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Designing an Elderly Hospital Admission Risk Prediction Model in Iran's Hospitals

BACKGROUND: The identification of elderly at risk of new functional disabilities in activities of daily living at admission to the hospital may facilitate referral for purposive interventions to prevent decline and institutionalization. This study was aimed at designing a risk prediction model for i...

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Autores principales: Maleki, Mohammad R., Doosty, Farzaneh, Yarmohammadian, Mohammad H., Rasi, Vahid, Tanner, Elizabeth (Ibby)
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer - Medknow 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8106286/
https://www.ncbi.nlm.nih.gov/pubmed/34084319
http://dx.doi.org/10.4103/ijpvm.IJPVM_433_18
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author Maleki, Mohammad R.
Doosty, Farzaneh
Yarmohammadian, Mohammad H.
Rasi, Vahid
Tanner, Elizabeth (Ibby)
author_facet Maleki, Mohammad R.
Doosty, Farzaneh
Yarmohammadian, Mohammad H.
Rasi, Vahid
Tanner, Elizabeth (Ibby)
author_sort Maleki, Mohammad R.
collection PubMed
description BACKGROUND: The identification of elderly at risk of new functional disabilities in activities of daily living at admission to the hospital may facilitate referral for purposive interventions to prevent decline and institutionalization. This study was aimed at designing a risk prediction model for identifying the elderly at risk of admission in Iran's hospitals. MATERIALS AND METHODS: This is a cross-sectional descriptive study conducted in 2017. In order to formulate and validate a prediction model, the study was done in two development and validation cohort study. Functional decline was defined as a decline of at least one point on the Katz ADL index at follow-up compared with preadmission status. RESULTS: In development cohort, the mean age was 71 years including 54% of men and 46% women, 22% of men and 17% of women experienced functional decline after 3 months. In the validation cohort, the mean age was 70 years, including 49% of men and 51% women, 19% of men and 15% of women, functional decline after 3 months was observed. CONCLUSION: On the basis of the findings, aging at risk of hospital admission can be identified by easy designed model with four questions: (1) Is the patient's age more than 85 years? (2) Does the patient's mini mental status <22? (3) Does the patient need help for using general transporting? (4) Has the patient lost weight <5% over the past 6 months and body mass index <18.5? And also geriatrics experts can use the designed model as a predictive tool in order to improve the quality level of healthcare services to elderly as a vulnerable and high risk group. The important point of model is easy to use even for nonspecialists.
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spelling pubmed-81062862021-06-02 Designing an Elderly Hospital Admission Risk Prediction Model in Iran's Hospitals Maleki, Mohammad R. Doosty, Farzaneh Yarmohammadian, Mohammad H. Rasi, Vahid Tanner, Elizabeth (Ibby) Int J Prev Med Original Article BACKGROUND: The identification of elderly at risk of new functional disabilities in activities of daily living at admission to the hospital may facilitate referral for purposive interventions to prevent decline and institutionalization. This study was aimed at designing a risk prediction model for identifying the elderly at risk of admission in Iran's hospitals. MATERIALS AND METHODS: This is a cross-sectional descriptive study conducted in 2017. In order to formulate and validate a prediction model, the study was done in two development and validation cohort study. Functional decline was defined as a decline of at least one point on the Katz ADL index at follow-up compared with preadmission status. RESULTS: In development cohort, the mean age was 71 years including 54% of men and 46% women, 22% of men and 17% of women experienced functional decline after 3 months. In the validation cohort, the mean age was 70 years, including 49% of men and 51% women, 19% of men and 15% of women, functional decline after 3 months was observed. CONCLUSION: On the basis of the findings, aging at risk of hospital admission can be identified by easy designed model with four questions: (1) Is the patient's age more than 85 years? (2) Does the patient's mini mental status <22? (3) Does the patient need help for using general transporting? (4) Has the patient lost weight <5% over the past 6 months and body mass index <18.5? And also geriatrics experts can use the designed model as a predictive tool in order to improve the quality level of healthcare services to elderly as a vulnerable and high risk group. The important point of model is easy to use even for nonspecialists. Wolters Kluwer - Medknow 2021-02-24 /pmc/articles/PMC8106286/ /pubmed/34084319 http://dx.doi.org/10.4103/ijpvm.IJPVM_433_18 Text en Copyright: © 2021 International Journal of Preventive Medicine https://creativecommons.org/licenses/by-nc-sa/4.0/This is an open access journal, and articles are distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as appropriate credit is given and the new creations are licensed under the identical terms.
spellingShingle Original Article
Maleki, Mohammad R.
Doosty, Farzaneh
Yarmohammadian, Mohammad H.
Rasi, Vahid
Tanner, Elizabeth (Ibby)
Designing an Elderly Hospital Admission Risk Prediction Model in Iran's Hospitals
title Designing an Elderly Hospital Admission Risk Prediction Model in Iran's Hospitals
title_full Designing an Elderly Hospital Admission Risk Prediction Model in Iran's Hospitals
title_fullStr Designing an Elderly Hospital Admission Risk Prediction Model in Iran's Hospitals
title_full_unstemmed Designing an Elderly Hospital Admission Risk Prediction Model in Iran's Hospitals
title_short Designing an Elderly Hospital Admission Risk Prediction Model in Iran's Hospitals
title_sort designing an elderly hospital admission risk prediction model in iran's hospitals
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8106286/
https://www.ncbi.nlm.nih.gov/pubmed/34084319
http://dx.doi.org/10.4103/ijpvm.IJPVM_433_18
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