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Enregistrement W2800952982 · doi:10.7326/m18-0883

Prescription Drug Monitoring Programs: Promising Practices in Need of Refinement

2018· letter· en· W2800952982 sur OpenAlexaboutno aff
Wilson M. Compton, Eric Wargo

Notice bibliographique

RevueAnnals of Internal Medicine · 2018
Typeletter
Langueen
DomaineMedicine
ThématiqueOpioid Use Disorder Treatment
Établissements canadiensnon disponible
Organismes subventionnairesNational Institute on Drug Abuse
Mots-clésMedicineMedical prescriptionDrugIntensive care medicineMedical physicsPharmacology

Résumé

récupéré en direct d'OpenAlex

Editorials5 June 2018Prescription Drug Monitoring Programs: Promising Practices in Need of RefinementWilson M. Compton, MD, MPE and Eric M. Wargo, PhDWilson M. Compton, MD, MPENational Institute on Drug Abuse, Bethesda, Maryland (W.M.C., E.M.W.) and Eric M. Wargo, PhDNational Institute on Drug Abuse, Bethesda, Maryland (W.M.C., E.M.W.)Author, Article, and Disclosure Informationhttps://doi.org/10.7326/M18-0883 SectionsAboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinkedInRedditEmail Although recent data indicate that overdose deaths involving illicit opioids (including heroin and, especially, synthetic opioids, such as fentanyl and related compounds) have escalated in the past 3 years, widespread overprescription, diversion, and misuse of opioid analgesics started the crisis (1). Prescription opioids remain a major contributor to overdose deaths and serve as an entry point for many persons to become addicted to opioids, even if they switch to illicit opioids later because of lower cost and progression of their opioid use disorder (2–4).Implementation of prescription drug monitoring programs (PDMPs) has been among the many policy-level efforts to curb ...References1. King NB, Fraser V, Boikos C, Richardson R, Harper S. Determinants of increased opioid-related mortality in the United States and Canada, 1990-2013: a systematic review. Am J Public Health. 2014;104:e32-42. [PMID: 24922138] doi:10.2105/AJPH.2014.301966 CrossrefMedlineGoogle Scholar2. Compton WM, Jones CM, Baldwin GT. Relationship between nonmedical prescription-opioid use and heroin use. N Engl J Med. 2016;374:154-63. [PMID: 26760086] doi:10.1056/NEJMra1508490 CrossrefMedlineGoogle Scholar3. Han B, Compton WM, Blanco C, Crane E, Lee J, Jones CM. Prescription opioid use, misuse, and use disorders in U.S. adults: 2015 national survey on drug use and health. Ann Intern Med. 2017;167:293-301. [PMID: 28761945]. doi:10.7326/M17-0865 LinkGoogle Scholar4. Cicero TJ, Ellis MS, Kasper ZA. Increased use of heroin as an initiating opioid of abuse. Addict Behav. 2017;74:63-66. [PMID: 28582659] doi:10.1016/j.addbeh.2017.05.030 CrossrefMedlineGoogle Scholar5. Fink DS, Schleimer JP, Sarvet A, Grover KK, Delcher C, Castillo-Carniglia A, et al. Association between prescription drug monitoring programs and nonfatal and fatal drug overdoses. A systematic review. Ann Intern Med. 2018;168:783-90. doi:10.7326/M17-3074 LinkGoogle Scholar6. Compton WM, Jones CM, Stein JB, Wargo EM. Promising roles for pharmacists in addressing the U.S. opioid crisis. Res Social Adm Pharm. 2017. [PMID: 29325708] doi:10.1016/j.sapharm.2017.12.009 CrossrefMedlineGoogle Scholar7. Volkow ND, Collins FS. The role of science in addressing the opioid crisis. N Engl J Med. 2017;377:391-394. [PMID: 28564549] doi:10.1056/NEJMsr1706626 CrossrefMedlineGoogle Scholar8. Dowell D, Haegerich TM, Chou R. CDC guideline for prescribing opioids for chronic pain—United States, 2016. JAMA. 2016;315:1624-45. [PMID: 26977696] doi:10.1001/jama.2016.1464 CrossrefMedlineGoogle Scholar9. Spoth R, Trudeau L, Shin C, Ralston E, Redmond C, Greenberg M, et al. Longitudinal effects of universal preventive intervention on prescription drug misuse: three randomized controlled trials with late adolescents and young adults. Am J Public Health. 2013;103:665-72. [PMID: 23409883] doi:10.2105/AJPH.2012.301209 CrossrefMedlineGoogle Scholar10. Jones CM, Lurie PG, Compton WM. Increase in naloxone prescriptions dispensed in US retail pharmacies since 2013. Am J Public Health. 2016;106:689-90. [PMID: 26890174] doi:10.2105/AJPH.2016.303062 CrossrefMedlineGoogle Scholar Author, Article, and Disclosure InformationAffiliations: National Institute on Drug Abuse, Bethesda, Maryland (W.M.C., E.M.W.)Disclaimer: The opinions expressed in this commentary are those of the authors and do not necessarily reflect the views of the National Institute on Drug Abuse, the National Institutes of Health, or the U.S. Department of Health and Human Services.Disclosures: Disclosures can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M18-0883.Corresponding Author: Wilson M. Compton, MD, MPE, 6001 Executive Boulevard, MSC 9581, Bethesda, MD 20892; e-mail, [email protected]nih.gov.Current Author Addresses: Dr. Compton: 6001 Executive Boulevard, MSC 9581, Bethesda, MD 20892.Dr. Wargo: National Institute on Drug Abuse, 6001 Executive Boulevard, Bethesda, MD 20892.This article was published at Annals.org on 8 May 2018. PreviousarticleNextarticle Advertisement FiguresReferencesRelatedDetailsSee AlsoAssociation Between Prescription Drug Monitoring Programs and Nonfatal and Fatal Drug Overdoses David S. Fink , Julia P. Schleimer , Aaron Sarvet , Kiran K. Grover , Chris Delcher , Alvaro Castillo-Carniglia , June H. Kim , Ariadne E. Rivera-Aguirre , Stephen G. Henry , Silvia S. Martins , and Magdalena Cerdá Metrics Cited byEffect of a Veterans Health Administration mandate to case review patients with opioid prescriptions on mortality among patients with opioid use disorder: a secondary analysis of the STORM randomized control trialYoung adult opioid misuse indicates a general tendency toward substance use and is strongly predicted by general substance use risk"Nobody Knows How You're Supposed to Interpret it:" End-user Perspectives on Prescription Drug Monitoring Program in MassachusettsMandates are not magic bullets: Leveraging context, meaning and relationships to increase meaningful use of prescription monitoring programs"People need them or else they're going to take fentanyl and die": A qualitative study examining the 'problem' of prescription opioid diversion during an overdose epidemicDeficiencies with the Use of Prescription Drug Monitoring Program in Cancer Pain Management: A Report of Two CasesPolysubstance use in the U.S. opioid crisisThe Importance of Learning Health Systems in Addressing the Opioid CrisisAdvances in prescription drug monitoring program research: a literature synthesis (June 2018 to December 2019)Association between buprenorphine/naloxone and high-dose opioid analgesic prescribing in Kentucky, 2012–2017Prescription drug monitoring programs: Assessing the association between "best practices" and opioid use in MedicareEpidemiology of the U.S. opioid crisis: the importance of the vectorFentanyl and fentanyl-analog involvement in drug-related deathsCurrent Opioid Access, Use, and Problems in Australasian JurisdictionsPrescription Drug Monitoring Programs and drug overdoses 5 June 2018Volume 168, Issue 11Page: 826-827KeywordsDisclosureDrug abuseDrugsHeroinOpioid use disorderOpioidsPatientsPharmacistsSystematic reviewsTherapeutic drug monitoring ePublished: 8 May 2018 Issue Published: 5 June 2018 PDF downloadLoading ...

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 machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,031
score de la tête « metaresearch » (Gemma)0,152
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
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 enseignants0,031
Score d'incertitude au seuil0,164

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0310,152
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,002
Bibliométrie0,0030,002
Études des sciences et des technologies0,0030,004
Communication savante0,0090,011
Science ouverte0,0040,002
Intégrité de la recherche0,0150,016
Charge utile insuffisante (le modèle a refusé de juger)0,0220,010

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 Opus0,103
Tête enseignante GPT0,395
Écart entre enseignants0,293 · 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 source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
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

Citations19
Publié2018
Routes d'admission1
Résumé présentoui

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