Literature DB >> 33948862

Specialty-Specific Readmission Risk Models Outperform General Models in Estimating Hepatopancreatobiliary Surgery Readmission Risk.

Florence E Turrentine1,2, Timothy L McMurry2,3, Mark E Smolkin2,3, R Scott Jones1,2, Victor M Zaydfudim4,5.   

Abstract

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.
© 2021. The Society for Surgery of the Alimentary Tract.

Entities:  

Keywords:  ACS NSQIP; Hepatobiliary surgery; Pancreatic surgery; Readmission; Readmission reduction; Readmission risk prediction

Mesh:

Year:  2021        PMID: 33948862     DOI: 10.1007/s11605-021-05023-z

Source DB:  PubMed          Journal:  J Gastrointest Surg        ISSN: 1091-255X            Impact factor:   3.452


  26 in total

1.  Assessing readmission after general, vascular, and thoracic surgery using ACS-NSQIP.

Authors:  Donald J Lucas; Adil Haider; Elliot Haut; Rebecca Dodson; Christopher L Wolfgang; Nita Ahuja; John Sweeney; Timothy M Pawlik
Journal:  Ann Surg       Date:  2013-09       Impact factor: 12.969

2.  A nomogram for estimating the risk of unplanned readmission after major surgery.

Authors:  Michael D Williams; Florence E Turrentine; George J Stukenborg
Journal:  Surgery       Date:  2015-02-07       Impact factor: 3.982

3.  Risk stratification for readmission after major hepatectomy: development of a readmission risk score.

Authors:  Michael E Egger; Malcolm H Squires; David A Kooby; Shishir K Maithel; Clifford S Cho; Sharon M Weber; Emily R Winslow; Robert C G Martin; Kelly M McMasters; Charles R Scoggins
Journal:  J Am Coll Surg       Date:  2014-12-20       Impact factor: 6.113

Review 4.  General and vascular surgery readmissions: a systematic review.

Authors:  Jason T Wiseman; Amanda M Guzman; Sara Fernandes-Taylor; Travis L Engelbert; R Scott Saunders; K Craig Kent
Journal:  J Am Coll Surg       Date:  2014-05-22       Impact factor: 6.113

5.  Readmission incidence and associated factors after a hepatic resection at a major hepato-pancreatico-biliary academic centre.

Authors:  Gaya Spolverato; Aslam Ejaz; Yuhree Kim; Mattew Weiss; Christopher L Wolfgang; Kenzo Hirose; Timothy M Pawlik
Journal:  HPB (Oxford)       Date:  2014-04-09       Impact factor: 3.647

6.  Costs of hepato-pancreato-biliary surgery and readmissions in privately insured US patients.

Authors:  Afif N Kulaylat; Jane R Schubart; Eric W Schaefer; Christopher S Hollenbeak; Amanda B Cooper; Niraj J Gusani
Journal:  J Surg Res       Date:  2015-05-07       Impact factor: 2.192

7.  A novel risk scoring system reliably predicts readmission after pancreatectomy.

Authors:  Vicente Valero; Joshua C Grimm; Arman Kilic; Russell L Lewis; Jeffrey J Tosoian; Jin He; James F Griffin; John L Cameron; Matthew J Weiss; Charles M Vollmer; Christopher L Wolfgang
Journal:  J Am Coll Surg       Date:  2015-01-08       Impact factor: 6.113

8.  Timing and severity of post-discharge morbidity after hepatectomy.

Authors:  Mustafa Raoof; Aaron Lewis; Leanne Goldstein; Sinziana Dumitra; Susanne G Warner; Gagandeep Singh; Yuman Fong; Laleh Melstrom
Journal:  HPB (Oxford)       Date:  2017-01-26       Impact factor: 3.647

9.  Influence of patient, physician, and hospital factors on 30-day readmission following pancreatoduodenectomy in the United States.

Authors:  Omar Hyder; Rebecca M Dodson; Hari Nathan; Eric B Schneider; Matthew J Weiss; John L Cameron; Michael A Choti; Martin A Makary; Kenzo Hirose; Christopher L Wolfgang; Joseph M Herman; Timothy M Pawlik
Journal:  JAMA Surg       Date:  2013-12       Impact factor: 14.766

10.  Factors affecting readmission rates after pancreatectomy.

Authors:  Jonathan J Hue; Suparna Navale; Nicholas Schiltz; Siran M Koroukian; John B Ammori
Journal:  J Hepatobiliary Pancreat Sci       Date:  2020-02-16       Impact factor: 7.027

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