Ensemble Machine Learning Models for Predicting Death in Post-Acute Skilled Nursing Facilities.

Key Points

• The aim is to develop machine learning models to predict mortality risk after discharge from skilled nursing facilities.
• Developed ensemble machine learning models for mortality prediction post-discharge.
• Focused on predicting death within 30 and 180 days after discharge.
• Emphasized the need for further calibration and external validation.
• Predicted mortality risk effectively using developed models.
• Provided insights for better patient-centered care strategies.
• Indicated the potential for preparing clinicians for care goal discussions.