Tehran University of Medical Sciences (TUMS) Academic Journal of Surgery 2423-3218 2 3-4 2016 01 16 33 38 ENGLISH 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 Peivand Bastani Department of Health Service Administration, School of Management and Medical Information Science, Shiraz University of Medical Sciences, Shiraz, Iran 2016 01 16 2016 01 16 Background: Today, the effective use of limited health care resources is increasingly regarded. Reduction of the readmission is one of the key tools can improve health outcomes and considered as one of the control levers that reduces health costs. Identifying the causes of readmission to the hospital helps to utilize hospital beds and facilities a more efficiently. Methods: This case-control study had been conducted in general surgery (GS) wards in 2011-2012. Using chisquare test, t-test, and multiple regressions, we studied risk factors associated with readmission in both groups of case and control. Finally, the predictive power of the Length of stay, Acuity of illness, Co morbidity of the patient, 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 difference between the two groups in the following variables: age, sex, length of hospital stay, marital status, discharge season, congestive heart failure, diabetes and renal failure. The rate of readmission with LACE index which is compared 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 decision making for using hospital facilities efficiently. Identifying patients at risk of readmission and erforming training plan, ischarging and following up medical programs can reduce the rate of readmission and costs of hospital. Predicting readmission can be very effective but identifying an effective index is very difficult. https://ajs.tums.ac.ir/index.php/ajs/article/view/35 https://ajs.tums.ac.ir/index.php/ajs/article/download/35/26