The incidence of dementia, including Alzheimer’s disease (AD) and related dementia (RD), is increasing globally.
It is expected that the number of dementia patients will triple in the next 30 years, and it will reach it by 2050 Nearly 153 million cases
.
Therefore, aging researchers advocate more methodological studies to assess the risk factors of dementia, hoping to reduce the morbidity and mortality associated with dementia
.
Although increasing age and family history are important predictors of dementia, sociodemographic and behavioral factors also play a role
.
Currently, it is estimated that at least 40% of the risk of dementia can be attributed to potentially modifiable factors, many of which start in the early and middle stages
.
The time difference between these early and mid-term exposures and the onset of dementia, as well as the limited scale of epidemiological studies, makes routinely collected health data a promising tool for risk factor research in larger cohorts
.
However, before conducting such research, it is necessary to understand the degree to which administrative health data accurately grasp dementia in the population cohort
.
Nearly 40 studies evaluated the accuracy of dementia case identification in administrative databases
.
Most of these studies focus on all causes of dementia and are extracted from a single administrative data set
.
In addition, due to different clinical practices and changes in electronic health records (her), administrative databases in different countries also differ in the accuracy of dementia diagnosis
.
In this way, Karen C.
Schliep and others of the University of Utah in the United States combined the clinical diagnosis (test method) of AD, RD and all-cause dementia found in outpatient, hospitalization, medical insurance records and death certificates with the participation in CacheCounty Memory and Health in the United States.
Compare with the research diagnosis (reference method) of the same individual in the Aging Study (CCSMHA)
.
The main goal is to evaluate the accuracy of AD, RD and all causes of dementia through each source and all sources combined, assuming that the information from different data sources can be complementary and provide a more accurate situation
.
They will participate in the clinical diagnosis of Alzheimer's disease (AD) and all-cause dementia in outpatient operations, inpatients, medical insurance administrative records and death certificates with the Catch County Memory, Health and Aging Study (CCSMHA) The study diagnoses of the authors were compared (1995-2008, N=5092)
.
Combining clinical health data from all sources improves the sensitivity of identifying all-cause dementia (71%) and AD (48%) while maintaining relatively high specificity (81% and 93%, respectively)
.
Medical insurance reimbursement has the highest sensitivity to case identification (57% and 40%, respectively)
.
The important significance of this research lies in the discovery: administrative health data may provide a less accurate method than research evaluation to identify individuals with dementia, but by combining health data sources, the accuracy will be improved
.
Evaluation of all causes of dementia and specific causes of dementia, such as AD, will lead to increased sensitivity, but at the cost of specificity
.
Original source:
Schliep KC, Ju S, Foster NL, et al.
How good are medical and death records for identifying dementia? Alzheimer's & Dementia.
Published online December 7, 2021:alz.
12526.
doi:10.
1002/alz.
12526
How good are medical and death records for identifying dementia? Alzheimer's & Dementia.
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