Exploring the use of machine learning for risk adjustment: A comparison of standard and penalized linear regression models in predicting health care costs in older adults

BACKGROUND: Payers and providers still primarily use ordinary least squares (OLS) to estimate expected economic and clinical outcomes for risk adjustment purposes. Penalized linear regression represents a practical and incremental step forward that provides transparency and interpretability within t...

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Detalles Bibliográficos
Autores principales: Kan, Hong J., Kharrazi, Hadi, Chang, Hsien-Yen, Bodycombe, Dave, Lemke, Klaus, Weiner, Jonathan P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6402678/
https://www.ncbi.nlm.nih.gov/pubmed/30840682
http://dx.doi.org/10.1371/journal.pone.0213258

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6402678/
https://www.ncbi.nlm.nih.gov/pubmed/30840682
http://dx.doi.org/10.1371/journal.pone.0213258

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