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Drivers Of Readmissions

Numbers and letters correspond to the affiliation list. Published by Elsevier Inc.Recommended articlesCiting articles ElsevierAbout ScienceDirectRemote accessShopping cartContact and supportTerms and conditionsPrivacy policyCookies are used by this site. Hammermeister, Mark R. The preoperative model based on patient demographics and comorbidities predicted readmission risk with a low C index of .67; the top five predictors of readmission were American Society of Anesthesiologists class,

Please enable JavaScript to use all the features on this page.Journal of Vascular SurgeryVolume 64, Issue 1, July 2016, Pages 185-194.e3Clinical research studyDrivers of readmissions in vascular surgery patientsPresented during Scientific Author links open the author workspace.William G.HendersonPhD, MPHb. Conclusions: Readmissions in vascular surgery patients are mainly driven by postoperative complications identified after discharge. Multivariable forward selection logistic regression analysis was used to model the relative contributions of patient comorbidities, operative factors, and postoperative complications for readmission.RESULTS: The unplanned readmission rate was 9.3%. https://www.ncbi.nlm.nih.gov/pubmed/27038838

Results: The unplanned readmission rate was 9.3%. Thus, efforts to reduce vascular readmissions focusing on inpatient hospital data may prove ineffective. The preoperative model based on patient demographics and comorbidities predicted readmission risk with a low C index of .67; the top five predictors of readmission were American Society of Anesthesiologists class, Multivariable forward selection logistic regression analysis was used to model the relative contributions of patient comorbidities, operative factors, and postoperative complications for readmission.ResultsThe unplanned readmission rate was 9.3%.

Results: The unplanned readmission rate was 9.3%. We sought to study the multiple potential drivers of readmission and to create a model for predicting the risk of readmission in vascular patients.MethodsThe 2012-2013 American College of Surgeons National Surgical Henderson, W. The top five predictors of readmission in the final model based on patient comorbidities and postoperative complications were postdischarge deep space infection, superficial surgical site infection, pneumonia, myocardial infection, and sepsis.ConclusionsReadmissions

Click to expose these in author workspace. Multivariable forward selection logistic regression analysis was used to model the relative contributions of patient comorbidities, operative factors, and postoperative complications for readmission. It also provides examples of innovative approaches to reduce readmissions that are being tested around the country. their explanation Thus, efforts to reduce vascular readmissions focusing on inpatient hospital data may prove ineffective.

However, the inclusion of complications identified after discharge from the hospital appreciably improved the predictive power of the model (C index, .78). Multivariable forward selection logistic regression analysis was used to model the relative contributions of patient comorbidities, operative factors, and postoperative complications for readmission. Importantly, postoperative complications identified before discharge from the hospital were not a strong predictor of readmission as the model using predischarge postoperative complications had a similar C index to our preoperative Available from, DOI: 10.1016/j.jvs.2016.02.024 Glebova, Natalia O.; Bronsert, Michael; Hammermeister, Karl E.; Nehler, Mark R.; Gibula, Douglas R.; Malas, Mahmoud B.; Black, James H.; Henderson, William G. / Drivers of readmissions

Results: The unplanned readmission rate was 9.3%. http://www.texasrhp6.com/examining-the-drivers-of-readmissions-and-reducing-unnecessary-readmissions-for-better-patient-care/ Conclusions: Readmissions in vascular surgery patients are mainly driven by postoperative complications identified after discharge. Malas, James H. Numbers and letters correspond to the affiliation list.

Click to expose these in author workspace. E., Nehler, M. We sought to study the multiple potential drivers of readmission and to create a model for predicting the risk of readmission in vascular patients. Results: The unplanned readmission rate was 9.3%.

Numbers and letters correspond to the affiliation list. The postoperative model using operative factors and postoperative complications predicted readmission risk better (C index, .78); postoperative complications were the most significant predictor of readmission, overpowering patient comorbidities. ScienceDirect ® is a registered trademark of Elsevier B.V.RELX Group Skip to main content Home Profiles Research Units Research Output Drivers of readmissions in vascular surgery patients Natalia O. Numbers and letters correspond to the affiliation list.

Henderson School of Medicine Research output: Contribution to journal › Article Abstract Objective: Postoperative readmissions are frequent in vascular surgery patients, but it is not clear which factors are the main We sought to study the multiple potential drivers of readmission and to create a model for predicting the risk of readmission in vascular patients. Author links open the author workspace.MichaelBronsertPhD, MSb.

Specifically, the relative contributions of patient comorbidities vs those of operative factors and postoperative complications are unknown.

or its licensors or contributors. Author links open the author workspace.Natalia O.GlebovaMD, PhDa. Nehler, Douglas R. Click to expose these in author workspace.

Importantly, postoperative complications identified before discharge from the hospital were not a strong predictor of readmission as the model using predischarge postoperative complications had a similar C index to our preoperative The postoperative model using operative factors and postoperative complications predicted readmission risk better (C index, .78); postoperative complications were the most significant predictor of readmission, overpowering patient comorbidities. R., Malas, M. Post navigation ← Previous Next → Webinars & Meetings Resources Behavioral Health General Milestone Documents Patient-Centered Medical Homes Performance Improvement Primary Care Project Management Readmissions SUBMIT RESOURCES

Importantly, postoperative complications identified before discharge from the hospital were not a strong predictor of readmission as the model using predischarge postoperative complications had a similar C index to our preoperative Our study suggests that interventions to reduce vascular readmissions should focus on prompt identification of modifiable postdischarge complications.Choose an option to locate/access this article:Check if you have access through your login The top five predictors of readmission in the final model based on patient comorbidities and postoperative complications were postdischarge deep space infection, superficial surgical site infection, pneumonia, myocardial infection, and sepsis.