Costs associated with adverse events during treatment episodes for adult attention-deficit/hyperactivity disorder
Bibliographic record
Abstract
OBJECTIVE: Attention-deficit/hyperactivity disorder (ADHD) medication is frequently associated with adverse events (AEs), but limited real-world data exist regarding their costs from a payer's perspective. Therefore, this study evaluated the healthcare costs associated with common AEs among adult patients treated for ADHD in the US. METHODS: Eligible adults treated for ADHD were identified from a large US claims database (1 October 2015-30 September 2021). A retrospective cohort study design was used to assess excess healthcare costs and costs directly related to AE-specific claims per-patient-per-month (PPPM) associated with 10 selected AEs during ADHD treatment. To account for all costs associated with the AE, treatment episodes with a given AE were compared to similar treatment episodes without this AE. Entropy balancing was used to create cohorts with similar characteristics. Studied AEs were selected based on their prevalence in clinical trials for common ADHD medications and were identified from ICD-10-CM diagnosis codes recorded in claims. RESULTS: < .05). LIMITATIONS: AEs were identified based on recorded diagnosis on medical claims and likely represent more severe AEs. Therefore, costs may not be representative of milder AEs. CONCLUSIONS: This study found that AEs occurring during ADHD treatment episodes are associated with significant healthcare costs. This highlights the potential of treatments with favorable safety profiles to alleviate the burden experienced by patients and the healthcare system.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".