, математики и инженерии — Университет Чарльза Стерта

Сантакумар А.Б.

Школа стоматологии и медицинских наук — Университет Чарльза Стерта

Дата поступления:

01.08.2025

Дата принятия в печать:

01.09.2025

Закрыть метаданные

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