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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| Veröffentlicht in: | Risk analysis Jg. 42; H. 6; S. 1277 - 1293 |
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| Format: | Journal Article |
| Sprache: | Englisch |
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Oxford
Blackwell Publishing Ltd
01.06.2022
John Wiley and Sons Inc |
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| ISSN: | 0272-4332, 1539-6924, 1539-6924 |
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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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| AbstractList | 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. 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.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. |
| Author | Simsekler, Mecit Can Emre Qazi, Abroon |
| AuthorAffiliation | 3 School of Business Administration American University of Sharjah Sharjah UAE 1 Department of Industrial and Systems Engineering Khalifa University of Science and Technology Abu Dhabi UAE 2 School of Management University College London London E14 5AA UK |
| AuthorAffiliation_xml | – name: 1 Department of Industrial and Systems Engineering Khalifa University of Science and Technology Abu Dhabi UAE – name: 3 School of Business Administration American University of Sharjah Sharjah UAE – name: 2 School of Management University College London London E14 5AA UK |
| Author_xml | – sequence: 1 givenname: Mecit Can Emre orcidid: 0000-0002-1555-5012 surname: Simsekler fullname: Simsekler, Mecit Can Emre email: emre.simsekler@ku.ac.ae organization: University College London – sequence: 2 givenname: Abroon orcidid: 0000-0001-6648-3306 surname: Qazi fullname: Qazi, Abroon organization: American University of Sharjah |
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| SubjectTerms | Aggregate data Bayesian analysis Bayesian Network Belief networks Bullying Critical incidents Decision making Errors Harassment Health care Health care industry Health services healthcare operations Hospitals Mathematical models Medical errors Medical research Near misses Organizational aspects Organizational factors Organizational research Original Original s Patient safety Patients Probabilistic models risk Risk assessment Safety Well being Work environment Working conditions |
| Title | Adoption of a Data‐Driven Bayesian Belief Network Investigating Organizational Factors that Influence Patient Safety |
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