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Prediction of Medical Disputes Between Health Care Workers and Patients in Terms of Hospital Legal Construction Using Machine Learning Techniques: Externally Validated Cross-Sectional Study.

Min YiYuebin CaoLin WangYao Wen GuXueqian ZhengJiangjun WangWei ChenLiangyu WeiYujin ZhouChenyi ShiYanlin Cao
Published in: Journal of medical Internet research (2023)
We established a prediction model to stratify medical workers into different risk groups for encountering medical disputes. Among the 5 ML models, GBDT demonstrated the optimal comprehensive performance and was used to construct the web-based app. Our proposed model can serve as a useful tool for identifying medical workers at high risk of medical disputes. We believe that preventive strategies should be implemented for the high-risk group.
Keyphrases
  • healthcare
  • end stage renal disease
  • ejection fraction
  • emergency department
  • patient reported outcomes
  • patient reported
  • electronic health record