The Howard Street Method: A Community Pharmacy-led Low Dose Overlap Buprenorphine Initiation Protocol for Individuals Using Fentanyl
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVES: Buprenorphine treatment significantly reduces morbidity and mortality for people with opioid use disorder. Fear of precipitated withdrawal remains a barrier to starting buprenorphine for patients who use synthetic opioids, particularly fentanyl. We aim to evaluate the development and implementation of a buprenorphine low dose overlap initiation (LDOI) protocol in an urban public health community pharmacy. METHODS: We performed a retrospective chart review of patients with nonprescribed fentanyl use (N = 27) to examine clinical outcomes of a buprenorphine LDOI schedule, named the Howard Street Method, dispensed from a community pharmacy in San Francisco from January to December 2020. RESULTS: Twenty-seven patients were prescribed the Howard Street Method. Twenty-six patients picked up the prescription and 14 completed the protocol. Of those who completed the protocol, 11 (79%) reported no symptoms of withdrawal and 3 (21%) reported mild symptoms. Four patients (29%) reported cessation of full opioid agonist use and 10 (71%) reported reduction in their use by the end of the protocol. At 30 days, 12 patients (86%) were retained in care and 10 (71%) continued buprenorphine. At 180 days, 6 patients (43%) were retained in care and 2 (14%) were still receiving buprenorphine treatment. CONCLUSIONS: We found that a LDOI blister-pack protocol based at a community pharmacy was a viable intervention for starting buprenorphine treatment and a promising alternative method for buprenorphine initiation in an underresourced, safety-net population of people using fentanyl.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it