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 and Petr ŠTOURAČ

Basic information

Original name

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

Authors

SKŘÍŠOVSKÁ, Tamara (203 Czech Republic, belonging to the institution); Daniel SCHWARZ (203 Czech Republic, belonging to the institution); Martina KOSINOVÁ (203 Czech Republic, belonging to the institution) and Petr ŠTOURAČ (203 Czech Republic, belonging to the institution)

Edition

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

Other information

Language

English

Type of outcome

Article in a journal

Field of Study

30230 Other clinical medicine subjects

Country of publisher

United States of America

Confidentiality degree

is not subject to a state or trade secret

References:

URL

Impact factor

Impact factor: 2.900 in 2023

Organization unit

Faculty of Medicine

DOI

http://dx.doi.org/10.1371/journal.pone.0317128

UT WoS

001407853100050

EID Scopus

2-s2.0-85215426084

Keywords in English

medical error; taxonomy; generic; domain

Abstract

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.

Links

MUNI/A/1551/2023, interní kód MU

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

Investor: Masaryk University, Expansion of scientigic aspects in simulation-based education I.

MUNI/A/1595/2023, interní kód MU

Name: Optimalizace bezpečnosti intenzivní a perioperační péče II

Investor: Masaryk University, Optimizing the safety of intensive and perioperative care II

Cite

SKŘÍŠOVSKÁ, Tamara; Daniel SCHWARZ; Martina KOSINOVÁ and Petr ŠTOURAČ. Exploring medical error taxonomies and human factors in simulation-based healthcare education. PLOS ONE. SAN FRANCISCO: PUBLIC LIBRARY SCIENCE, 2025, vol. 20, No 1, p. 1-13. ISSN 1932-6203. Available from: https://dx.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 = {http://dx.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 and Petr ŠTOURAČ. Exploring medical error taxonomies and human factors in simulation-based healthcare education. \textit{PLOS ONE}. SAN FRANCISCO: PUBLIC LIBRARY SCIENCE, 2025, vol.~20, No~1, p.~1-13. ISSN~1932-6203. Available from: https://dx.doi.org/10.1371/journal.pone.0317128.

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