Analyzing Patterns of Injury in Occupational Hand Trauma Focusing on Press Machines: A Registry-Based Study and Machine Learning Analysis †

Abstract

Objectives: The aim of the project is to analyze the data of patients who have been admitted to the emergency room due to severe hand and palm injuries. Methods: we have used data visualization and statistical analysis to observe trends in various factors pertaining to the patients, such as place of injury, machine-causing injuries, date and time of the injury, amputation, fracture, etiology, distribution of the injured hand, etc. Results: There is a significant difference between age and gender groups across various injuries. Most of the injuries in the dataset are occupational injuries caused by press machines. Most injuries take place in the later half of the week, on Wednesdays and Saturdays. Conclusion: There were 1676 patients who reported to the medical emergency center. Of these, only a handful of them have undergone extremely painstaking injuries where there was uncontrolled bleeding and hemi-amputation. We can also surmise the same by looking at the data that provides the summary of the number of fingers injured. Most patients have either one or two fingers injured. Very few patients had more than two fingers injured.