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 erro...

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Bibliographic Details
Published in:Risk analysis Vol. 42; no. 6; pp. 1277 - 1293
Main Authors: Simsekler, Mecit Can Emre, Qazi, Abroon
Format: Journal Article
Language:English
Published: Oxford Blackwell Publishing Ltd 01.06.2022
John Wiley and Sons Inc
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ISSN:0272-4332, 1539-6924, 1539-6924
Online Access:Get full text
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Summary: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.
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ISSN:0272-4332
1539-6924
1539-6924
DOI:10.1111/risa.13610