Predictors of High Profit and High Deficit Outliers under SwissDRG of a Tertiary Care Center.

ABSTRACT:

Principles

Case weights of Diagnosis Related Groups (DRGs) are determined by the average cost of cases from a previous billing period. However, a significant amount of cases are largely over- or underfunded. We therefore decided to analyze earning outliers of our hospital as to search for predictors enabling a better grouping under SwissDRG.

Methods

28,893 inpatient cases without additional private insurance discharged from our hospital in 2012 were included in our analysis. Outliers were defined by the interquartile range method. Predictors for deficit and profit outliers were determined with logistic regressions. Predictors were shortlisted with the LASSO regularized logistic regression method and compared to results of Random forest analysis. 10 of these parameters were s

SUBMITTER: Mehra T 

PROVIDER: S-EPMC4627843 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature