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Generating Older Adult Multimorbidity Trajectories Using Various Comorbidity Indices and Calculation Methods

BACKGROUND AND OBJECTIVES: Older adult multimorbidity trajectories are helpful for understanding the current and future health patterns of aging populations. The construction of multimorbidity trajectories from comorbidity index scores will help inform public health and clinical interventions target...

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Autores principales: Newman, Michael G, Porucznik, Christina A, Date, Ankita P, Abdelrahman, Samir, Schliep, Karen C, VanDerslice, James A, Smith, Ken R, Hanson, Heidi A
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10168588/
https://www.ncbi.nlm.nih.gov/pubmed/37179657
http://dx.doi.org/10.1093/geroni/igad023
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author Newman, Michael G
Porucznik, Christina A
Date, Ankita P
Abdelrahman, Samir
Schliep, Karen C
VanDerslice, James A
Smith, Ken R
Hanson, Heidi A
author_facet Newman, Michael G
Porucznik, Christina A
Date, Ankita P
Abdelrahman, Samir
Schliep, Karen C
VanDerslice, James A
Smith, Ken R
Hanson, Heidi A
author_sort Newman, Michael G
collection PubMed
description BACKGROUND AND OBJECTIVES: Older adult multimorbidity trajectories are helpful for understanding the current and future health patterns of aging populations. The construction of multimorbidity trajectories from comorbidity index scores will help inform public health and clinical interventions targeting those individuals that are on unhealthy trajectories. Investigators have used many different techniques when creating multimorbidity trajectories in prior literature, and no standard way has emerged. This study compares and contrasts multimorbidity trajectories constructed from various methods. RESEARCH DESIGN AND METHODS: We describe the difference between aging trajectories constructed with the Charlson Comorbidity Index (CCI) and Elixhauser Comorbidity Index (ECI). We also explore the differences between acute (single-year) and chronic (cumulative) derivations of CCI and ECI scores. Social determinants of health can affect disease burden over time; thus, our models include income, race/ethnicity, and sex differences. RESULTS: We use group-based trajectory modeling (GBTM) to estimate multimorbidity trajectories for 86,909 individuals aged 66–75 in 1992 using Medicare claims data collected over the following 21 years. We identify low-chronic disease and high-chronic disease trajectories in all 8 generated trajectory models. Additionally, all 8 models satisfied prior established statistical diagnostic criteria for well-performing GBTM models. DISCUSSION AND IMPLICATIONS: Clinicians may use these trajectories to identify patients on an unhealthy path and prompt a possible intervention that may shift the patient to a healthier trajectory.
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spelling pubmed-101685882023-05-10 Generating Older Adult Multimorbidity Trajectories Using Various Comorbidity Indices and Calculation Methods Newman, Michael G Porucznik, Christina A Date, Ankita P Abdelrahman, Samir Schliep, Karen C VanDerslice, James A Smith, Ken R Hanson, Heidi A Innov Aging Original Research Article BACKGROUND AND OBJECTIVES: Older adult multimorbidity trajectories are helpful for understanding the current and future health patterns of aging populations. The construction of multimorbidity trajectories from comorbidity index scores will help inform public health and clinical interventions targeting those individuals that are on unhealthy trajectories. Investigators have used many different techniques when creating multimorbidity trajectories in prior literature, and no standard way has emerged. This study compares and contrasts multimorbidity trajectories constructed from various methods. RESEARCH DESIGN AND METHODS: We describe the difference between aging trajectories constructed with the Charlson Comorbidity Index (CCI) and Elixhauser Comorbidity Index (ECI). We also explore the differences between acute (single-year) and chronic (cumulative) derivations of CCI and ECI scores. Social determinants of health can affect disease burden over time; thus, our models include income, race/ethnicity, and sex differences. RESULTS: We use group-based trajectory modeling (GBTM) to estimate multimorbidity trajectories for 86,909 individuals aged 66–75 in 1992 using Medicare claims data collected over the following 21 years. We identify low-chronic disease and high-chronic disease trajectories in all 8 generated trajectory models. Additionally, all 8 models satisfied prior established statistical diagnostic criteria for well-performing GBTM models. DISCUSSION AND IMPLICATIONS: Clinicians may use these trajectories to identify patients on an unhealthy path and prompt a possible intervention that may shift the patient to a healthier trajectory. Oxford University Press 2023-04-12 /pmc/articles/PMC10168588/ /pubmed/37179657 http://dx.doi.org/10.1093/geroni/igad023 Text en © The Author(s) 2023. Published by Oxford University Press on behalf of The Gerontological Society of America. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs licence (https://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial reproduction and distribution of the work, in any medium, provided the original work is not altered or transformed in any way, and that the work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Original Research Article
Newman, Michael G
Porucznik, Christina A
Date, Ankita P
Abdelrahman, Samir
Schliep, Karen C
VanDerslice, James A
Smith, Ken R
Hanson, Heidi A
Generating Older Adult Multimorbidity Trajectories Using Various Comorbidity Indices and Calculation Methods
title Generating Older Adult Multimorbidity Trajectories Using Various Comorbidity Indices and Calculation Methods
title_full Generating Older Adult Multimorbidity Trajectories Using Various Comorbidity Indices and Calculation Methods
title_fullStr Generating Older Adult Multimorbidity Trajectories Using Various Comorbidity Indices and Calculation Methods
title_full_unstemmed Generating Older Adult Multimorbidity Trajectories Using Various Comorbidity Indices and Calculation Methods
title_short Generating Older Adult Multimorbidity Trajectories Using Various Comorbidity Indices and Calculation Methods
title_sort generating older adult multimorbidity trajectories using various comorbidity indices and calculation methods
topic Original Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10168588/
https://www.ncbi.nlm.nih.gov/pubmed/37179657
http://dx.doi.org/10.1093/geroni/igad023
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