A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Evaluating Patient Safety Drivers using Decision Trees
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.
Evaluating Patient Safety Drivers using Decision Trees
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.
Evaluating Patient Safety Drivers using Decision Trees
Alderei, Bakhita (author) / Nammari, Ragheb (author) / Alalami, Mohammad A. (author) / Rodrigues, Clarence (author) / Qazi, Abroon (author) / Emre Simsekler, Mecit Can (author)
2022-02-21
1730585 byte
Conference paper
Electronic Resource
English
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