Evaluating Patient Safety Drivers using Decision Trees

Bakhita Alderei, Ragheb Nammari, M. A. Alalami, C. Rodrigues, Abroon Qazi, Mecit Can Emre Simsekler
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Abstract

This study aims to identify the drivers of patient safety challenges in healthcare. Hospital-level aggregate survey data from the UK hospital is used to identify what drives the number of reported incidents affecting patient safety. Leveraging a decision tree algorithm, our results suggest that the role of teamwork and safety culture in incident reporting and investigation are the most critical dimensions influencing the number of reported patient safety challenges. The decision tree algorithm can be useful for hospitals to enhance patient safety through data-driven approaches and direct resources towards service improvements.
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使用决策树评估患者安全驱动因素
本研究旨在确定医疗保健中患者安全挑战的驱动因素。来自英国医院的医院级汇总调查数据用于确定影响患者安全的报告事件数量的驱动因素。利用决策树算法,我们的研究结果表明,团队合作和安全文化在事件报告和调查中的作用是影响报告的患者安全挑战数量的最关键维度。决策树算法可以帮助医院通过数据驱动的方法提高患者安全,并将资源用于改善服务。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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