TY - JOUR
T1 - Assessment of the organizational factors in incident management practices in healthcare
T2 - A tree augmented Naive Bayes model
AU - Albreiki, Salma
AU - Simsekler, Mecit Can Emre
AU - Qazi, Abroon
AU - Bouabid, Ali
N1 - Publisher Copyright:
© 2024 Albreiki et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
PY - 2024/3
Y1 - 2024/3
N2 - Despite the exponential transformation occurring in the healthcare industry, operational failures pose significant challenges in the delivery of safe and efficient care. Incident management plays a crucial role in mitigating these challenges; however, it encounters limitations due to organizational factors within complex and dynamic healthcare systems. Further, there are limited studies examining the interdependencies and relative importance of these factors in the context of incident management practices. To address this gap, this study utilized aggregate-level hospital data to explore the influence of organizational factors on incident management practices. Employing a Bayesian Belief Network (BBN) structural learning algorithm, Tree Augmented Naive (TAN), this study assessed the probabilistic relationships, represented graphically, between organizational factors and incident management. Significantly, the model highlighted the critical roles of morale and staff engagement in influencing incident management practices within organizations. This study enhances our understanding of the importance of organizational factors in incident management, providing valuable insights for healthcare managers to effectively prioritize and allocate resources for continuous quality improvement efforts.
AB - Despite the exponential transformation occurring in the healthcare industry, operational failures pose significant challenges in the delivery of safe and efficient care. Incident management plays a crucial role in mitigating these challenges; however, it encounters limitations due to organizational factors within complex and dynamic healthcare systems. Further, there are limited studies examining the interdependencies and relative importance of these factors in the context of incident management practices. To address this gap, this study utilized aggregate-level hospital data to explore the influence of organizational factors on incident management practices. Employing a Bayesian Belief Network (BBN) structural learning algorithm, Tree Augmented Naive (TAN), this study assessed the probabilistic relationships, represented graphically, between organizational factors and incident management. Significantly, the model highlighted the critical roles of morale and staff engagement in influencing incident management practices within organizations. This study enhances our understanding of the importance of organizational factors in incident management, providing valuable insights for healthcare managers to effectively prioritize and allocate resources for continuous quality improvement efforts.
UR - http://www.scopus.com/inward/record.url?scp=85187180649&partnerID=8YFLogxK
U2 - 10.1371/journal.pone.0299485
DO - 10.1371/journal.pone.0299485
M3 - Article
C2 - 38451980
AN - SCOPUS:85187180649
SN - 1932-6203
VL - 19
JO - PLoS ONE
JF - PLoS ONE
IS - 3.0
M1 - e0299485
ER -