A study protocol for identifying aging trajectories toward chronic neurodegenerative diseases by means of Marche regional administrative databases - TREND project.


Journal

Frontiers in public health
ISSN: 2296-2565
Titre abrégé: Front Public Health
Pays: Switzerland
ID NLM: 101616579

Informations de publication

Date de publication:
2024
Historique:
received: 12 12 2023
accepted: 04 04 2024
medline: 8 5 2024
pubmed: 8 5 2024
entrez: 8 5 2024
Statut: epublish

Résumé

People are living longer but an increasing number of older people experience chronicity and disability in the latest years of their life. The Marche region is one of the Italian regions where people live the longest lives; therefore, the number of people with age-related chronic diseases is expected to be at least similar, if not higher, compared to the rest of Italy. The identification of the aging trajectories is of huge interest in the arena of public health. Administrative healthcare databases represent valuable reservoirs for reconstructing the trajectories of aging. Here, we present the protocol for a study (TREND project) aimed to integrate existing administrative databases into a Marche regional dataset in order to estimate the prevalence and incidence rates of age-related neurodegenerative diseases (ND), with a specific focus on Parkinsonism and Dementia. The TREND Project is a retrospective cross-sectional study. The source population includes permanent residents in the Marche region aged 40 years and older. A minimal dataset has been built up linking data on drug prescriptions, outpatient services, and diagnosis for hospital admission, from 2014 to 2021 in the Marche Region. Data on clinical outcomes (re-hospitalization, mortality, comorbidities), and therapeutic approaches (drugs and medicines) have been integrated with state-of-the-art statistical methods to define patients into different risk clusters and to analyze the aging trend by assessing the Comorbidity Index (CI) as a proxy for chronicity. Our research contributes to the integration of existing administrative databases on ND to create a Marche regional ND database, support regional health policy, and better understand patients' needs and their aging trajectories. This approach could be implemented also at the National level. Moreover, by linking different administrative data sources, this study sheds light on important issues related to ND, such as early-onset dementia; ethical aspects such as anticipated wills; problems of dementia in patients still in the job market, etc. The results of this study will contribute to the successful implementation of integrated care for patients affected by ND at regional or national levels.

Sections du résumé

Background UNASSIGNED
People are living longer but an increasing number of older people experience chronicity and disability in the latest years of their life. The Marche region is one of the Italian regions where people live the longest lives; therefore, the number of people with age-related chronic diseases is expected to be at least similar, if not higher, compared to the rest of Italy. The identification of the aging trajectories is of huge interest in the arena of public health. Administrative healthcare databases represent valuable reservoirs for reconstructing the trajectories of aging. Here, we present the protocol for a study (TREND project) aimed to integrate existing administrative databases into a Marche regional dataset in order to estimate the prevalence and incidence rates of age-related neurodegenerative diseases (ND), with a specific focus on Parkinsonism and Dementia.
Methods UNASSIGNED
The TREND Project is a retrospective cross-sectional study. The source population includes permanent residents in the Marche region aged 40 years and older. A minimal dataset has been built up linking data on drug prescriptions, outpatient services, and diagnosis for hospital admission, from 2014 to 2021 in the Marche Region. Data on clinical outcomes (re-hospitalization, mortality, comorbidities), and therapeutic approaches (drugs and medicines) have been integrated with state-of-the-art statistical methods to define patients into different risk clusters and to analyze the aging trend by assessing the Comorbidity Index (CI) as a proxy for chronicity.
Discussion UNASSIGNED
Our research contributes to the integration of existing administrative databases on ND to create a Marche regional ND database, support regional health policy, and better understand patients' needs and their aging trajectories. This approach could be implemented also at the National level. Moreover, by linking different administrative data sources, this study sheds light on important issues related to ND, such as early-onset dementia; ethical aspects such as anticipated wills; problems of dementia in patients still in the job market, etc. The results of this study will contribute to the successful implementation of integrated care for patients affected by ND at regional or national levels.

Identifiants

pubmed: 38716242
doi: 10.3389/fpubh.2024.1354538
pmc: PMC11075631
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

1354538

Informations de copyright

Copyright © 2024 Spazzafumo, Sabbatinelli, Biscetti, Balducci, Lilla, Ramini, Giuliani, Paciello, Rupelli, Pompili, Pelliccioni, Recchioni and Olivieri.

Déclaration de conflit d'intérêts

FB and LP were employed by the company Tech4Care srl. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Auteurs

Liana Spazzafumo (L)

Scientific Direction, IRCCS INRCA, Ancona, Italy.

Jacopo Sabbatinelli (J)

Department of Clinical and Molecular Sciences, Università Politecnica delle Marche, Ancona, Italy.
Clinic of Laboratory and Precision Medicine, IRCCS INRCA, Ancona, Italy.

Leonardo Biscetti (L)

Unit of Neurology, IRCCS INRCA, Ancona, Italy.

Francesco Balducci (F)

Tech4Care srl, Ancona, Italy.

Marco Lilla (M)

Regional Health Agency of Marche, Ancona, Italy.

Deborah Ramini (D)

Clinic of Laboratory and Precision Medicine, IRCCS INRCA, Ancona, Italy.

Angelica Giuliani (A)

Department of Clinical and Molecular Sciences, Università Politecnica delle Marche, Ancona, Italy.

Luca Paciello (L)

Tech4Care srl, Ancona, Italy.

Giuseppe Rupelli (G)

Regional Health Agency of Marche, Ancona, Italy.

Marco Pompili (M)

Regional Health Agency of Marche, Ancona, Italy.

Giuseppe Pelliccioni (G)

Unit of Neurology, IRCCS INRCA, Ancona, Italy.

Rina Recchioni (R)

Clinic of Laboratory and Precision Medicine, IRCCS INRCA, Ancona, Italy.

Fabiola Olivieri (F)

Department of Clinical and Molecular Sciences, Università Politecnica delle Marche, Ancona, Italy.
Clinic of Laboratory and Precision Medicine, IRCCS INRCA, Ancona, Italy.

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Classifications MeSH