TY - JOUR
T1 - Real-time automated clinical deterioration alerts predict thirty-day hospital readmission
AU - Micek, Scott T.
AU - Samant, Maanasi
AU - Bailey, Thomas
AU - Chen, Yixin
AU - Lu, Chenyang
AU - Heard, Kevin
AU - Kollef, Marin H.
N1 - Publisher Copyright:
© 2016 Society of Hospital Medicine
PY - 2016/11/1
Y1 - 2016/11/1
N2 - INTRODUCTION: Clinical deterioration alerts (CDAs) are increasingly employed to identify deteriorating patients. METHODS: We performed a retrospective study to determine whether CDAs predict 30-day readmission. Patients admitted to 8 general medicine units were assessed for all-cause 30-day readmission. RESULTS: Among 3015 patients, 567 (18.8%) were readmitted within 30 days. Patients triggering a CDA (n = 1141; 34.4%) were more likely to have a 30-day readmission (23.6% vs 15.9%; P < 0.001). Logistic regression identified triggering of a CDA to be independently associated with 30-day readmission (odds ratio [OR]: 1.40; 95% confidence interval [CI]: 1.26-1.55; P = 0.001). Other predictors were: an emergency department visit in the previous 6 months (OR: 1.23; 95% CI:, 1.20-1.26; P < 0.001), increasing age (OR: 1.01; 95% CI: 1.01-1.02; P = 0.003), presence of connective tissue disease (OR: 1.63; 95% CI: 1.34-1.98; P = 0.012), diabetes mellitus with end-organ complications (OR: 1.23; 95% CI: 1.13-1.33; P = 0.010), chronic renal disease (OR: 1.16; 95% CI: 1.08-1.24; P = 0.034), cirrhosis (OR: 1.25; 95% CI: 1.17-1.33; P < 0.001), and metastatic cancer (OR: 1.12; 95% CI: 1.08-1.17; P = 0.002). Addition of the CDA to the other predictors added only modest incremental value for the prediction of hospital readmission. CONCLUSIONS: Readily identifiable clinical variables can be identified that predict 30-day readmission. It may be important to include these variables in existing prediction tools if pay for performance and across-institution comparisons are to be “fair” to institutions that care for more seriously ill patients. Journal of Hospital Medicine 2016;11:768–772.
AB - INTRODUCTION: Clinical deterioration alerts (CDAs) are increasingly employed to identify deteriorating patients. METHODS: We performed a retrospective study to determine whether CDAs predict 30-day readmission. Patients admitted to 8 general medicine units were assessed for all-cause 30-day readmission. RESULTS: Among 3015 patients, 567 (18.8%) were readmitted within 30 days. Patients triggering a CDA (n = 1141; 34.4%) were more likely to have a 30-day readmission (23.6% vs 15.9%; P < 0.001). Logistic regression identified triggering of a CDA to be independently associated with 30-day readmission (odds ratio [OR]: 1.40; 95% confidence interval [CI]: 1.26-1.55; P = 0.001). Other predictors were: an emergency department visit in the previous 6 months (OR: 1.23; 95% CI:, 1.20-1.26; P < 0.001), increasing age (OR: 1.01; 95% CI: 1.01-1.02; P = 0.003), presence of connective tissue disease (OR: 1.63; 95% CI: 1.34-1.98; P = 0.012), diabetes mellitus with end-organ complications (OR: 1.23; 95% CI: 1.13-1.33; P = 0.010), chronic renal disease (OR: 1.16; 95% CI: 1.08-1.24; P = 0.034), cirrhosis (OR: 1.25; 95% CI: 1.17-1.33; P < 0.001), and metastatic cancer (OR: 1.12; 95% CI: 1.08-1.17; P = 0.002). Addition of the CDA to the other predictors added only modest incremental value for the prediction of hospital readmission. CONCLUSIONS: Readily identifiable clinical variables can be identified that predict 30-day readmission. It may be important to include these variables in existing prediction tools if pay for performance and across-institution comparisons are to be “fair” to institutions that care for more seriously ill patients. Journal of Hospital Medicine 2016;11:768–772.
UR - http://www.scopus.com/inward/record.url?scp=84973390612&partnerID=8YFLogxK
U2 - 10.1002/jhm.2617
DO - 10.1002/jhm.2617
M3 - Article
C2 - 27256009
AN - SCOPUS:84973390612
SN - 1553-5592
VL - 11
SP - 768
EP - 772
JO - Journal of hospital medicine
JF - Journal of hospital medicine
IS - 11
ER -