Nursing critical patient severity classification system predicts outcomes in patients admitted to surgical intensive care units: Use of data from clinical data repository

Abstract

To examine the Critical Patient Severity Classification System (CPSCS) recorded by nurses to predict ICU and hospital lengths of stay and mortality, data were drawn from patients admitted to 2 surgical intensive care units (SICUs) at a university hospital in Seoul, South Korea in 2010. This retrospective study used a large data set retrieved from the Clinical Data Repository System. Among 1432 patients, the mean grade of CPSCS was 4.9 out of 6, which indicated that the subjects had generally severe conditions. The CPSCS was a statistically significant predictor of ICU and hospital LOS and mortality when patients' demographic characteristics were adjusted. In the era of emphasis on using big data, analysis of nursing assessment data should be evaluated to show importance of nursing contribution to predict patients' clinical outcomes. © 2013 IMIA and IOS Press.