Predicting preventable hospital readmissions with causal machine learning.
Journal:
Health services research
PMID:
33125706
Abstract
OBJECTIVE: To assess both the feasibility and potential impact of predicting preventable hospital readmissions using causal machine learning applied to data from the implementation of a readmissions prevention intervention (the Transitions Program).
Authors
Keywords
Age Factors
Aged
Continuity of Patient Care
Diagnostic Techniques and Procedures
Electronic Health Records
Female
Health Services Research
Health Status
Humans
Machine Learning
Male
Middle Aged
Patient Readmission
Retrospective Studies
Risk Assessment
Risk Factors
Severity of Illness Index
Sex Factors