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

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

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

2020
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Overview
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. 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. 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. 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. 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.