ArticleRisk analysis : an official publication of the Society for Risk Analysis2022
Adoption of a Data-Driven Bayesian Belief Network Investigating Organizational Factors that Influence Patient Safety.
Article in Risk analysis : an official publication of the Society for Risk Analysis, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Review
- Enhancing maritime transportation security: A data-driven Bayesian network analysis of terrorist attack risks.Risk analysis : an official publication of the Society for Risk Analysis · 2025Article
- Evaluating patient experience in maternity services using a Bayesian belief network model.PloS one · 2025Article
- Impact of innovative technologies on quality and safety in surgery.Journal of robotic surgery · 2024Review
- Assessment of the organizational factors in incident management practices in healthcare: A tree augmented Naive Bayes model.PloS one · 2024Article
- Protective consumption behavior under smog: using a data-driven dynamic Bayesian network.Environment, development and sustainability · 2022Article
- Prioritizing Multidimensional Interdependent Factors Influencing COVID-19 Risk.Risk analysis : an official publication of the Society for Risk Analysis · 2022Review
- Exploring drivers of patient satisfaction using a random forest algorithm.BMC medical informatics and decision making · 2021Article
Corrections and comments
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Authors and funding
2 authors.
Funding
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Abstract
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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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.