While baseline characteristics may be associated with worse clinical outcomes, interactions between combined factors can have an impact that exceeds solely additive effects. In this exploratory study, we used the Lasso method and multivariable linear regression on a large inpatient dataset to identify diagnosis interactions that are independently associated with increased length of stay.

Learning Objective: The participant will learn a complex approach with a series of techniques used to identify diagnosis interactions increasing the length of stay independently of other risk factors.

Authors:

Patrick Beeler, University Hospital Zurich
Karol Tarcak (Presenter)
University Hospital Zurich

Ulrike Held, University of Zurich
Edouard Battegay, University Hospital Zurich

Presentation Materials:

• Abstract/Manuscript - 1