Lifetime medical costs attributable to sickle cell disease among nonelderly individuals with commercial insurance
Bibliographic record
Abstract
Sickle cell disease (SCD) is a severe monogenic disease associated with high morbidity, mortality, and a disproportionate burden on Black and Hispanic communities. Our objective was to estimate the total healthcare costs and out-of-pocket (OOP) costs attributable to SCD among commercially insured individuals over their nonelderly lifetimes (0 to 64 years of age). We constructed a retrospective cohort of individuals with diagnosed SCD using Truven Health Marketscan commercial claims data from 2007 through 2018, compared with matched control subjects from the Medical Expenditure Panel Survey. We estimated Kaplan-Meier sample average costs using previously reported survival curves for SCD and control subjects. Individuals with SCD (20 891) and control subjects (33 588) were included in our analysis. The SCD sample had a mean age of 25.7 (standard deviation, 17.4) years; 58.0% were female. Survival-adjusted costs of SCD peaked at age 13 to 24 years and declined at older ages. There was no significant difference in total medical costs or OOP costs between the sexes. SCD-attributable costs over 0 to 64 years of age were estimated to be $1.6 million (95% confidence interval [CI], $1.3M-$1.9M) and $1.7 million (95% CI, $1.4M-$2.1M) for females and males with SCD, respectively. The corresponding OOP estimates were $42 395 (95% CI, $34 756-$50 033) for females and $45 091 (95% CI, $36 491-$53 691) for males. These represent a 907% and 285% increase in total medical and OOP costs over control subjects, respectively. Although limited to the commercially insured population, these results indicate that the direct economic burden of SCD is substantial and peaks at younger ages, suggesting the need for curative and new medical therapies.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".