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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Autores principales:	AR Rajaei Fard, M Rafiei
Formato:	article
Lenguaje:	EN FA
Publicado:	Babol University of Medical Sciences 2006
Materias:	poisson mixture regression los poisson regression simple linear regression Medicine R Medicine (General) R5-920
Acceso en línea:	https://doaj.org/article/0022ec45130f4c02a8beeb2e40b2dd7d
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spelling	oai:doaj.org-article:0022ec45130f4c02a8beeb2e40b2dd7d2021-11-10T09:12:49ZLength of hospital stay (LOS) modeling with mixture Poisson distribution1561-41072251-7170https://doaj.org/article/0022ec45130f4c02a8beeb2e40b2dd7d2006-06-01T00:00:00Zhttp://jbums.org/article-1-2532-en.htmlhttps://doaj.org/toc/1561-4107https://doaj.org/toc/2251-7170BACKGROUND & 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.AR Rajaei FardM RafieiBabol University of Medical Sciencesarticlepoisson mixture regressionlospoisson regressionsimple linear regressionMedicineRMedicine (General)R5-920ENFAMajallah-i Dānishgāh-i ̒Ulūm-i Pizishkī-i Bābul, Vol 8, Iss 3, Pp 36-43 (2006)
institution	DOAJ
collection	DOAJ
language	EN FA
topic	poisson mixture regression los poisson regression simple linear regression Medicine R Medicine (General) R5-920
spellingShingle	poisson mixture regression los poisson regression simple linear regression Medicine R Medicine (General) R5-920 AR Rajaei Fard M Rafiei Length of hospital stay (LOS) modeling with mixture Poisson distribution
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.
format	article
author	AR Rajaei Fard M Rafiei
author_facet	AR Rajaei Fard M Rafiei
author_sort	AR Rajaei Fard
title	Length of hospital stay (LOS) modeling with mixture Poisson distribution
title_short	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_sort	length of hospital stay (los) modeling with mixture poisson distribution
publisher	Babol University of Medical Sciences
publishDate	2006
url	https://doaj.org/article/0022ec45130f4c02a8beeb2e40b2dd7d
work_keys_str_mv	AT arrajaeifard lengthofhospitalstaylosmodelingwithmixturepoissondistribution AT mrafiei lengthofhospitalstaylosmodelingwithmixturepoissondistribution
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Length of hospital stay (LOS) modeling with mixture Poisson distribution

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