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Identification of dementia and MCI cases in health information systems: An Italian validation study

INTRODUCTION: The identification of dementia cases through routinely collected health data represents an easily accessible and inexpensive method to estimate the prevalence of dementia. In Italy, a project aimed at the validation of an algorithm was conducted. METHODS: The project included cases (pa...

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Autores principales: Bacigalupo, Ilaria, Lombardo, Flavia L., Bargagli, Anna Maria, Cascini, Silvia, Agabiti, Nera, Davoli, Marina, Scalmana, Silvia, Palma, Annalisa Di, Greco, Annarita, Rinaldi, Marina, Giordana, Roberta, Imperiale, Daniele, Secreto, Piero, Golini, Natalia, Gnavi, Roberto, Lovaldi, Franca, Biagini, Carlo A., Gualdani, Elisa, Francesconi, Paolo, Magliocchetti, Natalia, Fiandra, Teresa Di, Vanacore, Nicola
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9617569/
https://www.ncbi.nlm.nih.gov/pubmed/36320346
http://dx.doi.org/10.1002/trc2.12327
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author Bacigalupo, Ilaria
Lombardo, Flavia L.
Bargagli, Anna Maria
Cascini, Silvia
Agabiti, Nera
Davoli, Marina
Scalmana, Silvia
Palma, Annalisa Di
Greco, Annarita
Rinaldi, Marina
Giordana, Roberta
Imperiale, Daniele
Secreto, Piero
Golini, Natalia
Gnavi, Roberto
Lovaldi, Franca
Biagini, Carlo A.
Gualdani, Elisa
Francesconi, Paolo
Magliocchetti, Natalia
Fiandra, Teresa Di
Vanacore, Nicola
author_facet Bacigalupo, Ilaria
Lombardo, Flavia L.
Bargagli, Anna Maria
Cascini, Silvia
Agabiti, Nera
Davoli, Marina
Scalmana, Silvia
Palma, Annalisa Di
Greco, Annarita
Rinaldi, Marina
Giordana, Roberta
Imperiale, Daniele
Secreto, Piero
Golini, Natalia
Gnavi, Roberto
Lovaldi, Franca
Biagini, Carlo A.
Gualdani, Elisa
Francesconi, Paolo
Magliocchetti, Natalia
Fiandra, Teresa Di
Vanacore, Nicola
author_sort Bacigalupo, Ilaria
collection PubMed
description INTRODUCTION: The identification of dementia cases through routinely collected health data represents an easily accessible and inexpensive method to estimate the prevalence of dementia. In Italy, a project aimed at the validation of an algorithm was conducted. METHODS: The project included cases (patients with dementia or mild cognitive impairment [MCI]) recruited in centers for cognitive disorders and dementias and controls recruited in outpatient units of geriatrics and neurology. The algorithm based on pharmaceutical prescriptions, hospital discharge records, residential long‐term care records, and information on exemption from health‐care co‐payment, was applied to the validation population. RESULTS: The main analysis was conducted on 1110 cases and 1114 controls. The sensitivity, specificity, and positive and negative predictive values in discerning cases of dementia were 74.5%, 96.0%, 94.9%, and 79.1%, respectively, whereas in detecting cases of MCI these values were 29.7%, 97.5%, 92.2%, and 58.1%, respectively. The variables associated with misclassification of cases were also identified. DISCUSSION: This study provided a validated algorithm, based on administrative data, which can be used to identify cases with dementia and, with lower sensitivity, also early onset dementia but not cases with MCI.
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spelling pubmed-96175692022-10-31 Identification of dementia and MCI cases in health information systems: An Italian validation study Bacigalupo, Ilaria Lombardo, Flavia L. Bargagli, Anna Maria Cascini, Silvia Agabiti, Nera Davoli, Marina Scalmana, Silvia Palma, Annalisa Di Greco, Annarita Rinaldi, Marina Giordana, Roberta Imperiale, Daniele Secreto, Piero Golini, Natalia Gnavi, Roberto Lovaldi, Franca Biagini, Carlo A. Gualdani, Elisa Francesconi, Paolo Magliocchetti, Natalia Fiandra, Teresa Di Vanacore, Nicola Alzheimers Dement (N Y) Research Articles INTRODUCTION: The identification of dementia cases through routinely collected health data represents an easily accessible and inexpensive method to estimate the prevalence of dementia. In Italy, a project aimed at the validation of an algorithm was conducted. METHODS: The project included cases (patients with dementia or mild cognitive impairment [MCI]) recruited in centers for cognitive disorders and dementias and controls recruited in outpatient units of geriatrics and neurology. The algorithm based on pharmaceutical prescriptions, hospital discharge records, residential long‐term care records, and information on exemption from health‐care co‐payment, was applied to the validation population. RESULTS: The main analysis was conducted on 1110 cases and 1114 controls. The sensitivity, specificity, and positive and negative predictive values in discerning cases of dementia were 74.5%, 96.0%, 94.9%, and 79.1%, respectively, whereas in detecting cases of MCI these values were 29.7%, 97.5%, 92.2%, and 58.1%, respectively. The variables associated with misclassification of cases were also identified. DISCUSSION: This study provided a validated algorithm, based on administrative data, which can be used to identify cases with dementia and, with lower sensitivity, also early onset dementia but not cases with MCI. John Wiley and Sons Inc. 2022-10-29 /pmc/articles/PMC9617569/ /pubmed/36320346 http://dx.doi.org/10.1002/trc2.12327 Text en © 2022 The Authors. Alzheimer's & Dementia: Translational Research & Clinical Interventions published by Wiley Periodicals LLC on behalf of Alzheimer's Association. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
spellingShingle Research Articles
Bacigalupo, Ilaria
Lombardo, Flavia L.
Bargagli, Anna Maria
Cascini, Silvia
Agabiti, Nera
Davoli, Marina
Scalmana, Silvia
Palma, Annalisa Di
Greco, Annarita
Rinaldi, Marina
Giordana, Roberta
Imperiale, Daniele
Secreto, Piero
Golini, Natalia
Gnavi, Roberto
Lovaldi, Franca
Biagini, Carlo A.
Gualdani, Elisa
Francesconi, Paolo
Magliocchetti, Natalia
Fiandra, Teresa Di
Vanacore, Nicola
Identification of dementia and MCI cases in health information systems: An Italian validation study
title Identification of dementia and MCI cases in health information systems: An Italian validation study
title_full Identification of dementia and MCI cases in health information systems: An Italian validation study
title_fullStr Identification of dementia and MCI cases in health information systems: An Italian validation study
title_full_unstemmed Identification of dementia and MCI cases in health information systems: An Italian validation study
title_short Identification of dementia and MCI cases in health information systems: An Italian validation study
title_sort identification of dementia and mci cases in health information systems: an italian validation study
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9617569/
https://www.ncbi.nlm.nih.gov/pubmed/36320346
http://dx.doi.org/10.1002/trc2.12327
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