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Record W3009112246 · doi:10.1111/add.15022

Commentary on Piske <i>et al</i>. (2020): Medication initiation is key to reduce deaths amid opioid crisis

2020· letter· en· W3009112246 on OpenAlexaboutno aff
Arthur Robin Williams

Bibliographic record

VenueAddiction · 2020
Typeletter
Languageen
FieldMedicine
TopicOpioid Use Disorder Treatment
Canadian institutionsnot available
FundersNational Institute on Drug AbuseNational Institute of Development Administration
KeywordsOpioid use disorderBuprenorphineOpioid overdoseMedicineMethadone(+)-NaloxonePublic healthAddictionOpioidHeroinPsychiatryDrugNursing

Abstract

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The OUD Cascade of Care is a public health framework for guiding efforts to more effectively respond to the opioid epidemic. Officials can track progress across each stage, from diagnosis to recovery, to help identify gaps across systems. This may be especially meaningful for improving outcomes among more complex patient populations. The OUD Cascade of Care has become a preferred framework for public health agencies monitoring progress amid the opioid epidemic 1, 2. Similar to trends in many parts of the United States, Piske and colleagues 3 observed a greater than threefold increase in the number of individuals diagnosed with opioid use disorder (OUD) across British Columbia, which has the highest provincial opioid-related death rate in Canada. Canada, however, has developed a much more capacious and low-threshold treatment system for OUD which other countries, especially the United States, could learn from. Indeed, the authors explain that the most commonly used forms of opioid agonist treatment (OAT), methadone and buprenorphine/naloxone, can be prescribed by primary physicians [with no need for a Drug Enforcement Administration (DEA) ‘X-waiver’] and dispensed via community-based pharmacies—something that US federal agencies have long refused to allow 4. Since mid-2017 alternative forms of OAT, including slow-release oral morphine and injectables, have also been offered in these low-threshold settings. The authors identified annual increases of up to 12% in the number of people with OUD who had ever initiated OAT, probably a reflection of long-standing provincial efforts to expand access to low-barrier addiction treatment. The authors also describe how, to expand access to OAT, the province of British Columbia has opened integrated care clinics, addiction treatment support programs, approved new forms of OAT with new clinical guidelines and eliminated copayment fees for the vast majority of clients, in addition to most physician eligibility requirements for prescribing capabilities. While there are clinical pilot programs in forward-thinking states such as Vermont and Massachusetts 5, none have been as all-encompassing as the level of regulatory reform referenced by the authors. It is not a surprise, then, that the authors’ findings along the OUD Cascade of Care far surpass estimates for US populations. They found that, in 2017, 71% of those diagnosed had engaged in past-year OAT and 33% were currently on OAT; however, only 16% had been retained on medication for more than a year. The comparable estimates are much lower in the United States, perhaps by two-thirds, although epidemiological surveillance is extremely limited—another facet of the US response that is inexplicably inferior to other western nations 1. Regardless, successful long-term retention (beyond 1 year) clearly is a challenge throughout the addiction field, especially for patients with OUD. Across treatment settings, Medicaid populations 6, 7 and commercially insured populations 8 in prospective and observational studies have replicated high rates of medication discontinuation within just a few weeks or months of medication initiation. However, empirical studies suggest that patients do not attain long-term benefits from short-term durations of care and probably need 1–2 years or longer of medication treatment before sustaining reduced risk of relapse and overdose 9. Novel strategies are needed to more effectively retain patients in care and these arguably require regulatory reform, system re-design, alternative payment structures for value-based care and massive efforts at work-force development extending throughout hard-hit areas 4. Despite greater rates of OAT among populations in British Columbia than other North American regions, the authors nonetheless found a widespread lack of evidence-based practices following high acuity service utilization—and, indeed, a missed opportunity for intervention that cannot be rationalized. The authors found that as of 2015, only 7% of cases identified by inpatient hospitalizations received OAT within 3 months of their diagnosis and yet hospitalizations were common, particularly among those diagnosed with OUD (46%) and those who discontinued OAT (22%) within the past year. Acute care (emergency departments and hospitals) and correctional settings (for instance, the United States has more than 5000 jails and prisons detaining millions of individuals a year) represent the front lines of where some of our largest institutions—all with medical professionals—interface with individuals with OUD. Recent estimates suggest that approximately half of individuals with heroin addiction have had criminal justice involvement in the past year 10. These are golden opportunities for OAT initiation and should be optimized for connecting patients with high quality care. The OUD Cascade of Care is a useful framework for guiding national and regional efforts to better respond to the opioid epidemic. While officials can track progress across each stage of the Cascade, from diagnosis to recovery, they can also zero in on major gaps across addiction treatment systems. This may be especially meaningful for reaching and stabilizing more complex and vulnerable patient populations. A.R.W.’s research is funded by NIDA and SAMHSA. He also receives consulting fees from treatment providers and insurance companies providing care for patients with OUD and other substance use disorders.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

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), 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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.030
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
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)0.0010.001

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 head0.015
GPT teacher head0.286
Teacher spread0.271 · 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".

Quick stats

Citations1
Published2020
Admission routes1
Has abstractyes

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