Cargando…
Using machine learning to predict risk of incident opioid use disorder among fee-for-service Medicare beneficiaries: A prognostic study
OBJECTIVE: To develop and validate a machine-learning algorithm to improve prediction of incident OUD diagnosis among Medicare beneficiaries with ≥1 opioid prescriptions. METHODS: This prognostic study included 361,527 fee-for-service Medicare beneficiaries, without cancer, filling ≥1 opioid prescri...
Autores principales: | Lo-Ciganic, Wei-Hsuan, Huang, James L., Zhang, Hao H., Weiss, Jeremy C., Kwoh, C. Kent, Donohue, Julie M., Gordon, Adam J., Cochran, Gerald, Malone, Daniel C., Kuza, Courtney C., Gellad, Walid F. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7367453/ https://www.ncbi.nlm.nih.gov/pubmed/32678860 http://dx.doi.org/10.1371/journal.pone.0235981 |
Ejemplares similares
-
Evaluation of Machine-Learning Algorithms for Predicting Opioid Overdose Risk Among Medicare Beneficiaries With Opioid Prescriptions
por: Lo-Ciganic, Wei-Hsuan, et al.
Publicado: (2019) -
Developing and validating a machine-learning algorithm to predict opioid overdose in Medicaid beneficiaries in two US states: a prognostic modelling study
por: Lo-Ciganic, Wei-Hsuan, et al.
Publicado: (2022) -
Integrating human services and criminal justice data with claims data to predict risk of opioid overdose among Medicaid beneficiaries: A machine-learning approach
por: Lo-Ciganic, Wei-Hsuan, et al.
Publicado: (2021) -
Predictors of Disenrollment Among Medicare Fee-for-Service Beneficiaries With Dementia
por: Rivera-Hernandez, Maricruz, et al.
Publicado: (2021) -
Opioid Use Among Rural Medicare Beneficiaries
por: Jonk, Yvonne Catharina, et al.
Publicado: (2021)