Literature DB >> 31617657

Hospital characteristics, rather than surgical volume, predict length of stay following colorectal cancer surgery.

Don Vicendese1,2, Luc Te Marvelde1,2, Peter D McNair3,4, Kathryn Whitfield2, Dallas R English1,5, Souhaib Ben Taieb6, Rob J Hyndman6, Robert Thomas7.   

Abstract

OBJECTIVE: Length of hospital stay (LOS) is considered a vital component for successful colorectal surgery treatment. Evidence of an association between hospital surgery volume and LOS has been mixed. Data modelling techniques may give inconsistent results that adversely impact conclusions. This study applied techniques to overcome possible modelling drawbacks.
METHOD: An additive quantile regression model formulated to isolate hospital contextual effects was applied to every colorectal surgery for cancer conducted in Victoria, Australia, between 2005 and 2015, involving 28,343 admissions in 90 Victorian hospitals. The model compared hospitals' operational efficiencies regarding LOS.
RESULTS: Hospital LOS operational efficiencies for colorectal cancer surgery varied markedly between the 90 hospitals and were independent of volume. This result was adjusted for pertinent patient and hospital characteristics.
CONCLUSION: No evidence was found that higher annual surgery volume was associated with lower LOS for patients undergoing colorectal cancer surgery. Our model showed strong evidence that differences in LOS efficiency between hospitals was driven by hospital contextual effects that were not predicted by provider volume. Further study is required to elucidate these inherent differences between hospitals. Implications for public health: Our model indicated improved efficiency would benefit the patient and medical system by lowering LOS and reducing expenditure by more than $3 million per year.
© 2019 The Authors.

Entities:  

Keywords:  cancer; colorectal; length of stay; quantile regression; surgery

Mesh:

Year:  2019        PMID: 31617657     DOI: 10.1111/1753-6405.12932

Source DB:  PubMed          Journal:  Aust N Z J Public Health        ISSN: 1326-0200            Impact factor:   2.939


  5 in total

1.  Effectiveness of care transition strategies for colorectal cancer patients: a systematic review and meta-analysis.

Authors:  Letícia Flores Trindade; Julia Estela Willrich Boell; Elisiane Lorenzini; Wilson Cañon Montañez; Michelle Malkiewiez; Edith Pituskin; Adriane Cristina Bernat Kolankiewicz
Journal:  Support Care Cancer       Date:  2022-04-22       Impact factor: 3.359

2.  Center-Level Procedure Volume Does Not Predict Failure-to-Rescue After Severe Complications of Oncologic Colon and Rectal Surgery.

Authors:  Miriam Lillo-Felipe; Rebecka Ahl Hulme; Maximilian Peter Forssten; Gary A Bass; Yang Cao; Peter Matthiessen; Shahin Mohseni
Journal:  World J Surg       Date:  2021-08-27       Impact factor: 3.352

3.  Data analytics and artificial intelligence in predicting length of stay, readmission, and mortality: a population-based study of surgical management of colorectal cancer.

Authors:  Shamsul Masum; Adrian Hopgood; Samuel Stefan; Karen Flashman; Jim Khan
Journal:  Discov Oncol       Date:  2022-02-28

4.  The prediction of hospital length of stay using unstructured data.

Authors:  Jan Chrusciel; François Girardon; Lucien Roquette; David Laplanche; Antoine Duclos; Stéphane Sanchez
Journal:  BMC Med Inform Decis Mak       Date:  2021-12-18       Impact factor: 2.796

5.  Impact of surgeon and hospital factors on length of stay after colorectal surgery systematic review.

Authors:  Zubair Bayat; Keegan Guidolin; Basheer Elsolh; Charmaine De Castro; Erin Kennedy; Anand Govindarajan
Journal:  BJS Open       Date:  2022-09-02
  5 in total

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