Length of hospital stay (LOS) modeling with mixture Poisson distribution

BACKGROUND & OBJECTIVE: Modeling is one of the most fundamental methods of denoting statistical variables which by using it, we can found distribution of noted response variable. For analysis data same as length of hospital stay (LOS), we have not data normality and error variances homogeneity,...

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Main Authors: AR Rajaei Fard, M Rafiei
Format: Article
Language:English
Published: Babol University of Medical Sciences 2006-06-01
Series:Majallah-i Dānishgāh-i ̒Ulūm-i Pizishkī-i Bābul
Subjects:
Online Access:http://jbums.org/article-1-2532-en.html
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author AR Rajaei Fard
M Rafiei
author_facet AR Rajaei Fard
M Rafiei
author_sort AR Rajaei Fard
collection DOAJ
description BACKGROUND & OBJECTIVE: Modeling is one of the most fundamental methods of denoting statistical variables which by using it, we can found distribution of noted response variable. For analysis data same as length of hospital stay (LOS), we have not data normality and error variances homogeneity, so, we can use nonparametric methods or distribution correction likes logarithmic transferring for using parametric methods. According to experiences in this situation, considering mixture distributions approximately can improve goodness- of- fit distribution. The goal of this study was to introduce mixture Poisson modeling and using mixture Poisson regression models for explaining duration of patient hospitalization in hospital and gaining effective factors on this time of duration and also comparing these models with common regression models in these data.METHODS: After interdicting mixture Poisson modeling and its regression, we applied these models for modeling LOS in two wards in Arak Vali-e-Asr hospital. Variables of age, marriage status, birth location and living location as independent variables and duration of hospitalization in hospital as countable response variable were considered and LOS was considered as response variable for application these models.FINDINGS: The findings have shown that in base Log-likelihood value and more dispersion LOS data in the surgical ward mixture Poisson model was a suitable for explain LOS with the other variables and in internal ward the variation of hospitalization time is not great, so this model cannot describe this variable explanation.CONCLUSION: By consideration Log-likelihood value and variation of LOS in surgical ward, the Poisson mixture model is a good model for describing this variable. By using general models, the Log-likelihood value is more than mixture Poisson modeling and there are less significant factors in models. Application of these models in cases which the countable response variable has great variation, is recommended.
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spelling doaj.art-0022ec45130f4c02a8beeb2e40b2dd7d2022-12-21T19:29:46ZengBabol University of Medical SciencesMajallah-i Dānishgāh-i ̒Ulūm-i Pizishkī-i Bābul1561-41072251-71702006-06-01833643Length of hospital stay (LOS) modeling with mixture Poisson distributionAR Rajaei Fard0M Rafiei1 BACKGROUND & OBJECTIVE: Modeling is one of the most fundamental methods of denoting statistical variables which by using it, we can found distribution of noted response variable. For analysis data same as length of hospital stay (LOS), we have not data normality and error variances homogeneity, so, we can use nonparametric methods or distribution correction likes logarithmic transferring for using parametric methods. According to experiences in this situation, considering mixture distributions approximately can improve goodness- of- fit distribution. The goal of this study was to introduce mixture Poisson modeling and using mixture Poisson regression models for explaining duration of patient hospitalization in hospital and gaining effective factors on this time of duration and also comparing these models with common regression models in these data.METHODS: After interdicting mixture Poisson modeling and its regression, we applied these models for modeling LOS in two wards in Arak Vali-e-Asr hospital. Variables of age, marriage status, birth location and living location as independent variables and duration of hospitalization in hospital as countable response variable were considered and LOS was considered as response variable for application these models.FINDINGS: The findings have shown that in base Log-likelihood value and more dispersion LOS data in the surgical ward mixture Poisson model was a suitable for explain LOS with the other variables and in internal ward the variation of hospitalization time is not great, so this model cannot describe this variable explanation.CONCLUSION: By consideration Log-likelihood value and variation of LOS in surgical ward, the Poisson mixture model is a good model for describing this variable. By using general models, the Log-likelihood value is more than mixture Poisson modeling and there are less significant factors in models. Application of these models in cases which the countable response variable has great variation, is recommended.http://jbums.org/article-1-2532-en.htmlpoisson mixture regressionlospoisson regressionsimple linear regression
spellingShingle AR Rajaei Fard
M Rafiei
Length of hospital stay (LOS) modeling with mixture Poisson distribution
Majallah-i Dānishgāh-i ̒Ulūm-i Pizishkī-i Bābul
poisson mixture regression
los
poisson regression
simple linear regression
title Length of hospital stay (LOS) modeling with mixture Poisson distribution
title_full Length of hospital stay (LOS) modeling with mixture Poisson distribution
title_fullStr Length of hospital stay (LOS) modeling with mixture Poisson distribution
title_full_unstemmed Length of hospital stay (LOS) modeling with mixture Poisson distribution
title_short Length of hospital stay (LOS) modeling with mixture Poisson distribution
title_sort length of hospital stay los modeling with mixture poisson distribution
topic poisson mixture regression
los
poisson regression
simple linear regression
url http://jbums.org/article-1-2532-en.html
work_keys_str_mv AT arrajaeifard lengthofhospitalstaylosmodelingwithmixturepoissondistribution
AT mrafiei lengthofhospitalstaylosmodelingwithmixturepoissondistribution