Prediction of early unplanned intensive care unit readmission in a UK tertiary care hospital: a cross-sectional machine learning approach.

ABSTRACT:

Objectives

Unplanned readmissions to the intensive care unit (ICU) are highly undesirable, increasing variance in care, making resource planning difficult and potentially increasing length of stay and mortality in some settings. Identifying patients who are likely to suffer unplanned ICU readmission could reduce the frequency of this adverse event.

Setting

A single academic, tertiary care hospital in the UK.

Participants

A set of 3326 ICU episodes collected between October 2014 and August 2016. All records were of patients who visited an ICU at some point during their stay. We excluded patients who were ≤16 years of age; visited ICUs other than the general and neurosciences ICU; were missing crucial electronic patient record measurements; or had indeterminate ICU disc

SUBMITTER: Desautels T 

PROVIDER: S-EPMC5640090 | biostudies-literature | 2017 Sep

REPOSITORIES: biostudies-literature