Generation and validation of algorithms to identify subjects with dementia using administrative data
| Autor: | Carlo Ferrarese, Ettore Beghi, Alessandro Nobili, Elisa Bianchi, Emanuele Amodio, Lucio Tremolizzo, Ildebrando Appollonio, Luca Cavalieri d’Oro, Giorgia Giussani, Valeria Isella, Jacopo C. DiFrancesco, Laura Cortesi, Alessandra Pina |
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| Přispěvatelé: | Difrancesco, J, Pina, A, Giussani, G, Cortesi, L, Bianchi, E, Cavalieri d'Oro, L, Amodio, E, Nobili, A, Tremolizzo, L, Isella, V, Appollonio, I, Ferrarese, C, Beghi, E, DiFrancesco, Jacopo C, Pina, Alessandra, Giussani, Giorgia, Cortesi, Laura, Bianchi, Elisa, Cavalieri d'Oro, Luca, Amodio, Emanuele, Nobili, Alessandro, Tremolizzo, Lucio, Isella, Valeria, Appollonio, Ildebrando, Ferrarese, Carlo, Beghi, Ettore |
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
Male
medicine.medical_specialty Neurology Databases Factual Administrative data Dermatology Disease Sensitivity and Specificity Medical Records 03 medical and health sciences 0302 clinical medicine Sensitivity Cost of Illness medicine Prevalence Dementia Humans 030212 general & internal medicine MED/01 - STATISTICA MEDICA Neuroradiology Aged Aged 80 and over MED/26 - NEUROLOGIA business.industry Medical record Neuropsychology Memantine General Medicine medicine.disease Algorithm Psychiatry and Mental health Italy Specificity Female Neurology (clinical) Neurosurgery business 030217 neurology & neurosurgery Algorithms medicine.drug |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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