Exploring medical error taxonomies and human factors in
simulation-based healthcare education

J 2025

Exploring medical error taxonomies and human factors in simulation-based healthcare education

SKŘÍŠOVSKÁ, Tamara; Daniel SCHWARZ; Martina KOSINOVÁ a Petr ŠTOURAČ

Základní údaje

Originální název

Exploring medical error taxonomies and human factors in simulation-based healthcare education

Autoři

SKŘÍŠOVSKÁ, Tamara; Daniel SCHWARZ; Martina KOSINOVÁ a Petr ŠTOURAČ

Vydání

PLOS ONE, SAN FRANCISCO, PUBLIC LIBRARY SCIENCE, 2025, 1932-6203

Další údaje

Jazyk

angličtina

Typ výsledku

Článek v odborném periodiku

Obor

30230 Other clinical medicine subjects

Stát vydavatele

Spojené státy

Utajení

není předmětem státního či obchodního tajemství

Odkazy

URL

Impakt faktor

Impact factor: 2.600 v roce 2024

Označené pro přenos do RIV

Ano

Organizační jednotka

Lékařská fakulta

Klíčová slova anglicky

medical error; taxonomy; generic; domain

Štítky

14110322, 14110528, rivok

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 3. 3. 2025 13:31, Mgr. Tereza Miškechová

Anotace

V originále

This study aims to provide an updated overview of medical error taxonomies by building on a robust review conducted in 2011. It seeks to identify the key characteristics of the most suitable taxonomy for use in high-fidelity simulation-based postgraduate courses in Critical Care. While many taxonomies are available, none seem to be explicitly designed for the unique context of healthcare simulation-based education, in which errors are regarded as essential learning opportunities. Rather than creating a new classification system, this study proposes integrating existing taxonomies to enhance their applicability in simulation training. Through data from surveys of participants and tutors in postgraduate simulation-based courses, this study provides an exploratory analysis of whether a generic or domain-specific taxonomy is more suitable for healthcare education. While a generic classification may cover a broad spectrum of errors, a domain-specific approach could be more relatable and practical for healthcare professionals in a given domain, potentially improving error-reporting rates. Seven strong links were identified in the reviewed classification systems. These correlations allowed the authors to propose various simulation training strategies to address the errors identified in both the classification systems. This approach focuses on error management and fostering a safety culture, aiming to reduce communication-related errors by introducing the principles of Crisis Resource Management, effective communication methods, and overall teamwork improvement. The gathered data contributes to a better understanding and training of the most prevalent medical errors, with significant correlations found between different medical error taxonomies, suggesting that addressing one can positively impact others. The study highlights the importance of simulation-based education in healthcare for error management and analysis.

Návaznosti

MUNI/A/1551/2023, interní kód MU

Název: Rozvoj vědeckých aspektů simulačního vzdělávání na LF MU I.

Investor: Masarykova univerzita, Rozvoj vědeckých aspektů simulačního vzdělávání na LF MU I.

MUNI/A/1595/2023, interní kód MU

Název: Optimalizace bezpečnosti intenzivní a perioperační péče II

Investor: Masarykova univerzita, Optimalizace bezpečnosti intenzivní a perioperační péče II

Citovat

SKŘÍŠOVSKÁ, Tamara; Daniel SCHWARZ; Martina KOSINOVÁ a Petr ŠTOURAČ. Exploring medical error taxonomies and human factors in simulation-based healthcare education. PLOS ONE. SAN FRANCISCO: PUBLIC LIBRARY SCIENCE, 2025, roč. 20, č. 1, s. 1-13. ISSN 1932-6203. Dostupné z: https://doi.org/10.1371/journal.pone.0317128.

@article{2470041,
   author = {Skříšovská, Tamara and Schwarz, Daniel and Kosinová, Martina and Štourač, Petr},
   article_location = {SAN FRANCISCO},
   article_number = {1},
   doi = {https://doi.org/10.1371/journal.pone.0317128},
   keywords = {medical error; taxonomy; generic; domain},
   language = {eng},
   issn = {1932-6203},
   journal = {PLOS ONE},
   title = {Exploring medical error taxonomies and human factors in simulation-based healthcare education},
   url = {https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0317128},
   volume = {20},
   year = {2025}
}

TY  - JOUR
ID  - 2470041
AU  - Skříšovská, Tamara - Schwarz, Daniel - Kosinová, Martina - Štourač, Petr
PY  - 2025
TI  - Exploring medical error taxonomies and human factors in simulation-based healthcare education
JF  - PLOS ONE
VL  - 20
IS  - 1
SP  - 1-13
EP  - 1-13
PB  - PUBLIC LIBRARY SCIENCE
SN  - 19326203
KW  - medical error
KW  - taxonomy
KW  - generic
KW  - domain
UR  - https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0317128
N2  - This study aims to provide an updated overview of medical error taxonomies by building on a robust review conducted in 2011. It seeks to identify the key characteristics of the most suitable taxonomy for use in high-fidelity simulation-based postgraduate courses in Critical Care. While many taxonomies are available, none seem to be explicitly designed for the unique context of healthcare simulation-based education, in which errors are regarded as essential learning opportunities. Rather than creating a new classification system, this study proposes integrating existing taxonomies to enhance their applicability in simulation training. Through data from surveys of participants and tutors in postgraduate simulation-based courses, this study provides an exploratory analysis of whether a generic or domain-specific taxonomy is more suitable for healthcare education. While a generic classification may cover a broad spectrum of errors, a domain-specific approach could be more relatable and practical for healthcare professionals in a given domain, potentially improving error-reporting rates. Seven strong links were identified in the reviewed classification systems. These correlations allowed the authors to propose various simulation training strategies to address the errors identified in both the classification systems. This approach focuses on error management and fostering a safety culture, aiming to reduce communication-related errors by introducing the principles of Crisis Resource Management, effective communication methods, and overall teamwork improvement. The gathered data contributes to a better understanding and training of the most prevalent medical errors, with significant correlations found between different medical error taxonomies, suggesting that addressing one can positively impact others. The study highlights the importance of simulation-based education in healthcare for error management and analysis.
ER  -

SKŘÍŠOVSKÁ, Tamara; Daniel SCHWARZ; Martina KOSINOVÁ a Petr ŠTOURAČ. Exploring medical error taxonomies and human factors in simulation-based healthcare education. \textit{PLOS ONE}. SAN FRANCISCO: PUBLIC LIBRARY SCIENCE, 2025, roč.~20, č.~1, s.~1-13. ISSN~1932-6203. Dostupné z: https://doi.org/10.1371/journal.pone.0317128.

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