Nahid Hatam - Department of Health Service Administration, School of Management and Medical Information Science, Shiraz University of Medical Sciences, Shiraz, Iran
Mehrdad Askarian - Department of Community Medicine, Shiraz Nephro–Urology Research Center, Shiraz University of Medical Sciences, Shiraz, Iran
Fahime Khamzade - Student Research Committee, School of Management and Medical Information Science, Shiraz University of Medical Sciences, Shiraz, Iran
Peyman Jafari - Department of Biostatistics, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran

Background: Today, the effective use of limited health care resources is increasingly regarded. Reduction ofthe readmission is one of the key tools can improve health outcomes and considered as one of the control leversthat reduces health costs. Identifying the causes of readmission to the hospital helps to utilize hospital beds andfacilities a more efficiently.Methods: This case-control study had been conducted in general surgery (GS) wards in 2011-2012. Using chisquaretest, t-test, and multiple regressions, we studied risk factors associated with readmission in both groupsof case and control. Finally, the predictive power of the Length of stay, Acuity of illness, Co morbidity of thepatient, Emergency (LACE) index was evaluated using receiver operating characteristic (ROC) curve.Results: About 20% of patients in GS wards were admitted within 30 days. There is a significant differencebetween the two groups in the following variables: age, sex, length of hospital stay, marital status, dischargeseason, congestive heart failure, diabetes and renal failure. The rate of readmission with LACE index which iscompared with the ROC curve shows that it is significant (P < 0.001 and Kappa = 0.22).Conclusions: Awareness of the prevalence and risk factors of readmission is effective in planning and decisionmaking for using hospital facilities efficiently. Identifying patients at risk of readmission and performingtraining plan, discharging and following up medical programs can reduce the rate of readmission and costs ofhospital. Predicting readmission can be very effective but identifying an effective index is very difficult.© 2015 Tehran University of Medical Sciences. All rights reserved.Citation: Hatam N, Askarian M, Khamzade F, Jafari P, Bastani P. Readmission Risk Factors in Patients ofGeneral Surgery Wards in Shiraz Hospitals: Applying LACE Index as a Predictive Indicator. Acad JSurg, 2015; 2(3-4): 33-8.

Receiver operating characteristic curve, General surgery, Hospitals, LACE index, Patients,Patient readmission, Risk factors