Adoption of a Data-Driven Bayesian Belief Network Investigating Organizational Factors that Influence Patient Safety.
Medical errors pose high risks to patients. Several organizational factors may impact the high rate of medical errors in complex and dynamic healthcare systems. However, limited research is available regarding probabilistic interdependencies between the organizational factors and patient safety errors. To explore this, we adopt a data-driven Bayesian Belief Network (BBN) model to represent a class of probabilistic models, using the hospital-level aggregate survey data from U.K. hospitals. Leveraging the use of probabilistic dependence models and visual features in the BBN model, the results shed new light on relationships existing among eight organizational factors and patient safety errors. With the high prediction capability, the data-driven approach results suggest that "health and well-being" and "bullying and harassment in the work environment" are the two leading factors influencing the number of reported errors and near misses affecting patient safety. This study provides significant insights to understand organizational factors' role and their relative importance in supporting decision-making and safety improvements.
['Simsekler|Mecit Can Emre|MCE|https://orcid.org/0000-0002-1555-5012', 'Qazi|Abroon|A|https://orcid.org/0000-0001-6648-3306']
patient safety medical errors risk Bayesian Network healthcare operations