Evidence map›Paper›PMID 40855523›Full record

ArticleBMC geriatrics2025

Causal effect of conventional anti-dementia drugs on economic burden: an orthogonal double/debiased machine learning approach.

Xiangxiang Jiang, Gang Lv, Jordan Franklin, Minghui Li, Z Kevin Lu

Abstract read
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Article in BMC geriatrics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Xiangxiang JiangDepartment of Clinical Pharmacy and Outcomes Sciences, College of Pharmacy, University of South Carolina, 715 Sumter Street, Columbia, SC, 29208, USA.
Gang LvDepartment of General Surgery, The First Medical Center of Chinese PLA General Hospital, Beijing, China.
Jordan FranklinDepartment of Clinical Pharmacy and Outcomes Sciences, College of Pharmacy, University of South Carolina, 715 Sumter Street, Columbia, SC, 29208, USA.
Minghui LiDepartment of Clinical Pharmacy and Translational Science, University of Tennessee Health Science Center, Memphis, TN, USA.
Z Kevin LuDepartment of Clinical Pharmacy and Outcomes Sciences, College of Pharmacy, University of South Carolina, 715 Sumter Street, Columbia, SC, 29208, USA. lu32@email.sc.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe Inflation Reduction Act (IRA) did not introduce a cap on out-of-pocket (OOP) for newly approved Alzheimer's Disease (AD) drugs, such as lecanemab which is covered under Medicare Part B. Therefore, expanding the use of conventional anti-dementia drugs is critical to addressing the growing economic burden of dementia. In this study, we aimed to evaluate the causal relationship between specific conventional anti-dementia drug use and various healthcare costs with the Double/Debiased Machine Learning (DML) approach.

methodsLeveraging data from the Medicare Current Beneficiary Survey (MCBS) spanning 2015 to 2019, we utilized a nationally representative survey linked to Medicare data in this study. The presence of Alzheimer's Disease and Related Dementias (ADRD) and anti-dementia drug use was determined through Medicare claims data. The health care costs were measured as total medical costs and categorized into Medicare costs, OOP costs, inpatient costs, and outpatient costs. Conventional anti-dementia drugs include Cholinesterase inhibitors (ChEIs) and N-methyl-D-aspartate receptor (NMDAR) antagonists. The DML techniques were employed to investigate causal relationships.

resultsA total of 12,764,487 weighted older adults with ADRD were included, with 34.60% of them using anti-dementia drugs. Using anti-dementia drugs could significantly reduce Medicare costs and inpatient costs by $4,804.26 and $2,842.48 on average (P < 0.001), while did not significantly influence total costs, OOP costs, and outpatient costs. ChEIs use could help decrease Medicare costs and inpatient costs significantly (P < 0.05), whereas the NMDAR antagonist (memantine) showed no statistically significant effect across all cost types. Both donepezil and rivastigmine could help significantly decrease Medicare costs and inpatient costs (P < 0.001). Additionally, anti-dementia drug use could significantly reduce Medicare costs and inpatient costs among non-Hispanic Whites, and significantly lower inpatient costs among non-Hispanic Blacks (P < 0.05).

conclusionThis study revealed the causal relationship between anti-dementia drug use and Medicare costs by employing DML. ChEIs were found to be contributors to the decreased Medicare costs and inpatient costs, which could mainly be attributed to donepezil. The use of donepezil should be expanded, considering the significant benefits. Furthermore, a lower OOP cap for ADRD beneficiaries should be established under the IRA.

Indexed as

Alzheimer DiseaseCost of IllnessDementiaHealth Care CostsHealth ExpendituresMachine LearningNootropic AgentsAgedAged, 80 and overCholinesterase InhibitorsFemaleHumansMaleMedicareUnited StatesCholinesterase InhibitorsNootropic AgentsAlzheimer's disease and related dementia (ADRD)Anti-dementia drugsDouble/Debiased machine learning (DML)Economic burden

Identifiers

PMID40855523
PMCPMC12376492

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.