Nursing critical patient severity classification system predicts outcomes in patients admitted to surgical intensive care units: use of data from clinical data repository.
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.
College of Nursing, Yonsei University, Seoul, South Korea.
Mona
M
Choi
JuHee
J
Lee
Mi Jung
MJ
Ahn
YoungAh
Y
Kim
D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D003422:Critical Care / Q000706:statistics & numerical data; D064648:Critical Care Nursing / Q000706:statistics & numerical data*; D005260:Female; D017052:Hospital Mortality; D006801:Humans; D007362:Intensive Care Units / Q000706:statistics & numerical data*; D007902:Length of Stay / Q000706:statistics & numerical data*; D008297:Male; D016347:Medical Records Systems, Computerized / Q000706:statistics & numerical data*; D008875:Middle Aged; D009730:Nursing Assessment / Q000706:statistics & numerical data*; D056910:Republic of Korea / Q000453:epidemiology; D018570:Risk Assessment; D012720:Severity of Illness Index; D013503:Surgery Department, Hospital / Q000706:statistics & numerical data; D016019:Survival Analysis; D055815:Young Adult