Healthcare Costs and Resource Utilization in Patients with Infantile Spasms Treated with H.P. Acthar Gel®
Bibliographic record
Abstract
INTRODUCTION: The purpose of this study was to describe healthcare resource utilization and costs resulting from early (within 30 days of diagnosis) versus late (>30 days after diagnosis) treatment with prescriptions for H.P. Acthar(®) Gel (repository corticotropin injection; Acthar; Mallinckrodt) to manage infantile spasms (IS). METHODS: We included all patients in the Truven Health MarketScan(®) Commercial Claims and Encounters Database and the Truven Health MarketScan Multi-State Medicaid Database who were diagnosed with IS from 2007 to 2012. We performed unadjusted and adjusted regressions examining the relationship between healthcare resource utilization variables and their associated costs to compare outcomes in the early and late Acthar users. RESULTS: A total of 252 patients with IS who received Acthar fit our study criteria; 191 (76%) were early Acthar users. In adjusted analyses, we found that early Acthar use was associated with, on average, 3.8 fewer outpatient services (99% CI 0.7-6.7 fewer services). We did not find significant associations between early prescriptions for Acthar and number of hospitalizations, emergency room visits, prescription medications filled, or total costs of health services. CONCLUSION: Patients prescribed Acthar within 30 days of their IS diagnoses tended to have fewer outpatient services performed compared to patients prescribed Acthar later in the disease process. Although additional research is needed to confirm these exploratory findings, physicians may consider early treatment with Acthar to manage IS. FUNDING: This study was funded by a grant to the University of Washington from Mallinckrodt Pharmaceuticals.
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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 | 0.003 |
| 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 | 0.001 | 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".