Cost Analysis of Buprenorphine Extended-Release Injection Versus Sublingual Buprenorphine/Naloxone Tablets in a Correctional Setting
Bibliographic record
Abstract
Incarcerated clients experience high rates of opioid use disorder and overdose. It is critical that opioid agonist treatment (OAT) is provided in correctional facilities. However, few receive OAT due to concerns about diversion, misuse, and safety. Buprenorphine extended-release (BUP-XR), a monthly buprenorphine depot injection, could be especially advantageous in the correctional setting as it can prevent diversion and misuse, saving staff resources and time. An injection of BUP-XR is costly compared with a monthly supply of buprenorphine/naloxone (BUP/NX) tablets. We demonstrate that when factoring in the added costs of medication preparation, administration, monitoring, and personnel, it is more economical to provide BUP-XR than BUP/NX. Other facilities, by utilizing our cost breakdown, can determine whether BUP-XR is economically advantageous at their own facility.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".