BACKGROUND: Institutions are now incentivized to decrease rates of preventable readmissions. The purpose of this study was to examine readmissions following open ventral hernia repair (VHR), to ultimately create a model to preoperatively identify high-risk patients. STUDY DESIGN: Utilizing the 2011 and 2012 ACS-NSQIP datasets, patients undergoing open VHR were identified by CPT codes. Patients who were readmitted in 2011 within 30 days of the procedure were compared to those who were not with regard to preoperative and operative characteristics. A bootstrap analysis was performed to identify internally validated risk factors to be included in the final logistic regression, which was utilized to create a weighted model to predict the risk of readmission. This model was then validated with VHR patients in 2012. RESULTS: Overall, 10,745 patients were included for model generation. Of these, 850 (7.9%) patients were readmitted within 30 days. The final bootstrap analysis demonstrated that active smoking, ASA ≥ 3, a history of bleeding disorder or anemia, long operative time, inpatient status, and concurrent panniculectomy were all independently associated with readmission following ventral hernia repair. Significant variables were assigned a weighted score, ranging from 1 to 3. Each patient was then placed into one of four cohorts according to their summed score. The internally validated model [Hernia Readmission Risk (HERR) Score] demonstrated that risk increased in a linear fashion, with the highest risk cohort having a 21% risk of 30-day readmission. CONCLUSIONS: Perioperative predictors of readmission following VHR include smoking, ASA score, operative magnitude, concurrent panniculectomy, and preoperative anemia and bleeding disorders. The presented model based on these factors can aid in perioperative risk stratification for readmission.
BACKGROUND: Institutions are now incentivized to decrease rates of preventable readmissions. The purpose of this study was to examine readmissions following open ventral hernia repair (VHR), to ultimately create a model to preoperatively identify high-risk patients. STUDY DESIGN: Utilizing the 2011 and 2012 ACS-NSQIP datasets, patients undergoing open VHR were identified by CPT codes. Patients who were readmitted in 2011 within 30 days of the procedure were compared to those who were not with regard to preoperative and operative characteristics. A bootstrap analysis was performed to identify internally validated risk factors to be included in the final logistic regression, which was utilized to create a weighted model to predict the risk of readmission. This model was then validated with VHR patients in 2012. RESULTS: Overall, 10,745 patients were included for model generation. Of these, 850 (7.9%) patients were readmitted within 30 days. The final bootstrap analysis demonstrated that active smoking, ASA ≥ 3, a history of bleeding disorder or anemia, long operative time, inpatient status, and concurrent panniculectomy were all independently associated with readmission following ventral hernia repair. Significant variables were assigned a weighted score, ranging from 1 to 3. Each patient was then placed into one of four cohorts according to their summed score. The internally validated model [Hernia Readmission Risk (HERR) Score] demonstrated that risk increased in a linear fashion, with the highest risk cohort having a 21% risk of 30-day readmission. CONCLUSIONS: Perioperative predictors of readmission following VHR include smoking, ASA score, operative magnitude, concurrent panniculectomy, and preoperative anemia and bleeding disorders. The presented model based on these factors can aid in perioperative risk stratification for readmission.
Authors: Mylan T Nguyen; Linda T Li; Stephanie C Hicks; Jessica A Davila; James W Suliburk; Mimi Leong; Lillian S Kao; David H Berger; Mike K Liang Journal: Am J Surg Date: 2013-10-18 Impact factor: 2.565
Authors: Jonas A Nelson; John P Fischer; Cyndi Chung; Liza C Wu; Joseph M Serletti; Stephen J Kovach Journal: Plast Reconstr Surg Date: 2014-08 Impact factor: 4.730
Authors: John P Fischer; Ari M Wes; Jonas A Nelson; Joseph M Serletti; Stephen J Kovach Journal: Plast Reconstr Surg Date: 2013-09 Impact factor: 4.730
Authors: P A Baltodano; Y Webb-Vargas; K C Soares; C W Hicks; C M Cooney; P Cornell; K K Burce; T M Pawlik; F E Eckhauser Journal: Hernia Date: 2015-08-19 Impact factor: 4.739
Authors: Julie L Holihan; Juan R Flores-Gonzalez; Jiandi Mo; Tien C Ko; Lillian S Kao; Mike K Liang Journal: World J Surg Date: 2017-05 Impact factor: 3.352