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Neurological Sciences
Published in: Neurological Sciences 10/2019

01-10-2019 | Dementia | Original Article

Generation and validation of algorithms to identify subjects with dementia using administrative data

Authors: Jacopo C. DiFrancesco, Alessandra Pina, Giorgia Giussani, Laura Cortesi, Elisa Bianchi, Luca Cavalieri d’Oro, Emanuele Amodio, Alessandro Nobili, Lucio Tremolizzo, Valeria Isella, Ildebrando Appollonio, Carlo Ferrarese, Ettore Beghi

Published in: Neurological Sciences | Issue 10/2019

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Abstract

Objectives

To generate and validate algorithms for the identification of individuals with dementia in the community setting, by the interrogation of administrative records, an inexpensive and already available source of data.

Methods

We collected and anonymized information on demented individuals 65 years of age or older from ten general practitioners (GPs) in the district of Brianza (Northern Italy) and compared this with the administrative data of the local health protection agency (Agenzia per la Tutela della Salute). Indicators of the disease in the administrative database (diagnosis of dementia in the hospital discharge records; use of cholinesterase inhibitors/memantine; neuropsychological tests; brain CT/MRI; outpatient neurological visits) were used separately and in different combinations to generate algorithms for the detection of patients with dementia.

Results

When used individually, indicators of dementia showed good specificity, but low sensitivity. By their combination, we generated different algorithms: I-therapy with ChEI/memantine or diagnosis of dementia at discharge or neuropsychological tests (specificity 97.9%, sensitivity 52.5%); II-therapy with ChEI/memantine or diagnosis of dementia at discharge or neuropsychological tests or brain CT/MRI or neurological visit (sensitivity 90.8%, specificity 70.6%); III-therapy with ChEI/memantine or diagnosis of dementia at discharge or neuropsychological tests or brain CT/MRIMRI and neurological visit (specificity 89.3%, sensitivity 73.3%).

Conclusions

These results show that algorithms obtained from administrative data are not sufficiently accurate in classifying patients with dementia, whichever combination of variables is used for the identification of the disease. Studies in large patient cohorts are needed to develop further strategies for identifying patients with dementia in the community setting.
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Metadata
Title
Generation and validation of algorithms to identify subjects with dementia using administrative data
Authors
Jacopo C. DiFrancesco
Alessandra Pina
Giorgia Giussani
Laura Cortesi
Elisa Bianchi
Luca Cavalieri d’Oro
Emanuele Amodio
Alessandro Nobili
Lucio Tremolizzo
Valeria Isella
Ildebrando Appollonio
Carlo Ferrarese
Ettore Beghi
Publication date
01-10-2019
Publisher
Springer International Publishing
Keywords
Dementia
Dementia
Published in
Neurological Sciences / Issue 10/2019
Print ISSN: 1590-1874
Electronic ISSN: 1590-3478
DOI
https://doi.org/10.1007/s10072-019-03968-3

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