Proposing a validated clinical app predicting hospitalization cost for extracranial-intracranial bypass surgery.

ABSTRACT:

Object

United States healthcare reforms are focused on curtailing rising expenditures. In neurosurgical domain, limited or no data exists identifying potential modifiable targets associated with high-hospitalization cost for cerebrovascular procedures such as extracranial-intracranial (ECIC) bypass. Our study objective was to develop a predictive model of initial cost for patients undergoing bypass surgery.

Methods

In an observational cohort study, we analyzed patients registered in the Nationwide Inpatient Sample (2002-2011) that underwent ECIC bypass. Split-sample 1:1 randomization of the study cohort was performed. Hospital cost data was modelled using ordinary least square to identity potential drivers impacting initial hospitalization cost. Subsequently, a validated cli

SUBMITTER: Sun H 

PROVIDER: S-EPMC5659612 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature