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Analysis of Factors Related to Domestic Patient Safety Incidents Using Decision Tree Technique

PURPOSE: To address the increasing number of patient safety incidents, their scope and extent should be assessed and the situations in which they occur determined. This study employed a decision tree analysis based on patient safety incident cases to identify groups at high risk for adverse patient...

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Autores principales: Shin, Jieun, Lee, Ji-Hoon, Kim, Nam-Yi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10422998/
https://www.ncbi.nlm.nih.gov/pubmed/37575685
http://dx.doi.org/10.2147/RMHP.S421167
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author Shin, Jieun
Lee, Ji-Hoon
Kim, Nam-Yi
author_facet Shin, Jieun
Lee, Ji-Hoon
Kim, Nam-Yi
author_sort Shin, Jieun
collection PubMed
description PURPOSE: To address the increasing number of patient safety incidents, their scope and extent should be assessed and the situations in which they occur determined. This study employed a decision tree analysis based on patient safety incident cases to identify groups at high risk for adverse patient safety incidents and provide data to develop prevention strategies for minimizing their occurrence or recurrence. METHODS: In total, 8934 patient safety incidents were analyzed using the “2021 Patient Safety Report Data”, which were systematically collected by the Korea Institute for Healthcare Accreditation. A decision tree analysis (Chi-square Automatic Interaction Detection) was employed to identify the characteristics associated with the degree of risk for patient safety incidents. RESULTS: The groups most vulnerable to adverse events were those who experienced healthcare-associated infections (HAI) in long-term care facilities, followed by those experiencing HAI in tertiary hospitals, general hospitals, or clinics, and those experiencing fall-related events in neuropsychiatry departments of tertiary hospitals, general hospitals, or clinics. CONCLUSION: The most important factor in the degree of harm in patient safety accidents was the type of accident, followed by the type of medical institution, and then the treatment department. Particularly, HAI and falls are the most important factors determining the degree of harm in patient safety accidents.
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spelling pubmed-104229982023-08-13 Analysis of Factors Related to Domestic Patient Safety Incidents Using Decision Tree Technique Shin, Jieun Lee, Ji-Hoon Kim, Nam-Yi Risk Manag Healthc Policy Original Research PURPOSE: To address the increasing number of patient safety incidents, their scope and extent should be assessed and the situations in which they occur determined. This study employed a decision tree analysis based on patient safety incident cases to identify groups at high risk for adverse patient safety incidents and provide data to develop prevention strategies for minimizing their occurrence or recurrence. METHODS: In total, 8934 patient safety incidents were analyzed using the “2021 Patient Safety Report Data”, which were systematically collected by the Korea Institute for Healthcare Accreditation. A decision tree analysis (Chi-square Automatic Interaction Detection) was employed to identify the characteristics associated with the degree of risk for patient safety incidents. RESULTS: The groups most vulnerable to adverse events were those who experienced healthcare-associated infections (HAI) in long-term care facilities, followed by those experiencing HAI in tertiary hospitals, general hospitals, or clinics, and those experiencing fall-related events in neuropsychiatry departments of tertiary hospitals, general hospitals, or clinics. CONCLUSION: The most important factor in the degree of harm in patient safety accidents was the type of accident, followed by the type of medical institution, and then the treatment department. Particularly, HAI and falls are the most important factors determining the degree of harm in patient safety accidents. Dove 2023-08-08 /pmc/articles/PMC10422998/ /pubmed/37575685 http://dx.doi.org/10.2147/RMHP.S421167 Text en © 2023 Shin et al. https://creativecommons.org/licenses/by-nc/3.0/This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/ (https://creativecommons.org/licenses/by-nc/3.0/) ). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php).
spellingShingle Original Research
Shin, Jieun
Lee, Ji-Hoon
Kim, Nam-Yi
Analysis of Factors Related to Domestic Patient Safety Incidents Using Decision Tree Technique
title Analysis of Factors Related to Domestic Patient Safety Incidents Using Decision Tree Technique
title_full Analysis of Factors Related to Domestic Patient Safety Incidents Using Decision Tree Technique
title_fullStr Analysis of Factors Related to Domestic Patient Safety Incidents Using Decision Tree Technique
title_full_unstemmed Analysis of Factors Related to Domestic Patient Safety Incidents Using Decision Tree Technique
title_short Analysis of Factors Related to Domestic Patient Safety Incidents Using Decision Tree Technique
title_sort analysis of factors related to domestic patient safety incidents using decision tree technique
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10422998/
https://www.ncbi.nlm.nih.gov/pubmed/37575685
http://dx.doi.org/10.2147/RMHP.S421167
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