Identification of dementia and MCI cases in health information systems: An Italian validation study
Abstract 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 ca...
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| Format: | Article |
| Language: | English |
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Wiley
2022-01-01
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| Series: | Alzheimer’s & Dementia: Translational Research & Clinical Interventions |
| Subjects: | |
| Online Access: | https://doi.org/10.1002/trc2.12327 |
| _version_ | 1826950786034171904 |
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| author | Ilaria Bacigalupo Flavia L. Lombardo Anna Maria Bargagli Silvia Cascini Nera Agabiti Marina Davoli Silvia Scalmana Annalisa Di Palma Annarita Greco Marina Rinaldi Roberta Giordana Daniele Imperiale Piero Secreto Natalia Golini Roberto Gnavi Franca Lovaldi Carlo A. Biagini Elisa Gualdani Paolo Francesconi Natalia Magliocchetti Teresa Di Fiandra Nicola Vanacore |
| author_facet | Ilaria Bacigalupo Flavia L. Lombardo Anna Maria Bargagli Silvia Cascini Nera Agabiti Marina Davoli Silvia Scalmana Annalisa Di Palma Annarita Greco Marina Rinaldi Roberta Giordana Daniele Imperiale Piero Secreto Natalia Golini Roberto Gnavi Franca Lovaldi Carlo A. Biagini Elisa Gualdani Paolo Francesconi Natalia Magliocchetti Teresa Di Fiandra Nicola Vanacore |
| author_sort | Ilaria Bacigalupo |
| collection | DOAJ |
| description | Abstract 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. |
| first_indexed | 2024-04-10T21:52:19Z |
| format | Article |
| id | doaj.art-804cc71eb1c640dfa77ba62858863e7c |
| institution | Directory Open Access Journal |
| issn | 2352-8737 |
| language | English |
| last_indexed | 2025-02-17T22:37:16Z |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Alzheimer’s & Dementia: Translational Research & Clinical Interventions |
| spelling | doaj.art-804cc71eb1c640dfa77ba62858863e7c2024-12-03T12:37:32ZengWileyAlzheimer’s & Dementia: Translational Research & Clinical Interventions2352-87372022-01-0181n/an/a10.1002/trc2.12327Identification of dementia and MCI cases in health information systems: An Italian validation studyIlaria Bacigalupo0Flavia L. Lombardo1Anna Maria Bargagli2Silvia Cascini3Nera Agabiti4Marina Davoli5Silvia Scalmana6Annalisa Di Palma7Annarita Greco8Marina Rinaldi9Roberta Giordana10Daniele Imperiale11Piero Secreto12Natalia Golini13Roberto Gnavi14Franca Lovaldi15Carlo A. Biagini16Elisa Gualdani17Paolo Francesconi18Natalia Magliocchetti19Teresa Di Fiandra20Nicola Vanacore21National Center for Disease Prevention and Health Promotion Italian National Institute of Health Rome ItalyNational Center for Disease Prevention and Health Promotion Italian National Institute of Health Rome ItalyDepartment of Epidemiology Lazio Regional Health Service Rome ItalyDepartment of Epidemiology Lazio Regional Health Service Rome ItalyDepartment of Epidemiology Lazio Regional Health Service Rome ItalyDepartment of Epidemiology Lazio Regional Health Service Rome ItalyPrimary Care Health Authority of Lazio Region Rome ItalyLocal Health Authority Naples 1 Campania Region Naples ItalyHealth Authority of Campania Region Naples ItalyHealth Authority of Campania Region Naples ItalySoresa Campania Regional Healthcare Agency Naples ItalyNeurology Unit ASL Città di Torino Turin ItalyGeriatric unit Local Health Authority TO3 Piemonte Region Turin ItalyEpidemiology Unit Local Health Authority TO3 Piemonte Region Grugliasco ItalyEpidemiology Unit Local Health Authority TO3 Piemonte Region Grugliasco ItalyHealth Department Piemonte Region Turin ItalyGeriatric Local Health Authority Pistoia ItalyEpidemiology Unit Toscana Regional Health Agency Florence ItalyEpidemiology Unit Toscana Regional Health Agency Florence ItalyGeneral Directorate for Health Prevention Ministry of Health Rome ItalyGeneral Directorate for Health Prevention Ministry of Health Rome ItalyNational Center for Disease Prevention and Health Promotion Italian National Institute of Health Rome ItalyAbstract 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.https://doi.org/10.1002/trc2.12327algorithmDementiaearly onset dementiahealth electronic datamild cognitive impairmentprevalence |
| spellingShingle | Ilaria Bacigalupo Flavia L. Lombardo Anna Maria Bargagli Silvia Cascini Nera Agabiti Marina Davoli Silvia Scalmana Annalisa Di Palma Annarita Greco Marina Rinaldi Roberta Giordana Daniele Imperiale Piero Secreto Natalia Golini Roberto Gnavi Franca Lovaldi Carlo A. Biagini Elisa Gualdani Paolo Francesconi Natalia Magliocchetti Teresa Di Fiandra Nicola Vanacore Identification of dementia and MCI cases in health information systems: An Italian validation study Alzheimer’s & Dementia: Translational Research & Clinical Interventions algorithm Dementia early onset dementia health electronic data mild cognitive impairment prevalence |
| 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 | algorithm Dementia early onset dementia health electronic data mild cognitive impairment prevalence |
| url | https://doi.org/10.1002/trc2.12327 |
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