Assessment of the organizational factors in incident management practices in healthcare: A tree augmented Naive Bayes model

Salma Albreiki, Mecit Can Emre Simsekler, Abroon Qazi, Ali Bouabid

    Research output: Contribution to journalArticlepeer-review

    18 Scopus citations

    Abstract

    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.

    Original languageBritish English
    Article numbere0299485
    JournalPLoS ONE
    Volume19
    Issue number3.0
    DOIs
    StatePublished - Mar 2024

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