Financial Burden of Atopic Dermatitis Out-of-Pocket Health Care Expenses in the United States
Bibliographic record
Abstract
BACKGROUND: Atopic dermatitis (AD) is associated with considerable financial cost. However, the full burden of out-of-pocket (OOP) expenses is not well understood. OBJECTIVE: We sought to characterize the OOP health care expenses associated with AD management. METHODS: A 25-question voluntary online survey was administered to National Eczema Association members worldwide (n = 113,502). Inclusion criteria (US residents age ≥18 years who either self-reported had AD or were primary caregivers of individuals with AD) were met by 77.3% (1118/1447) of respondents. RESULTS: Respondents reported OOP expenses in 3 categories: (1) health care providers and prescriptions, including health care provider visit deductibles (68.7% [686]), prescription co-pays (64.3% [635]), and prescriptions not covered by insurance (48.6% [468]); (2) nonprescription health care products, including moisturizers (94.3% [934]), hygiene products (85.0% [824], allergy medications (75.1% [715]), itch relievers (68.25% [647]), dietary supplements (52.2% [491]), and sleep aids (37.0% [336]); and (3) complementary approaches, including cleaning products (74.7% [732]), clothing/bedding (44.8% [430]), alternative medications (19.0% [180]), and adjunctive therapies (15.9% [150]). The median annual AD OOP expense was US $600 (range, US $0-$200,000), with 41.9% (364) reporting expenditures US $1000 or greater. CONCLUSIONS: Out-of-pocket expenses place a significant financial burden on individuals with AD. Additional studies are needed to better understand associations and impact of OOP costs.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".