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https://hdl.handle.net/2440/75890
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dc.contributor.author | Moran, J. | - |
dc.contributor.author | Solomon, P. | - |
dc.date.issued | 2012 | - |
dc.identifier.citation | BMC Medical Research Methodology, 2012; 12(1):1-17 | - |
dc.identifier.issn | 1471-2288 | - |
dc.identifier.issn | 1471-2288 | - |
dc.identifier.uri | http://hdl.handle.net/2440/75890 | - |
dc.description | Extent: 17p. | - |
dc.description.abstract | <h4>Background</h4>For the analysis of length-of-stay (LOS) data, which is characteristically right-skewed, a number of statistical estimators have been proposed as alternatives to the traditional ordinary least squares (OLS) regression with log dependent variable.<h4>Methods</h4>Using a cohort of patients identified in the Australian and New Zealand Intensive Care Society Adult Patient Database, 2008-2009, 12 different methods were used for estimation of intensive care (ICU) length of stay. These encompassed risk-adjusted regression analysis of firstly: log LOS using OLS, linear mixed model [LMM], treatment effects, skew-normal and skew-t models; and secondly: unmodified (raw) LOS via OLS, generalised linear models [GLMs] with log-link and 4 different distributions [Poisson, gamma, negative binomial and inverse-Gaussian], extended estimating equations [EEE] and a finite mixture model including a gamma distribution. A fixed covariate list and ICU-site clustering with robust variance were utilised for model fitting with split-sample determination (80%) and validation (20%) data sets, and model simulation was undertaken to establish over-fitting (Copas test). Indices of model specification using Bayesian information criterion [BIC: lower values preferred] and residual analysis as well as predictive performance (R2, concordance correlation coefficient (CCC), mean absolute error [MAE]) were established for each estimator.<h4>Results</h4>The data-set consisted of 111663 patients from 131 ICUs; with mean(SD) age 60.6(18.8) years, 43.0% were female, 40.7% were mechanically ventilated and ICU mortality was 7.8%. ICU length-of-stay was 3.4(5.1) (median 1.8, range (0.17-60)) days and demonstrated marked kurtosis and right skew (29.4 and 4.4 respectively). BIC showed considerable spread, from a maximum of 509801 (OLS-raw scale) to a minimum of 210286 (LMM). R2 ranged from 0.22 (LMM) to 0.17 and the CCC from 0.334 (LMM) to 0.149, with MAE 2.2-2.4. Superior residual behaviour was established for the log-scale estimators. There was a general tendency for over-prediction (negative residuals) and for over-fitting, the exception being the GLM negative binomial estimator. The mean-variance function was best approximated by a quadratic function, consistent with log-scale estimation; the link function was estimated (EEE) as 0.152(0.019, 0.285), consistent with a fractional-root function.<h4>Conclusions</h4>For ICU length of stay, log-scale estimation, in particular the LMM, appeared to be the most consistently performing estimator(s). Neither the GLM variants nor the skew-regression estimators dominated. | - |
dc.description.statementofresponsibility | John L Moran and Patricia J Solomon | - |
dc.language.iso | en | - |
dc.publisher | BioMed Central Ltd. | - |
dc.rights | © 2012 Moran and Solomon; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. | - |
dc.source.uri | http://dx.doi.org/10.1186/1471-2288-12-68 | - |
dc.subject | ANZICS Centre for Outcome and Resource Evaluation (CORE) of the Australian and New Zealand Intensive Care Society (ANZICS) | - |
dc.subject | Humans | - |
dc.subject | Critical Care | - |
dc.subject | Length of Stay | - |
dc.subject | APACHE | - |
dc.subject | Severity of Illness Index | - |
dc.subject | Data Interpretation, Statistical | - |
dc.subject | Models, Statistical | - |
dc.subject | Regression Analysis | - |
dc.subject | Databases, Factual | - |
dc.subject | Intensive Care Units | - |
dc.subject | Australia | - |
dc.subject | New Zealand | - |
dc.title | A review of statistical estimators for risk-adjusted length of stay: analysis of the Australian and New Zealand intensive care adult patient data-base, 2008-2009 | - |
dc.type | Journal article | - |
dc.identifier.doi | 10.1186/1471-2288-12-68 | - |
pubs.publication-status | Published | - |
dc.identifier.orcid | Moran, J. [0000-0003-2311-0440] | - |
dc.identifier.orcid | Solomon, P. [0000-0002-0667-6947] | - |
Appears in Collections: | Aurora harvest Mathematical Sciences publications |
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hdl_75890.pdf | Published version | 1.38 MB | Adobe PDF | View/Open |
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