Who bounces back? Physiologic and other predictors of intensive care unit readmission.
OBJECTIVE
To determine the influence of changes in acute physiology scores (APS) and other patient characteristics on predicting intensive care unit (ICU) readmission.


METHODS
Secondary analysis of a prospective cohort study.


METHODS
Single large university medical intensive care unit.


METHODS
A total of 4,684 consecutive admissions from January 1, 1994, to April 1, 1998, to the medical ICU.


METHODS
None.


RESULTS
The independent influence of patient characteristics, including daily APS, admission diagnosis, treatment status, and admission location, on ICU readmission was evaluated using logistic regression. After accounting for first ICU admission deaths, 3,310 patients were "at-risk" for ICU readmission and 317 were readmitted (9.6%). Hospital mortality was five times higher (43% vs. 8%; p < .0001), and length of stay was two times longer (16 +/- 16 vs. 32 +/- 28 days; p < .001) in readmitted patients. Mean discharge APS was significantly higher in the readmitted group compared with the not readmitted group (43 +/- 19 vs. 34 +/- 18; p > .01). Significant independent predictors of ICU readmission included discharge APS >40 (odds ratio [OR] 2.1; 95% confidence interval [CI] 1.6-2.7; p < .0001), admission to the ICU from a general medicine ward (Floor) (OR 1.9; 95% CI 1.4-2.6; p < .0001), and transfer to the ICU from other hospital (Transfer) (OR 1.7; 95% CI 1.3-2.3; p < .01). The overall model calibration and discrimination were (H-L chi2 = 3.8, df = 8; p = .85) and (receiver operating characteristic 0.67), respectively.


CONCLUSIONS
Patients readmitted to medical ICUs have significantly higher hospital lengths of stay and mortality. ICU readmissions may be more common among patients who respond poorly to treatment as measured by increased severity of illness at first ICU discharge and failure of prior therapy at another hospital or on a general medicine unit. Tertiary care ICUs may have higher than expected readmission rates and mortalities, even when accounting for severity of illness, if they care for significant numbers of transferred patients.
Rosenberg
A L
AL
Robert Wood Johnson Clinical Scholars Program, the Department of Anesthesiology and Critical Care Medicine, The University of Michigan Health System, Ann Arbor, MI, USA.
Hofer
T P
TP
Hayward
R A
RA
Strachan
C
C
Watts
C M
CM
D018806:APACHE; D000046:Academic Medical Centers; D000368:Aged; D000704:Analysis of Variance; D015897:Comorbidity; D016638:Critical Illness / Q000145:classification* / Q000401:mortality; D016002:Discriminant Analysis; 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; D008824:Michigan / Q000453:epidemiology; D008875:Middle Aged; D015233:Models, Statistical; D016017:Odds Ratio; D010359:Patient Readmission / Q000706:statistics & numerical data*; D010360:Patient Transfer / Q000706:statistics & numerical data; D011237:Predictive Value of Tests; D011446:Prospective Studies; D012372:ROC Curve; D012307:Risk Factors; D013997:Time Factors; D016896:Treatment Outcome