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Specialty-Specific Readmission Risk Models Outperform General Models in Estimating Hepatopancreatobiliary Surgery
Florence E Turrentine1,2, Timothy L McMurry2,3, Mark E Smolkin2,3
1Department of Surgery, University of Virginia, Box 800709, Charlottesville, VA, 22908-0709, USA.
Background:
Readmissions are costly and inconvenient for patients, and occur frequently in hepatopancreatobiliary (HPB) surgery practice. Readmission prediction tools exist, but most have not been designed or tested in the HPB patient population.
Methods:
Pancreatectomy and hepatectomy operation-specific readmission models defined as subspecialty readmission risk assessments (SRRA) were developed using clinically relevant data from merged 2014-15 ACS NSQIP Participant Use Data Files and Procedure Targeted datasets. The two derived procedure-specific models were tested along with 6 other readmission models in institutional validation cohorts in patients who had pancreatectomy or hepatectomy, respectively, between 2013 and 2017. Models were compared using area under the receiver operating characteristic curves (AUC).
Results:
A total of 16,884 patients (9169 pancreatectomy and 7715 hepatectomy) were included in the derivation models. A total of 665 patients (383 pancreatectomy and 282 hepatectomy) were included in the validation models. Specialty-specific readmission models outperformed general models. AUC characteristics of the derived pancreatectomy and hepatectomy SRRA (pancreatectomy AUC=0.66, hepatectomy AUC=0.74), modified Readmission After Pancreatectomy (AUC=0.76), and modified Readmission Risk Score for hepatectomy (AUC=0.78) outperformed general models for readmission risk: LOS/2 + ASA integer-based score (pancreatectomy AUC=0.58, hepatectomy AUC=0.66), LACE Index (pancreatectomy AUC=0.54, hepatectomy AUC=0.62), Unplanned Readmission Nomogram (pancreatectomy AUC=0.52, hepatectomy AUC=0.55), and institutional ARIA (pancreatectomy AUC=0.46, hepatectomy AUC=0.58).
Conclusion:
HPB readmission risk models using 30-day subspecialty-specific data outperform general readmission risk tools. Hospitals and practices aiming to decrease readmissions in HPB surgery patient populations should use specialty-specific readmission reduction strategies.
