The PharmNet Harm Reduction Intervention for Community Pharmacies: Protocol for a Pilot Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: The overdose epidemic in the United States has continued to worsen despite substantial efforts to mitigate its harms. The opioid antagonist naloxone has been identified as a key means of reducing the prevalence of fatal overdoses. An important evidence-based approach to optimizing naloxone's impact is to seed it throughout the community, because bystanders are often able to reverse overdoses more quickly than first responders and sometimes are the only possible means of overdose reversal. As part of a multipronged approach to distributing naloxone nationwide, community pharmacies have been identified as ideal venues for naloxone dispensing, especially under standing orders. However, dispensing rates remain surprisingly low, and there is a need to understand how best to engage community pharmacies in naloxone-based harm reduction services. OBJECTIVE: The objective of this trial is to determine whether a tailored, pragmatic pharmacy intervention (PharmNet) results in greater naloxone dispensing relative to baseline (the prior 3 months) compared to a control condition. This pilot trial is intended to determine whether it is appropriate to invest the substantial resources that would be required to conduct a full-scale, randomized controlled study of PharmNet. METHODS: We will conduct a 3-month randomized controlled pilot trial consisting of 2 parallel groups with a 4:3 allocation ratio. A group of 7 independent pharmacies from rural areas in Indiana will be randomly assigned to either the PharmNet intervention arm (n=4) or the control arm (n=3). The primary outcome will be overall naloxone dispensing (both at cost and free), and secondary outcomes will include the distribution of referral cards and multiple variables at the level of individual staff members. Dispensing data will be collected for the 3 months prior to the intervention and the 3 months of the intervention, and all other data will be collected using a pretest-posttest design. The primary analysis will be a generalized linear mixed model with a Poisson distribution with fixed effects for group, time, and their interaction and a random effect for pharmacy ID to account for repeated measures within pharmacies. RESULTS: This study was approved by the Indiana University institutional review board in 2 phases (August 2, 2021, and April 26, 2022) and was funded by the Indiana University Grand Challenge: Responding to the Addictions Crisis. CONCLUSIONS: If this study produces evidence that the PharmNet intervention results in increased naloxone dispensing relative to control pharmacies, it will be both appropriate and important to study it in a large, full-scale randomized controlled trial. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/42373.
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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 | 0.046 | 0.038 |
| Meta-epidemiology (narrow) | 0.009 | 0.005 |
| Meta-epidemiology (broad) | 0.013 | 0.007 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.009 | 0.013 |
| Insufficient payload (model declined to judge) | 0.118 | 0.017 |
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".