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运用决策树技术分析国内患者安全事件相关因素

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

作者信息

Shin Jieun, Lee Ji-Hoon, Kim Nam-Yi

机构信息

Department of Biomedical Informatics, College of Medicine, Konyang University, Daejeon, Republic of Korea.

Department of Nursing, Konyang University, Daejeon, Republic of Korea.

出版信息

Risk Manag Healthc Policy. 2023 Aug 8;16:1467-1476. doi: 10.2147/RMHP.S421167. eCollection 2023.

DOI:10.2147/RMHP.S421167
PMID:37575685
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10422998/
Abstract

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.

摘要

目的

为应对患者安全事件数量的不断增加,应评估其范围和程度,并确定事件发生的情况。本研究采用基于患者安全事件案例的决策树分析,以识别发生不良患者安全事件的高风险群体,并提供数据以制定预防策略,尽量减少此类事件的发生或复发。

方法

使用韩国医疗认证院系统收集的“2021年患者安全报告数据”,对总共8934起患者安全事件进行了分析。采用决策树分析(卡方自动相互作用检测)来识别与患者安全事件风险程度相关的特征。

结果

最易发生不良事件的群体是那些在长期护理机构中发生医疗相关感染(HAI)的患者,其次是在三级医院、综合医院或诊所发生HAI的患者,以及在三级医院、综合医院或诊所的神经精神科发生跌倒相关事件的患者。

结论

患者安全事故危害程度的最重要因素是事故类型,其次是医疗机构类型,然后是治疗科室。特别是,HAI和跌倒事件是决定患者安全事故危害程度的最重要因素。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/793a/10422998/be5787dff173/RMHP-16-1467-g0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/793a/10422998/08ed24a9dd91/RMHP-16-1467-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/793a/10422998/be5787dff173/RMHP-16-1467-g0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/793a/10422998/08ed24a9dd91/RMHP-16-1467-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/793a/10422998/be5787dff173/RMHP-16-1467-g0002.jpg

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