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Commentary on Kurdyak <i>et al</i>. (2012): Methadone and other opioids – need for coordinated prescribing

2012· letter· en· W1586390098 on OpenAlexaboutno aff
Malcolm Dobbin, M.A. McDonough

Bibliographic record

VenueAddiction · 2012
Typeletter
Languageen
FieldMedicine
TopicOpioid Use Disorder Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsOxycodoneMethadoneMedicineMedical prescriptionHeroinOpioidAddictionBuprenorphineOpioid use disorderPrescription Drug MisuseHarm reductionPer capitaPsychiatryDrugEnvironmental healthPublic healthPharmacologyNursingPopulationInternal medicine

Abstract

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Drug epidemics change over time, and the important relationship between supply and harm is well recognized 1, 2. Abuse of pharmaceutical opioids is not new, but increased supply of a greater number of formulations has resulted in increasing problems within an ‘opioid-rich’ environment 3 similar to trends in obesity prevalence in ‘obesogenic’ environments. Several studies relate increased prescription opioid availability to increasing misuse 4, medical emergencies 5, poisoning death 6 and poisoning of children 7. Per capita global pharmaceutical opioid consumption has more than tripled in the last 12 years, and the United States and Canada now consume 60% of global morphine and 87% of global oxycodone supply between them 8. These countries are now well-advanced into an epidemic involving misuse of prescription opioids that shows no sign of abating 9, with other high-income 10, 11 and low-income countries 12 also affected. In this issue of Addiction, Kurdyak and colleagues describe the provision of prescription opioids to people during methadone maintenance treatment (MMT), often by prescribers and pharmacies not involved in their MMT 13 who may have been unaware of their MMT status. This raises a number of important questions about whether these were opioids sought and prescribed for the treatment of pain, treatment for opioid dependence because of subtherapeutic methadone dosing or as a source of income from on-selling to the ‘street market’. Further, it is unknown whether all prescribers were aware of each others' prescribing; for example, either by direct communication or awareness from urine drug screening to identify ‘unsanctioned’ opioid use. It remains a medical duty of care to protect vulnerable opioid-dependent individuals potentially at risk of poisoning deaths, and this principle should override individual patient privacy concerns when providing addictive and potentially dangerous drugs. In many countries, patient privacy is protected by legislation and safeguards which recognize the primacy of this duty of care to prevent disease and death. Also of concern is the high proportion of patients using short-acting combination products, many of which probably contain paracetamol/acetaminophen. Opioid-tolerant patients may require higher opioid analgesic doses, thereby increasing exposure to paracetamol with risk of paracetamol hepatotoxicity. The patient population eligibility criteria for social assistance in this study also suggests a greater risk because of the association between low socio-economic status and opioid poisoning death 14. There is also concern because the primary drugs of concern for patients seeking MMT for opioid dependence are increasingly prescription opioids, rather than heroin, and the unsanctioned use of sedating drugs such as opioids jeopardizes the safety of MMTs by contributing to combined drug toxicity causing many methadone-related deaths. Despite their limitations, existing systems designed to oversee subsidized drug supply can identify individuals at high risk of opioid-related death 15. A Washington State study identified that Medicaid patients experience a 5.7-fold greater risk of prescription opioid drug overdoses than the non-Medicaid population, and a subgroup of individuals with a high prevalence of misuse of prescription opioids experienced a 92.6-fold greater risk 14. A system that provided information about all supply of drugs of concern, whether cost was subsidized or not, would be considerably more effective in identifying individuals at risk of opioid-related death, and enable the development of countermeasures to prevent these. Poor coordination of care is a key risk factor for medication error in general medical care 16, but poorly coordinated supply of prescription opioids is a particular concern, given the escalating number of poisoning deaths involving these drugs. Current prescription monitoring programs provide historical information only to regulatory authorities, and in some cases to prescribers and pharmacists, about an individual's medication supply, but there is limited evidence of their effectiveness in preventing opioid-related deaths 17. Kurdyak and colleagues suggest that real-time information about the supply of all drugs of abuse may be needed; such could enable prescribers to make informed decisions about the safety of supply prior to prescribing, i.e. a fourth-generation coordinated medication management system (CMMS) 18. This could function similar to clinical decision support systems in general medical care designed to inform patient care decisions, prevent medical errors and improve patient safety and coordinate medical treatment 19. It is evident that much more needs to be done to improve the safety of supply and use of misused prescription drugs while maintaining availability for treatment of pain and other disabling conditions. This complex new category of substance misuse requires a comprehensive strategic response, including redesign of treatment services to attract and retain this new and often different cohort of dependent people into treatment. Finally, the iatrogenic nature of this new epidemic focuses attention on the need to understand and respond to those factors enabling the inappropriate supply or diversion of prescription opioids from licit to illicit use and to provide training and resources, such as a CMMS, to enhance the safe, coordinated supply of dangerous medicines. Dr McDonough in the past, has provided medical consultancy services to Reckitt-Benckiser regarding buprenorphine.

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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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.005
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.022
GPT teacher head0.280
Teacher spread0.258 · 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
GenreCommentary

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".

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Citations0
Published2012
Admission routes1
Has abstractyes

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