Readmission following ventral hernia repair: a model derived from the ACS-NSQIP datasets

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• 作者：J. A. Nelson (1)
  J. Fischer (1)
  C. C. Chung (1)
  J. Wink (1)
  A. Wes (1)
  J. M. Serletti (1)
  S. Kovach (1)
  
  1. Division of Plastic Surgery ; Hospital of the University of Pennsylvania ; 3400 Spruce Street ; Philadelphia ; PA ; 19104 ; USA
  
• 关键词：Readmission ; Ventral hernia repair ; NSQIP ; Complications ; Outcomes
• 刊名：Hernia
• 出版年：2015
• 出版时间：February 2015
• 年：2015
• 卷：19
• 期：1
• 页码：125-133
• 全文大小：238 KB
• 参考文献：1. HIMSS: reducing readmissions鈥攖op ways information technology can help (Internet) (cited 2013 September 30). http://www.himss.org/files/HIMSSorg/content/files/ControlReadmissionsTechnology.pdf
  2. Readmissions reduction program: centers for medicare and medicaid services (Internet) (cited 2013 September 28). http://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/Readmissions-Reduction-Program.html
  3. Rau J (2012) Medicare to Penalize 2,217 hospitals for excess readmissions. Kaiser Health News. [Internet] [cited 2013 September 30]. http://www.kaiserhealthnews.org/stories/2012/august/13/medicare-hospitals-readmissions-penalties.aspx
  4. Caramenico A (2013) 鈥淢edicare slaps two-thirds of US hospitals with readmission penalties.鈥?Fierce Healthcare. http://www.fiercehealthcare.com/story/medicare-slaps-two-thirds-us-hospitals-readmission-penalties/2013-08-05. Accessed 4 Nov 2013
  5. Gordon D 鈥淲orking to avoid next CMS penalties: surgery readmissions鈥? Curaspan Health Group. http://connect.curaspan.com/articles/working-avoid-next-cms-penalties-surgery-readmissions. Accessed 4 Nov 2013
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  13. ACS-NSQIP. American College of Surgeon National Surgical Quality Improvement Program. http://site.acsnsqip.org/participant-usedata-file/. Accessed 1 December 2012
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  18. Fischer JP, Wes AM, Nelson JA et al (2013) Factors associated with readmission following plastic surgery: a review of 10,669 procedures from the 2011 American College of Surgeons National Surgical Quality Improvement Program data set. Plast Reconstr Surg 132(3):666鈥?74 CrossRef
  19. Nelson JA, Fischer JP, Chung CU, et al. (2014) Risk of readmission following immediate breast reconstruction: results from the 2011 ACS-NSQIP datasets. Plast Reconstr Surg 134(2):193e鈥?01e CrossRef
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• 刊物类别：Medicine
• 刊物主题：Medicine & Public Health
  Abdominal Surgery
  
• 出版者：Springer Paris
• ISSN：1248-9204

文摘

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聽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聽VHR patients in 2012. Results Overall, 10,745 patients were included for model generation. Of these, 850 (7.9聽%) patients were readmitted within 30聽days. The final bootstrap analysis demonstrated that active smoking, ASA聽鈮ヂ?, 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聽% 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.