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Retrospective assessment of patient characteristics and healthcare costs prior to a diagnosis of Alzheimer’s disease in an administrative claims database

BACKGROUND: The objective of this study was to examine patient characteristics and health care resource utilization (HCRU) in the 36 months prior to a confirmatory diagnosis of Alzheimer’s disease (AD) compared to a matched cohort without dementia during the same time interval. METHODS: Patients new...

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Autores principales: Nair, Radhika, Haynes, Virginia S., Siadaty, Mir, Patel, Nick C., Fleisher, Adam S., Van Amerongen, Derek, Witte, Michael M., Downing, AnnCatherine M., Fernandez, Leslie Ann Hazel, Saundankar, Vishal, Ball, Daniel E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6192320/
https://www.ncbi.nlm.nih.gov/pubmed/30326851
http://dx.doi.org/10.1186/s12877-018-0920-2
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author Nair, Radhika
Haynes, Virginia S.
Siadaty, Mir
Patel, Nick C.
Fleisher, Adam S.
Van Amerongen, Derek
Witte, Michael M.
Downing, AnnCatherine M.
Fernandez, Leslie Ann Hazel
Saundankar, Vishal
Ball, Daniel E.
author_facet Nair, Radhika
Haynes, Virginia S.
Siadaty, Mir
Patel, Nick C.
Fleisher, Adam S.
Van Amerongen, Derek
Witte, Michael M.
Downing, AnnCatherine M.
Fernandez, Leslie Ann Hazel
Saundankar, Vishal
Ball, Daniel E.
author_sort Nair, Radhika
collection PubMed
description BACKGROUND: The objective of this study was to examine patient characteristics and health care resource utilization (HCRU) in the 36 months prior to a confirmatory diagnosis of Alzheimer’s disease (AD) compared to a matched cohort without dementia during the same time interval. METHODS: Patients newly diagnosed with AD (with ≥2 claims) were identified between January 1, 2013 to September 31, 2015, and the date of the second claim for AD was defined as the index date. Patients were enrolled for at least 36 months prior to index date. The AD cohort was matched to a cohort with no AD or dementia codes (1:3) on age, gender, race/ethnicity, and enrollment duration prior to the index date. Descriptive analyses were used to summarize patient characteristics, HCRU, and healthcare costs prior to the confirmatory AD diagnosis. The classification and regression tree analysis and logistic regression were used to identify factors associated with the AD diagnosis. RESULTS: The AD cohort (N = 16,494) had significantly higher comorbidity indices and greater odds of comorbid mental and behavioral diagnoses, including mild cognitive impairment, mood and anxiety disorders, behavioral disturbances, and cerebrovascular disease, heart disease, urinary tract infections, and pneumonia than the matched non-AD or dementia cohort (N = 49,482). During the six-month period before the confirmatory AD diagnosis, AD medication use and diagnosis of mild cognitive impairment, Parkinson’s disease, or mood disorder were the strongest predictors of a subsequent confirmatory diagnosis of AD. Greater HCRU and healthcare costs were observed for the AD cohort primarily during the six-month period before the confirmatory AD diagnosis. CONCLUSION: The results of this study demonstrated a higher comorbidity burden and higher costs for patients prior to a diagnosis of AD in comparison to the matched cohort. Several comorbidities were associated with a subsequent diagnosis of AD. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12877-018-0920-2) contains supplementary material, which is available to authorized users.
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spelling pubmed-61923202018-10-22 Retrospective assessment of patient characteristics and healthcare costs prior to a diagnosis of Alzheimer’s disease in an administrative claims database Nair, Radhika Haynes, Virginia S. Siadaty, Mir Patel, Nick C. Fleisher, Adam S. Van Amerongen, Derek Witte, Michael M. Downing, AnnCatherine M. Fernandez, Leslie Ann Hazel Saundankar, Vishal Ball, Daniel E. BMC Geriatr Research Article BACKGROUND: The objective of this study was to examine patient characteristics and health care resource utilization (HCRU) in the 36 months prior to a confirmatory diagnosis of Alzheimer’s disease (AD) compared to a matched cohort without dementia during the same time interval. METHODS: Patients newly diagnosed with AD (with ≥2 claims) were identified between January 1, 2013 to September 31, 2015, and the date of the second claim for AD was defined as the index date. Patients were enrolled for at least 36 months prior to index date. The AD cohort was matched to a cohort with no AD or dementia codes (1:3) on age, gender, race/ethnicity, and enrollment duration prior to the index date. Descriptive analyses were used to summarize patient characteristics, HCRU, and healthcare costs prior to the confirmatory AD diagnosis. The classification and regression tree analysis and logistic regression were used to identify factors associated with the AD diagnosis. RESULTS: The AD cohort (N = 16,494) had significantly higher comorbidity indices and greater odds of comorbid mental and behavioral diagnoses, including mild cognitive impairment, mood and anxiety disorders, behavioral disturbances, and cerebrovascular disease, heart disease, urinary tract infections, and pneumonia than the matched non-AD or dementia cohort (N = 49,482). During the six-month period before the confirmatory AD diagnosis, AD medication use and diagnosis of mild cognitive impairment, Parkinson’s disease, or mood disorder were the strongest predictors of a subsequent confirmatory diagnosis of AD. Greater HCRU and healthcare costs were observed for the AD cohort primarily during the six-month period before the confirmatory AD diagnosis. CONCLUSION: The results of this study demonstrated a higher comorbidity burden and higher costs for patients prior to a diagnosis of AD in comparison to the matched cohort. Several comorbidities were associated with a subsequent diagnosis of AD. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12877-018-0920-2) contains supplementary material, which is available to authorized users. BioMed Central 2018-10-16 /pmc/articles/PMC6192320/ /pubmed/30326851 http://dx.doi.org/10.1186/s12877-018-0920-2 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Nair, Radhika
Haynes, Virginia S.
Siadaty, Mir
Patel, Nick C.
Fleisher, Adam S.
Van Amerongen, Derek
Witte, Michael M.
Downing, AnnCatherine M.
Fernandez, Leslie Ann Hazel
Saundankar, Vishal
Ball, Daniel E.
Retrospective assessment of patient characteristics and healthcare costs prior to a diagnosis of Alzheimer’s disease in an administrative claims database
title Retrospective assessment of patient characteristics and healthcare costs prior to a diagnosis of Alzheimer’s disease in an administrative claims database
title_full Retrospective assessment of patient characteristics and healthcare costs prior to a diagnosis of Alzheimer’s disease in an administrative claims database
title_fullStr Retrospective assessment of patient characteristics and healthcare costs prior to a diagnosis of Alzheimer’s disease in an administrative claims database
title_full_unstemmed Retrospective assessment of patient characteristics and healthcare costs prior to a diagnosis of Alzheimer’s disease in an administrative claims database
title_short Retrospective assessment of patient characteristics and healthcare costs prior to a diagnosis of Alzheimer’s disease in an administrative claims database
title_sort retrospective assessment of patient characteristics and healthcare costs prior to a diagnosis of alzheimer’s disease in an administrative claims database
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6192320/
https://www.ncbi.nlm.nih.gov/pubmed/30326851
http://dx.doi.org/10.1186/s12877-018-0920-2
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