Using predicted length of stay to define treatment and model costs in hospitalized adults with serious illness: an evaluation of palliative care.

ABSTRACT:

Background

Economic research on hospital palliative care faces major challenges. Observational studies using routine data encounter difficulties because treatment timing is not under investigator control and unobserved patient complexity is endemic. An individual's predicted LOS at admission offers potential advantages in this context.

Methods

We conducted a retrospective cohort study on adults admitted to a large cancer center in the United States between 2009 and 2015. We defined a derivation sample to estimate predicted LOS using baseline factors (N = 16,425) and an analytic sample for our primary analyses (N = 2674) based on diagnosis of a terminal illness and high risk of hospital mortality. We modelled our treatment variable according to the timing of first palliative

SUBMITTER: May P 

PROVIDER: S-EPMC8454145 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature