Modelling risk-adjusted variation in length of stay among Australian and New Zealand ICUs

Research output: Contribution to journalArticleResearchpeer-review

Abstract

Purpose Comparisons between institutions of intensive care unit (ICU) length of stay (LOS) are significantly confounded by individual patient characteristics, and currently there is a paucity of methods available to calculate risk-adjusted metrics. Methods We extracted de-identified data from the Australian and New Zealand Intensive Care Society (ANZICS) Adult Patient Database for admissions between January 1 2011 and December 31 2015. We used a mixed-effects log-normal regression model to predict LOS using patient and admission characteristics. We calculated a risk-adjusted LOS ratio (RALOSR) by dividing the geometric mean observed LOS by the exponent of the expected Ln-LOS for each site and year. The RALOSR is scaled such that values <1 indicate a LOS shorter than expected, while values >1 indicate a LOS longer than expected. Secondary mixed effects regression modelling was used to assess the stability of the estimate in units over time. Results During the study there were a total of 662, 525 admissions to 168 units (median annual admissions = 767, IQR:426-1121). The mean observed LOS was 3.21 days (median = 1.79 IQR = 0.92-3.52) over the entire period, and declined on average 1.97 hours per year (95% CI:1.76-2.18) from 2011 to 2015. The RALOSR varied considerably between units, ranging from 0.35 to 2.34 indicating large differences after accounting for case-mix. Conclusions There are large disparities in risk-adjusted LOS among Australian and New Zealand ICUs which may reflect differences in resource utilization.

Original languageEnglish
Article numbere0176570
Number of pages12
JournalPLoS ONE
Volume12
Issue number5
DOIs
Publication statusPublished - 1 May 2017

Cite this

@article{17f827c58a1f4861aff08cec549b108b,
title = "Modelling risk-adjusted variation in length of stay among Australian and New Zealand ICUs",
abstract = "Purpose Comparisons between institutions of intensive care unit (ICU) length of stay (LOS) are significantly confounded by individual patient characteristics, and currently there is a paucity of methods available to calculate risk-adjusted metrics. Methods We extracted de-identified data from the Australian and New Zealand Intensive Care Society (ANZICS) Adult Patient Database for admissions between January 1 2011 and December 31 2015. We used a mixed-effects log-normal regression model to predict LOS using patient and admission characteristics. We calculated a risk-adjusted LOS ratio (RALOSR) by dividing the geometric mean observed LOS by the exponent of the expected Ln-LOS for each site and year. The RALOSR is scaled such that values <1 indicate a LOS shorter than expected, while values >1 indicate a LOS longer than expected. Secondary mixed effects regression modelling was used to assess the stability of the estimate in units over time. Results During the study there were a total of 662, 525 admissions to 168 units (median annual admissions = 767, IQR:426-1121). The mean observed LOS was 3.21 days (median = 1.79 IQR = 0.92-3.52) over the entire period, and declined on average 1.97 hours per year (95{\%} CI:1.76-2.18) from 2011 to 2015. The RALOSR varied considerably between units, ranging from 0.35 to 2.34 indicating large differences after accounting for case-mix. Conclusions There are large disparities in risk-adjusted LOS among Australian and New Zealand ICUs which may reflect differences in resource utilization.",
author = "Straney, {Lahn D.} and Udy, {Andrew A.} and Aidan Burrell and Christoph Bergmeir and Huckson, {Sue D} and Cooper, {D. James} and Pilcher, {David V.}",
year = "2017",
month = "5",
day = "1",
doi = "10.1371/journal.pone.0176570",
language = "English",
volume = "12",
journal = "PLoS ONE",
issn = "1932-6203",
publisher = "Public Library of Science",
number = "5",

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Modelling risk-adjusted variation in length of stay among Australian and New Zealand ICUs. / Straney, Lahn D.; Udy, Andrew A.; Burrell, Aidan; Bergmeir, Christoph; Huckson, Sue D; Cooper, D. James; Pilcher, David V.

In: PLoS ONE, Vol. 12, No. 5, e0176570, 01.05.2017.

Research output: Contribution to journalArticleResearchpeer-review

TY - JOUR

T1 - Modelling risk-adjusted variation in length of stay among Australian and New Zealand ICUs

AU - Straney, Lahn D.

AU - Udy, Andrew A.

AU - Burrell, Aidan

AU - Bergmeir, Christoph

AU - Huckson, Sue D

AU - Cooper, D. James

AU - Pilcher, David V.

PY - 2017/5/1

Y1 - 2017/5/1

N2 - Purpose Comparisons between institutions of intensive care unit (ICU) length of stay (LOS) are significantly confounded by individual patient characteristics, and currently there is a paucity of methods available to calculate risk-adjusted metrics. Methods We extracted de-identified data from the Australian and New Zealand Intensive Care Society (ANZICS) Adult Patient Database for admissions between January 1 2011 and December 31 2015. We used a mixed-effects log-normal regression model to predict LOS using patient and admission characteristics. We calculated a risk-adjusted LOS ratio (RALOSR) by dividing the geometric mean observed LOS by the exponent of the expected Ln-LOS for each site and year. The RALOSR is scaled such that values <1 indicate a LOS shorter than expected, while values >1 indicate a LOS longer than expected. Secondary mixed effects regression modelling was used to assess the stability of the estimate in units over time. Results During the study there were a total of 662, 525 admissions to 168 units (median annual admissions = 767, IQR:426-1121). The mean observed LOS was 3.21 days (median = 1.79 IQR = 0.92-3.52) over the entire period, and declined on average 1.97 hours per year (95% CI:1.76-2.18) from 2011 to 2015. The RALOSR varied considerably between units, ranging from 0.35 to 2.34 indicating large differences after accounting for case-mix. Conclusions There are large disparities in risk-adjusted LOS among Australian and New Zealand ICUs which may reflect differences in resource utilization.

AB - Purpose Comparisons between institutions of intensive care unit (ICU) length of stay (LOS) are significantly confounded by individual patient characteristics, and currently there is a paucity of methods available to calculate risk-adjusted metrics. Methods We extracted de-identified data from the Australian and New Zealand Intensive Care Society (ANZICS) Adult Patient Database for admissions between January 1 2011 and December 31 2015. We used a mixed-effects log-normal regression model to predict LOS using patient and admission characteristics. We calculated a risk-adjusted LOS ratio (RALOSR) by dividing the geometric mean observed LOS by the exponent of the expected Ln-LOS for each site and year. The RALOSR is scaled such that values <1 indicate a LOS shorter than expected, while values >1 indicate a LOS longer than expected. Secondary mixed effects regression modelling was used to assess the stability of the estimate in units over time. Results During the study there were a total of 662, 525 admissions to 168 units (median annual admissions = 767, IQR:426-1121). The mean observed LOS was 3.21 days (median = 1.79 IQR = 0.92-3.52) over the entire period, and declined on average 1.97 hours per year (95% CI:1.76-2.18) from 2011 to 2015. The RALOSR varied considerably between units, ranging from 0.35 to 2.34 indicating large differences after accounting for case-mix. Conclusions There are large disparities in risk-adjusted LOS among Australian and New Zealand ICUs which may reflect differences in resource utilization.

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U2 - 10.1371/journal.pone.0176570

DO - 10.1371/journal.pone.0176570

M3 - Article

VL - 12

JO - PLoS ONE

JF - PLoS ONE

SN - 1932-6203

IS - 5

M1 - e0176570

ER -