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September 1, 2023European Journal of Medical and Health Research

Predictive Risk Modelling and Occupational Hazard Mapping in the United States Healthcare Sector: A Data-Driven Safety Surveillance Study

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Authors

MIMusfikul IslamMKM. A. M. KhanMRMd Obayed Al Rahman

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Overview

Data-driven safety surveillance predicts occupational hazards in healthcare, suggesting areas for improvement.

Key Points

  • Occupational hazards in healthcare were predicted using machine learning models, revealing high-risk departments.
  • The optimal predictive model was XGBoost, achieving an AUC-ROC score of 0.91, highlighting its accuracy.
  • Analysis of over 12,000 incident records used geospatial analytics to identify risk hotspots across multiple states.
  • Results indicate a need for improved safety governance in healthcare, focusing on areas with high injury rates.

Cite This Study

Islam et al. (2023) studied this question.

synapsesocial.com/papers/68af659bad7bf08b1eae5ad6https://doi.org/10.59324/ejmhr.2023.1(2).24
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