Total Healthcare Costs across the Alzheimer’s Disease Continuum in the United States (US)
Bibliographic record
Abstract
Abstract Background This study describes the total healthcare costs integrating direct, indirect, and intangible or emotional cost components across the severity stages of Alzheimer’s disease (AD) in US. Method Utilizing Health and Retirement Study (HRS) data (1994‐2018), a bi‐annual US national survey of older adults, we assessed out‐of‐pocket and indirect costs, including unpaid caregiving services, missed workdays, and early retirement. HRS, analyzed with sampling weights, provided a representative US national sample. Mild cognitive impairment (MCI) and AD severity were ascertained using the modified telephone interview of cognitive status (TICS‐M). Besides data from HRS, 100 pairs of patients and their caregivers were referred by physicians and surveyed for quality of life (QoL). Patient and caregiver responses to QoL were converted to utility values. The MCI‐ or AD‐specific health utility value was subtracted from the age‐standardized health utility value from the general US population to derive the estimate of utility reduction due to AD. Intangible costs were calculated using the willingness to pay threshold of $150,000 for one quality‐adjusted life year gained. Direct costs were derived from current literature, comprising patient and caregiver healthcare costs, patient social care costs and nursing home costs. Costs were adjusted to the 2023 US price index. Result HRS patient sample (N = 18,786) with MCI (n = 17,885) and AD (n = 901) were aged 67.8±10.7 and 80.9±9.3 years, 55.7% and 63.3% female, and 28.3% and 0.9% employed, respectively. A total of 100 patient‐caregiver pairs with MCI (n = 27) and AD (n = 73) were surveyed, with 21% and 47% of patients > 75 years, 59% and 48% female, and 7.4% and 4.1% employed, respectively. Figure 1 shows mean annual costs per patient across AD severity levels, with direct costs from literature, indirect costs estimated from HRS and intangible costs estimated from the patient‐caregiver survey. Total annual healthcare costs increased from $69,380 for MCI to $150,488 for severe AD. Conclusion This study provides a comprehensive view of escalating healthcare costs with worsening AD severity, emphasizing the need for targeted interventions to address the multifaceted economic impact on patients, caregivers, and society.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".