Complications after discharge predict readmission after colorectal surgery View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2019-04

AUTHORS

Jeremy Albright, Farwa Batool, Robert K. Cleary, Andrew J. Mullard, Edward Kreske, Jane Ferraro, Scott E. Regenbogen

ABSTRACT

BACKGROUND: Health care providers, hospitals, and pay-for-performance programs are focused on strategies identifying patients at highest risk for re-admission after colorectal surgery. The study objective was to determine characteristics most associated with re-admission after elective colorectal surgery using a conceptual framework approach. METHODS: This is an observational study of Michigan Surgical Quality Collaborative clinical registry data for 8962 colorectal surgery cases between July-2012 and April-2015. Separate mixed models were fit using known re-admission risk factors aligned in categories that may impact re-admissions by different mechanisms. Overall model discrimination was evaluated using Area Under the Curve estimated on a hold-out data set and examining differences in predicted versus observed re-admission across risk quintiles. RESULTS: The overall 30-day re-admission rate was 10.5%. From Model 1 to Model 6, discrimination of re-admission was poor until Model 6 (AUC, 0.56, 0.61, 0.65, 0.63, 0.72, 0.81). Differences for observed re-admission rates comparing 'very low' versus 'very high' risk strata from Model 1 to Model 6 were 6%, 11%, 15%, 14%, 20%, and 30% respectively, and all comparisons were significant (p < 0.01). Though there were significant predictors in the first five models, most were no longer significant when additional predictors were included in subsequent models. Complications identified after discharge significantly increased the likelihood of re-admission and were the strongest predictors. CONCLUSION: Statistical models that include complications identified after discharge predict re-admission. Strategies to reduce re-admission after colorectal surgery should emphasize prevention of complications and more effective interventions to manage and ameliorate evolving complications identified after discharge. More... »

PAGES

1216-1224

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s00464-018-6398-3

DOI

http://dx.doi.org/10.1007/s00464-018-6398-3

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1106366033

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/30167952


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