Cargando…

Predictive model of length of stay and discharge destination in neuroscience admissions

BACKGROUND: The purpose of this study was to try and determine the best predictors of hospital length of stay and discharge destination in patients admitted to a neuroscience service. METHODS: Valid data was collected for 170 patients. Variables included age, gender, location prior to admission, pri...

Descripción completa

Detalles Bibliográficos
Autores principales: Stecker, M. M., Stecker, M., Falotico, J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Medknow Publications & Media Pvt Ltd 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5309446/
https://www.ncbi.nlm.nih.gov/pubmed/28217396
http://dx.doi.org/10.4103/2152-7806.199558
_version_ 1782507706675888128
author Stecker, M. M.
Stecker, M.
Falotico, J.
author_facet Stecker, M. M.
Stecker, M.
Falotico, J.
author_sort Stecker, M. M.
collection PubMed
description BACKGROUND: The purpose of this study was to try and determine the best predictors of hospital length of stay and discharge destination in patients admitted to a neuroscience service. METHODS: Valid data was collected for 170 patients. Variables included age, gender, location prior to admission, principle diagnosis, various physiological measurements upon admission, comorbidity, independence in various activities of daily living prior to admission, length of stay, and disposition upon discharge. Study design was a correlational descriptive study performed through the analysis of data and the development and validation of statistically significant factors in determining the length of stay. RESULTS: All factors with a strong (P < 0.05) relationship with the length of stay were entered into a forward stepwise linear regression with length of stay as the dependent variable. The three most significant variables in predicting length of stay in this study were admission from an outpatient setting, modified Rankin score on admission, and systolic blood pressure on admission. CONCLUSIONS: Functional status at admission, specifically, a higher modified Rankin score and a lower systolic blood pressure along with the acquisition of deep vein thrombosis, catheter associated urinary tract infections, intubation, and admission to an intensive care unit all have a statistically significant effect on the hospital length of stay.
format Online
Article
Text
id pubmed-5309446
institution National Center for Biotechnology Information
language English
publishDate 2017
publisher Medknow Publications & Media Pvt Ltd
record_format MEDLINE/PubMed
spelling pubmed-53094462017-02-17 Predictive model of length of stay and discharge destination in neuroscience admissions Stecker, M. M. Stecker, M. Falotico, J. Surg Neurol Int Neuroscience Nursing: Original Article BACKGROUND: The purpose of this study was to try and determine the best predictors of hospital length of stay and discharge destination in patients admitted to a neuroscience service. METHODS: Valid data was collected for 170 patients. Variables included age, gender, location prior to admission, principle diagnosis, various physiological measurements upon admission, comorbidity, independence in various activities of daily living prior to admission, length of stay, and disposition upon discharge. Study design was a correlational descriptive study performed through the analysis of data and the development and validation of statistically significant factors in determining the length of stay. RESULTS: All factors with a strong (P < 0.05) relationship with the length of stay were entered into a forward stepwise linear regression with length of stay as the dependent variable. The three most significant variables in predicting length of stay in this study were admission from an outpatient setting, modified Rankin score on admission, and systolic blood pressure on admission. CONCLUSIONS: Functional status at admission, specifically, a higher modified Rankin score and a lower systolic blood pressure along with the acquisition of deep vein thrombosis, catheter associated urinary tract infections, intubation, and admission to an intensive care unit all have a statistically significant effect on the hospital length of stay. Medknow Publications & Media Pvt Ltd 2017-02-06 /pmc/articles/PMC5309446/ /pubmed/28217396 http://dx.doi.org/10.4103/2152-7806.199558 Text en Copyright: © 2017 Surgical Neurology International http://creativecommons.org/licenses/by-nc-sa/3.0 This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as the author is credited and the new creations are licensed under the identical terms.
spellingShingle Neuroscience Nursing: Original Article
Stecker, M. M.
Stecker, M.
Falotico, J.
Predictive model of length of stay and discharge destination in neuroscience admissions
title Predictive model of length of stay and discharge destination in neuroscience admissions
title_full Predictive model of length of stay and discharge destination in neuroscience admissions
title_fullStr Predictive model of length of stay and discharge destination in neuroscience admissions
title_full_unstemmed Predictive model of length of stay and discharge destination in neuroscience admissions
title_short Predictive model of length of stay and discharge destination in neuroscience admissions
title_sort predictive model of length of stay and discharge destination in neuroscience admissions
topic Neuroscience Nursing: Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5309446/
https://www.ncbi.nlm.nih.gov/pubmed/28217396
http://dx.doi.org/10.4103/2152-7806.199558
work_keys_str_mv AT steckermm predictivemodeloflengthofstayanddischargedestinationinneuroscienceadmissions
AT steckerm predictivemodeloflengthofstayanddischargedestinationinneuroscienceadmissions
AT faloticoj predictivemodeloflengthofstayanddischargedestinationinneuroscienceadmissions