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Record W4317685275 · doi:10.1111/add.16124

Clarifying ‘safer supply’ to enrich policy discussions

2023· editorial· en· W4317685275 on OpenAlexaboutno aff
Beau Kilmer, Bryce Pardo

Bibliographic record

VenueAddiction · 2023
Typeeditorial
Languageen
FieldMedicine
TopicOpioid Use Disorder Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsSAFERBuprenorphineCounterfeitHeroinHarm reductionMethadoneBusinessMedicineInternet privacyMarketingDrugOpioidComputer securityPharmacologyPublic healthLawNursingPolitical science

Abstract

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In response to the overdose crisis in the United States and Canada, a debate is emerging about providing a ‘safer supply’ to people who use drugs [1-3]. However, ambiguity about the term muddles discussions and could stifle innovation. There has always been uncertainty about the composition of drugs sold in illegal markets. Today’s street drug mixtures increasingly include illegally manufactured fentanyl and other harmful drug combinations, elevating health risks for people who use drugs (PWUD) [4, 5]. Counterfeit pills containing fentanyl create more confusion and are especially risky to unsuspecting or novice users [5]. While there is emerging interest in increasing access to drug-checking services and supervised consumption sites, there is also a growing debate about providing PWUD with a drug of known composition in lieu of what is sold in illegal markets [1-3], sometimes referred to as ‘safe supply’ or ‘safer supply’. However, these terms are used to describe a diverse set of interventions with different levels of evidence, target populations, outcomes and regulatory involvement. One approach to safer supply involves offering medications to people who use drugs, sometimes for their drug of choice, sometimes for an alternative. There is no consensus about which substances and under what conditions of use constitute safer supply versus more traditional treatments. Is liquid methadone consumed at a clinic a form of safer supply? What about diamorphine (heroin) or pharmaceutical-grade fentanyl? Health Canada distinguishes the goals between opioid agonist treatment (which in Canada includes methadone, buprenorphine and slow-release oral morphine) and safer supply (which includes hydromorphone, fentanyl, other opioids and some stimulants or benzodiazepines), stating: ‘Usually, the goal of traditional [opioid agonist treatment] is for a patient to stop taking drugs… [whereas] safer supply refers to providing prescribed medications as a safer alternative to the toxic illegal drug supply to people who are at high risk of overdose’ [6]. Some medical approaches to safer supply require supervision by a health professional (e.g. supervised injectable heroin treatment [7]), but another approach implemented in parts of Canada expands a range of prescribed substances for PWUD that are ‘provided in a less clinical and more flexible way’ (i.e. with minimal or no supervision) with the goal of preventing overdose from drugs found in the illegal supply [6]. For example, a clinic in Vancouver now allows registered patients to purchase individual doses of pharmaceutical-grade fentanyl that are priced competitively to opioids sold on the street [8]. Some are promoting other safer supply interventions outside the traditional prescription model. One approach that has been proposed is a cooperative purchase-based model of pharmaceutical-grade drugs (e.g. heroin) for members without a prescription to ensure quality and competitive pricing [9]. This model is based on the cannabis compassion clubs or buyers’ clubs that emerged in the 1980s during the HIV/AIDS epidemic. Another approach is for a group to purchase illegal drugs, test them and then re-package and distribute them to PWUD. The Drug User Liberation Front in Vancouver has held at least five events where they have distributed the tested and re-packaged drugs without inciting a crackdown by local law enforcement [10, 11]. In August 2022, it was reported that a ‘Cocaine, Heroin and Methamphetamine Compassion Club and Fulfilment Centre’ had been in operation in Vancouver for a month, although the club was not authorized by the government and the drugs were not sourced from a pharmaceutical company; they were purchased from the dark web, tested and sold at cost [12, 13]. Access to this club is limited to members of the Vancouver Area Network of Drug Users who are at least 19 years old [13]. Beyond the variation in substances, levels of supervision and provision, discussions associating safer supply with drug legalization can create additional ambiguity. For example, in an essay about British Columbia’s safer supply prescription program, one researcher concluded, ‘Hopefully British Columbia's novel approach will gain wider acceptance. If so, it will provide a "real world" lesson that drug prohibition kills and legalization saves lives' [14]. In an example from the media, an essay published by a major news outlet included a subheading which read: ‘Ending the overdose crisis will require full drug legalization—so people can access a safe supply, with accurate information about the dosage’ [15]. A prescription model that limits access to individuals currently using drugs is different from allowing people to test and distribute illegally produced drugs, which is very different from a legalization model that regulates drug sales to any adult. Policy debates about reducing harms posed by the increasingly dangerous drug supply would be more productive if participants recognized and described the particularities of interventions instead of referring to them broadly as safer supply. Such generalities limit nuanced discussions about the available policy options. In Table 1, we offer a framework to facilitate discussions, highlighting four examples of interventions sometimes referred to as safer supply; these options are not necessarily mutually exclusive. We do not include a column for traditional opioid agonist treatment (such as buprenorphine and methadone), which is sometimes ultimately focused upon abstinence, but realize that some people may consider this safer supply. Addressing the ambiguity surrounding safer supply is not simply an academic exercise. We are concerned that conflating prescription models with some of these other approaches—about which we are not offering judgments—could create barriers to piloting and evaluating new interventions, especially in the United States. For example, while there are documented barriers to accessing existing treatments for substance use disorder in the United States, there is also a growing recognition of the need to pilot and evaluate new medication treatments, especially those that are already approved for treating opioid use disorder (OUD) in other countries. After an extensive review of the international evidence for prescribing diamorphine for those with OUD, a RAND report argued for clinical trials in ‘some of the US jurisdictions that already provide a spectrum of social services and good accessibility to medication treatments for OUD’ [17]. The Stanford–Lancet Commission on the North American Opioid Crisis recommended that given the exigency of the overdose crisis, ‘regulatory agencies should increase their willingness to approve drugs on the basis of data from trials done abroad’ [18]. If these efforts become labeled as safer supply and confused with legalization, or conflated with the actions of Purdue Pharma and some other oxycodone producers (e.g. [19]), this could create major political barriers to adoption or deter much-needed research. It is critical that decision-makers innovate, especially when it comes to reducing harms related to drug consumption. Some of these ideas will be controversial, but that does not mean they should not be discussed. Being specific about the intervention, instead of using slogans such as safer supply, could make these conversations more productive. We are grateful to Jon Caulkins, Keith Humphreys, Peter Reuter, Dan Werb, and the anonymous reviewers for their comments on an earlier version. The views presented here only reflect those of the authors. None. Beau Kilmer: Conceptualization; investigation; writing-original draft. Bryce A. Pardo: Conceptualization; investigation; writing-original draft.

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.032
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.003

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.

Opus teacher head0.013
GPT teacher head0.318
Teacher spread0.306 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEditorial

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".

Quick stats

Citations9
Published2023
Admission routes1
Has abstractyes

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