Can diverse population characteristics be leveraged in a machine learning pipeline to predict resource intensive healthcare utilization among hospital service areas?

Background: Super-utilizers represent approximately 5% of the population in the United States (U.S.) and yet they are responsible for over 50% of healthcare expenditures. Using characteristics of hospital service areas (HSAs) to predict utilization of resource intensive healthcare (RIHC) may offer a...

Full description

Bibliographic Details
Main Authors: Ailawadi, K.L (Author), Brown, J.R (Author), Emond, J.A (Author), MacKenzie, T.A (Author), Ricket, I.M (Author)
Format: Article
Language:English
Published: BioMed Central Ltd 2022
Subjects:
Online Access:View Fulltext in Publisher