Determining the association of insurance coverage and survival outcomes in patients with olfactory neuroblastoma utilizing machine learning

David Fenton; Ashley Diaz; Haobin Chen; Mikhayla Armstrong; Samuel Auger; Daniel Bujnowski; Alena Pedroza; Sean Polster; Paramita Das; Peleg Horowitz; Christopher Roxbury

doi:10.1002/alr.23172

Determining the association of insurance coverage and survival outcomes in patients with olfactory neuroblastoma utilizing machine learning

Int Forum Allergy Rhinol. 2023 Nov;13(11):2082-2085. doi: 10.1002/alr.23172. Epub 2023 May 21.

Authors

Affiliations

¹ Pritzker School of Medicine, University of Chicago, Chicago, Illinois, USA.
² Program in Quantitative Biomedical Sciences, Geisel School of Medicine, Dartmouth College, Hanover, New Hampshire, USA.
³ Department of Surgery, Section of Otolaryngology, University of Chicago, Chicago, Illinois, USA.
⁴ Stritch School of Medicine, Loyola University Chicago, Maywood, Illinois, USA.
⁵ Univerisity of Chicago, Division of the Biological Sciences, Chicago, Illinois, USA.
⁶ Department of Surgery, Section of Neurological Surgery, University of Chicago, Chicago, Illinois, USA.

PMID: 37132277
DOI: 10.1002/alr.23172

Abstract

We use machine learning to examine health insurance and mortality in olfactory neuroblastoma. Private insurance significantly improved survival even after adjusting for confounders. The regression model also found no statistical difference between Medicare and no insurance.

Keywords: olfaction; olfactory disorders; sinus surgery.