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

• Κύριοι συγγραφείς: Iben M. Ricket (Συγγραφέας), Todd A. MacKenzie (Συγγραφέας), Jennifer A. Emond (Συγγραφέας), Kusum L. Ailawadi (Συγγραφέας), Jeremiah R. Brown (Συγγραφέας)
• Μορφή: Βιβλίο
• Έκδοση: BMC, 2022-06-01T00:00:00Z.
• Θέματα: article
• Διαθέσιμο Online: Connect to this object online.

Abstract 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...