Medical resource use and costs among pain patients with potential opioid-tolerability issues
Bibliographic record
Abstract
OBJECTIVE: To estimate excess medical resource use and costs associated with prescription opioid (RxO) tolerability issues. DESIGN: This was an observational, retrospective analysis of deidentified administrative claims data. SETTING: The study included commercially insured patients treated in different healthcare settings captured in the Truven MarketScan claims database. PATIENTS: Patients aged 18-64 years initiating treatment with an RxO (index) and continuously treated with pain relievers over a 6-month period were selected. "Switchers" were patients who discontinued their index RxO and switched to non-RxO pain relievers < 30 days post-index, and whose last pain reliever in the 6-month follow-up period was not an RxO. Such switching was considered a proxy for RxO-tolerability issues. "Continuous RxO users" were patients who remained on the index RxO for the follow-up period. Switchers and continuous RxO users were matched 1:1 on propensity score, baseline medical costs, index RxO days supply, and short-/long-acting index RxO. MAIN OUTCOME MEASURES: Six-month follow-up medical resource use and costs were compared between matched switchers and continuous RxO users. RESULTS: A total of 10,704 pairs of switchers and continuous RxO users were matched. In the 6-month follow-up period, switchers had more outpatient (7.5 vs 6.8; p < 0.001) and inpatient (0.05 vs 0.04; p = 0.002) visits and longer inpatient stays (0.26 days vs 0.19; p = 0.006) compared to continuous RxO users. Switchers also had higher total medical costs ($4,522 vs $3,657; p < 0.001). CONCLUSIONS: Switchers incur greater medical resource use and costs than similar patients continuously treated with their index RxO.
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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 | 0.000 |
| 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".