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Geriatric Health Charts for Individual Assessment and Prediction of Care Needs: A Population-Based Prospective Study

BACKGROUND: Geriatric health charts that are similar to pediatric growth charts could facilitate monitoring health changes and predicting care needs in older adults. We aimed to validate an existing composite score (Health Assessment Tool [HAT]) and provide provisional age-specific reference curves...

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Autores principales: Santoni, Giola, Calderón-Larrañaga, Amaia, Vetrano, Davide L, Welmer, Anna-Karin, Orsini, Nicola, Fratiglioni, Laura
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6909908/
https://www.ncbi.nlm.nih.gov/pubmed/30517610
http://dx.doi.org/10.1093/gerona/gly272
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author Santoni, Giola
Calderón-Larrañaga, Amaia
Vetrano, Davide L
Welmer, Anna-Karin
Orsini, Nicola
Fratiglioni, Laura
author_facet Santoni, Giola
Calderón-Larrañaga, Amaia
Vetrano, Davide L
Welmer, Anna-Karin
Orsini, Nicola
Fratiglioni, Laura
author_sort Santoni, Giola
collection PubMed
description BACKGROUND: Geriatric health charts that are similar to pediatric growth charts could facilitate monitoring health changes and predicting care needs in older adults. We aimed to validate an existing composite score (Health Assessment Tool [HAT]) and provide provisional age-specific reference curves for the general older population. METHODS: Data came from the Swedish National study on Aging and Care in Kungsholmen (N = 3,363 participants aged 60 years and over examined clinically at baseline and 3 years later). HAT was validated by exploring its relationship with health indicators (logistic regression) and comparing its ability to predict care consumption with that of two of its components, morbidity and disability (receiver operating characteristic curve areas). A flowchart was developed to obtain individual-level HAT scores (nominal response method). Sex-specific health charts were derived by graphing seven percentile curves of age-related HAT change (logistic quantile regression). RESULTS: HAT scores above the age- and sex-specific median were related to good performance in chair-stand tests (odds ratio [OR] = 2.62, 95% confidence interval [CI]: 2.07–3.31), balance and grip tests (interaction balance grip test, OR = 1.15, 95% CI: 1.05–1.25), and good self-rated health (OR = 2.19, 95% CI: 1.77–2.71). Receiver operating characteristic curve areas (HAT vs number of chronic disorders) were formal care, 0.76 versus 0.58 (p value < .001); informal care, 0.74 versus 0.59 (p value < .001); hospital admission, 0.70 versus 0.66 (p value < .001); primary care visits, 0.71 versus 0.69 (p value > .05); and specialty care visits, 0.62 versus 0.65 (p value < .001). HAT consistently predicted medical and social care service use better than disability. CONCLUSIONS: HAT is a valid tool that predicts care consumption well and could be useful in developing geriatric health charts to better monitor health changes in older populations.
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spelling pubmed-69099082019-12-17 Geriatric Health Charts for Individual Assessment and Prediction of Care Needs: A Population-Based Prospective Study Santoni, Giola Calderón-Larrañaga, Amaia Vetrano, Davide L Welmer, Anna-Karin Orsini, Nicola Fratiglioni, Laura J Gerontol A Biol Sci Med Sci THE JOURNAL OF GERONTOLOGY: Medical Sciences BACKGROUND: Geriatric health charts that are similar to pediatric growth charts could facilitate monitoring health changes and predicting care needs in older adults. We aimed to validate an existing composite score (Health Assessment Tool [HAT]) and provide provisional age-specific reference curves for the general older population. METHODS: Data came from the Swedish National study on Aging and Care in Kungsholmen (N = 3,363 participants aged 60 years and over examined clinically at baseline and 3 years later). HAT was validated by exploring its relationship with health indicators (logistic regression) and comparing its ability to predict care consumption with that of two of its components, morbidity and disability (receiver operating characteristic curve areas). A flowchart was developed to obtain individual-level HAT scores (nominal response method). Sex-specific health charts were derived by graphing seven percentile curves of age-related HAT change (logistic quantile regression). RESULTS: HAT scores above the age- and sex-specific median were related to good performance in chair-stand tests (odds ratio [OR] = 2.62, 95% confidence interval [CI]: 2.07–3.31), balance and grip tests (interaction balance grip test, OR = 1.15, 95% CI: 1.05–1.25), and good self-rated health (OR = 2.19, 95% CI: 1.77–2.71). Receiver operating characteristic curve areas (HAT vs number of chronic disorders) were formal care, 0.76 versus 0.58 (p value < .001); informal care, 0.74 versus 0.59 (p value < .001); hospital admission, 0.70 versus 0.66 (p value < .001); primary care visits, 0.71 versus 0.69 (p value > .05); and specialty care visits, 0.62 versus 0.65 (p value < .001). HAT consistently predicted medical and social care service use better than disability. CONCLUSIONS: HAT is a valid tool that predicts care consumption well and could be useful in developing geriatric health charts to better monitor health changes in older populations. Oxford University Press 2020-01 2018-12-04 /pmc/articles/PMC6909908/ /pubmed/30517610 http://dx.doi.org/10.1093/gerona/gly272 Text en © The Author(s) 2018. Published by Oxford University Press on behalf of The Gerontological Society of America. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle THE JOURNAL OF GERONTOLOGY: Medical Sciences
Santoni, Giola
Calderón-Larrañaga, Amaia
Vetrano, Davide L
Welmer, Anna-Karin
Orsini, Nicola
Fratiglioni, Laura
Geriatric Health Charts for Individual Assessment and Prediction of Care Needs: A Population-Based Prospective Study
title Geriatric Health Charts for Individual Assessment and Prediction of Care Needs: A Population-Based Prospective Study
title_full Geriatric Health Charts for Individual Assessment and Prediction of Care Needs: A Population-Based Prospective Study
title_fullStr Geriatric Health Charts for Individual Assessment and Prediction of Care Needs: A Population-Based Prospective Study
title_full_unstemmed Geriatric Health Charts for Individual Assessment and Prediction of Care Needs: A Population-Based Prospective Study
title_short Geriatric Health Charts for Individual Assessment and Prediction of Care Needs: A Population-Based Prospective Study
title_sort geriatric health charts for individual assessment and prediction of care needs: a population-based prospective study
topic THE JOURNAL OF GERONTOLOGY: Medical Sciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6909908/
https://www.ncbi.nlm.nih.gov/pubmed/30517610
http://dx.doi.org/10.1093/gerona/gly272
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