Prolonged hospital length of stay in pediatric trauma: a model for targeted interventions.
David GibbsLouis EhwerhemuephaTatiana MorenoYigit GunerPeter YuJohn SchombergElizabeth WallaceWilliam FeasterPublished in: Pediatric research (2020)
Targeted interventions on high-risk patients would improve the quality of care of pediatric trauma patients and reduce the length of stay. This comprehensive study includes data from multiple hospitals analyzed with advanced statistical and machine learning models. The statistical and machine learning models provide opportunities for targeted interventions and reduction in prolonged length of stay reducing the burden of hospitalization on families.
Keyphrases
- machine learning
- trauma patients
- healthcare
- cancer therapy
- physical activity
- end stage renal disease
- big data
- artificial intelligence
- ejection fraction
- chronic kidney disease
- newly diagnosed
- palliative care
- quality improvement
- prognostic factors
- deep learning
- emergency department
- patient reported outcomes
- young adults
- chronic pain