Dataset Information

Epidemiology of dementia: prevalence and incidence estimates using validated electronic health records from primary care.

ABSTRACT: Purpose:Updated estimates of incidence and prevalence of dementia are crucial to ensure adequate public health policy. However, most of the epidemiological studies in the population in Spain were conducted before 2010. This study assessed the validity of dementia diagnoses recorded in electronic health records contained in a large primary-care database to determine if they could be used for research purposes. Then, to update the epidemiology of dementia in Catalonia (Spain), we estimated crude and standardized prevalence and incidence rates of dementia in Catalonia in 2016. Methods:The System for the Development of Research in Primary Care (SIDIAP) database contains anonymized information for >80% of the Catalan population. Validity of dementia codes in SIDIAP was assessed in patients at least 40 years old by asking general practitioners for additional evidence to support the diagnosis. Crude and standardized incidence and prevalence (95% CI) in people aged ?65 years were estimated assuming a Poisson distribution. Results:The positive predictive value of dementia diagnoses recorded in SIDIAP was estimated as 91.0% (95% CI 87.5%-94.5%). Age-and sex-standardized incidence and prevalence of dementia were 8.6/1,000 person-years (95% CI 8.0-9.3) and 5.1% (95% CI 4.5%-5.7%), respectively. Conclusion:SIDIAP contains valid dementia records. We observed incidence and prevalence estimations similar to recent face-to-face studies conducted in Spain and higher than studies using electronic health data from other European populations.

SUBMITTER: Ponjoan A

PROVIDER: S-EPMC6407519 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Epidemiology of dementia: prevalence and incidence estimates using validated electronic health records from primary care.

Ponjoan Anna A Garre-Olmo Josep J Blanch Jordi J Fages Ester E Alves-Cabratosa Lia L Martí-Lluch Ruth R Comas-Cufí Marc M Parramon Dídac D Garcia-Gil María M Ramos Rafel R

Clinical epidemiology 20190304

<h4>Purpose</h4>Updated estimates of incidence and prevalence of dementia are crucial to ensure adequate public health policy. However, most of the epidemiological studies in the population in Spain were conducted before 2010. This study assessed the validity of dementia diagnoses recorded in electronic health records contained in a large primary-care database to determine if they could be used for research purposes. Then, to update the epidemiology of dementia in Catalonia (Spain), we estimated ...[more]

PMID: 30881138

Similar Datasets

Project description:It is unclear how medication use evolved before diagnosis of dementia (DoD). This study aims to identify varied patterns of polypharmacy before DoD, their prevalence and possible complications. We collected primary care e-health records for 33,451 dementia patients in Wales from 1990 to 2015. The medication uses in every 5-year period along with 20-years prior to dementia diagnosis were considered. Exploratory factor analysis was used to identify clusters of medicines for every 5-year period. The prevalence of patients taking three or more medications was 82.16%, 69.7%, 41.1% and 5.5% in the Period 1 (0-5 years before DoD) ~ Period 4 (16-20 years before DoD) respectively. The Period 1 showed 3 clusters of polypharmacy - medicines for respiratory/urinary infections, arthropathies and rheumatism, and cardio-vascular disease (CVD) (66.55%); medicines for infections, arthropathies and rheumatism (AR), cardio-metabolic disease (CMD) and depression (22.02%); and medicines for arthropathies, rheumatism and osteoarthritis (2.6%). The Period 2 showed 4 clusters of polypharmacy - medicines for infections, arthropathies, and CVD (69.7%); medicines for CVD and depression (3%); medicines for CMD and arthropathies (0.3%); and medicines for AR, and CVD (2,5%). The Period 3 showed 6 clusters of polypharmacy - medicines for infections, arthropathies, and CVD (41.1%); medicines for CVD, acute-respiratory-infection (ARI), and arthropathies (1.25%); medicines for AR (1.16%); medicines for depression, anxiety (0.06%); medicines for CMD (1.4%); and medicines for dermatologic disorders (0.9%). The Period 4 showed 3 main clusters of polypharmacy - medicines for infections, arthropathy, and CVD (5.5%); medicines for anxiety, ARI (2.4%); and medicines for ARI and CVD (2.1%). As the development towards dementia progressed, the associative diseases tended to cluster with a larger prevalence in each cluster. Farther away before DoD, the clusters of polypharmacy tended to be clearly distinct between each other, resulting in an increasing number of patterns, but in a smaller prevalence.

Project description:IntroductionPossible dementia is usually identified in primary care by general practitioners (GPs) who refer to specialists for diagnosis. Only two-thirds of dementia cases are currently recorded in primary care, so increasing the proportion of cases diagnosed is a strategic priority for the UK and internationally. Variables in the primary care record may indicate risk of developing dementia, and could be combined in a predictive model to help find patients who are missing a diagnosis. We conducted a meta-analysis to identify clinical entities with potential for use in such a predictive model for dementia in primary care.Methods and findingsWe conducted a systematic search in PubMed, Web of Science and primary care database bibliographies. We included cohort or case-control studies which used routinely collected primary care data, to measure the association between any clinical entity and dementia. Meta-analyses were performed to pool odds ratios. A sensitivity analysis assessed the impact of non-independence of cases between studies. From a sift of 3836 papers, 20 studies, all European, were eligible for inclusion, comprising >1 million patients. 75 clinical entities were assessed as risk factors for all cause dementia, Alzheimer's (AD) and Vascular dementia (VaD). Data included were unexpectedly heterogeneous, and assumptions were made about definitions of clinical entities and timing as these were not all well described. Meta-analysis showed that neuropsychiatric symptoms including depression, anxiety, and seizures, cognitive symptoms, and history of stroke, were positively associated with dementia. Cardiovascular risk factors such as hypertension, heart disease, dyslipidaemia and diabetes were positively associated with VaD and negatively with AD. Sensitivity analyses showed similar results.ConclusionsThese findings are of potential value in guiding feature selection for a risk prediction tool for dementia in primary care. Limitations include findings being UK-focussed. Further predictive entities ascertainable from primary care data, such as changes in consulting patterns, were absent from the literature and should also be explored in future studies.

Dataset Information

Epidemiology of dementia: prevalence and incidence estimates using validated electronic health records from primary care.

Publications

Epidemiology of dementia: prevalence and incidence estimates using validated electronic health records from primary care.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets