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Enregistrement 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 sur OpenAlexaboutno aff
Arthur Robin Williams

Notice bibliographique

RevueAddiction · 2020
Typeletter
Langueen
DomaineMedicine
ThématiqueOpioid Use Disorder Treatment
Établissements canadiensnon disponible
Organismes subventionnairesNational Institute on Drug AbuseNational Institute of Development Administration
Mots-clésOpioid use disorderBuprenorphineOpioid overdoseMedicineMethadone(+)-NaloxonePublic healthAddictionOpioidHeroinPsychiatryDrugNursing

Résumé

récupéré en direct d'OpenAlex

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.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Charge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Commentaire · Signal consensuel: Commentaire
Score de désaccord entre enseignants0,030
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0010,001

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,015
Tête enseignante GPT0,286
Écart entre enseignants0,271 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeSans objet
Domainenon disponible
GenreCommentaire

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2020
Routes d'admission1
Résumé présentoui

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