Machine Learning Applied to Electronic Health Records: Identification of Chemotherapy Patients at High Risk for Preventable Emergency Department Visits and Hospital Admissions

PURPOSE: Acute care use (ACU) is a major driver of oncologic costs and is penalized by a Centers for Medicare & Medicaid Services quality measure, OP-35. Targeted interventions reduce preventable ACU; however, identifying which patients might benefit remains challenging. Prior predictive models...

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Detalles Bibliográficos
Autores principales: Peterson, Dylan J., Ostberg, Nicolai P., Blayney, Douglas W., Brooks, James D., Hernandez-Boussard, Tina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer Health 2021
Materias:
ORIGINAL REPORTS
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8807019/
https://www.ncbi.nlm.nih.gov/pubmed/34752139
http://dx.doi.org/10.1200/CCI.21.00116

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8807019/
https://www.ncbi.nlm.nih.gov/pubmed/34752139
http://dx.doi.org/10.1200/CCI.21.00116

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