Toward Better Stewardship: Gaining Control Over Controlled Substances
Authors: Lynn E. Fiellin, David A. Fiellin
Journal: Annals of Internal Medicine (2018)

Editorials19 June 2018Toward Better Stewardship: Gaining Control Over Controlled SubstancesLynn E. Fiellin, MD and David A. Fiellin, MDLynn E. Fiellin, MDYale University School of Medicine, New Haven, Connecticut (L.E.F., D.A.F.) and David A. Fiellin, MDYale University School of Medicine, New Haven, Connecticut (L.E.F., D.A.F.)Author, Article, and Disclosure Informationhttps://doi.org/10.7326/M18-1146 SectionsAboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinkedInRedditEmail In 2016, 11.5 million persons in the United States reported nonmedical use of prescription opioids; close to half a million reported nonmedical use of sedative agents, such as benzodiazepines; and 1.7 million reported nonmedical use of stimulant medications (1). The current prevalence of nonmedical use of controlled substances raises an essential question: How can we provide better stewardship of these medications?It is in this context that Carey and colleagues (2) conducted a study in 627 391 Medicare beneficiaries who received opioid prescriptions between 2008 and 2012. The authors examined the relationship between various opioid prescription patterns, including quantity of opioids, ...References1. Substance Abuse and Mental Health Services Administration. Key substance use and mental health indicators in the United States: results from the 2016 National Survey on Drug Use and Health (HHS Publication No. SMA 17-5044, NSDUH Series H-52). 2017. Accessed at www.samhsa.gov/data/ on 29 April 2018. Google Scholar2. Carey CM, Jena AB, Barnett ML. Patterns of potential opioid misuse and subsequent adverse outcomes in Medicare, 2008 to 2012. Ann Intern Med. 2018;168:837-45. doi:10.7326/M17-3065 LinkGoogle Scholar3. Piper BJ, Shah DT, Simoyan OM, McCall KL, Nichols SD. Trends in medical use of opioids in the U.S., 2006-2016. Am J Prev Med. 2018;54:652-660. [PMID: 29551331] doi:10.1016/j.amepre.2018.01.034 CrossrefMedlineGoogle Scholar4. Renoux C, Dell'Aniello S, Brenner B, Suissa S. Bias from depletion of susceptibles: the example of hormone replacement therapy and the risk of venous thromboembolism. Pharmacoepidemiol Drug Saf. 2017;26:554-560. [PMID: 28326633] doi:10.1002/pds.4197 CrossrefMedlineGoogle Scholar5. Patrick SW, Fry CE, Jones TF, Buntin MB. Implementation of prescription drug monitoring programs associated with reductions in opioid-related death rates. Health Aff (Millwood). 2016;35:1324-32. [PMID: 27335101] doi:10.1377/hlthaff.2015.1496 CrossrefMedlineGoogle Scholar6. Pauly NJ, Slavova S, Delcher C, Freeman PR, Talbert J. Features of prescription drug monitoring programs associated with reduced rates of prescription opioid-related poisonings. Drug Alcohol Depend. 2018;184:26-32. [PMID: 29402676] doi:10.1016/j.drugalcdep.2017.12.002 CrossrefMedlineGoogle Scholar7. Gugelmann H, Perrone J, Nelson L. Windmills and pill mills: can PDMPs tilt the prescription drug epidemic? J Med Toxicol. 2012;8:378-86. [PMID: 23180357] doi:10.1007/s13181-012-0273-8 CrossrefMedlineGoogle Scholar8. McLellan AT, Turner B. Prescription opioids, overdose deaths, and physician responsibility [Editorial]. JAMA. 2008;300:2672-3. [PMID: 19066389] doi:10.1001/jama.2008.793 CrossrefMedlineGoogle Scholar9. Hawk K, D'Onofrio G, Fiellin DA, Chawarski MC, O'Connor PG, Owens PH, et al. Past-year prescription drug monitoring program opioid prescriptions and self-reported opioid use in an emergency department population with opioid use disorder. Acad Emerg Med. 2017. [PMID: 29165853] doi:10.1111/acem.13352 CrossrefMedlineGoogle Scholar10. Becker WC, Tobin DG, Fiellin DA. Nonmedical use of opioid analgesics obtained directly from physicians: prevalence and correlates. Arch Intern Med. 2011;171:1034-6. [PMID: 21670373] doi:10.1001/archinternmed.2011.217 CrossrefMedlineGoogle Scholar Author, Article, and Disclosure InformationAffiliations: Yale University School of Medicine, New Haven, Connecticut (L.E.F., D.A.F.)Disclosures: Authors have disclosed no conflicts of interest. Forms can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M18-1146.Corresponding Author: Lynn E. Fiellin, MD, Yale University School of Medicine, 367 Cedar Street, ESH A, New Haven, CT 06510; e-mail, lynn.[email protected]edu.Current Author Addresses: Drs. L.E. Fiellin and D.A. Fiellin: Yale University School of Medicine, 367 Cedar Street, ESH A, New Haven, CT 06510.This article was published at Annals.org on 22 May 2018. PreviousarticleNextarticle Advertisement FiguresReferencesRelatedDetailsSee AlsoPatterns of Potential Opioid Misuse and Subsequent Adverse Outcomes in Medicare, 2008 to 2012 Colleen M. Carey , Anupam B. Jena , and Michael L. Barnett Metrics Cited byUsing Prescription Drug Monitoring Program Data to Assess Likelihood of Incident Long-Term Opioid Use: a Statewide Cohort StudyA Risk Prediction Model for Long-term Prescription Opioid UseThe Tightrope Walk 19 June 2018Volume 168, Issue 12Page: 883-884KeywordsComputed axial tomographyDatabasesElectronic medical recordsMedicareMortalityOpioidsRelative riskSedativesSoftware toolsTherapeutic drug monitoring ePublished: 22 May 2018 Issue Published: 19 June 2018 Copyright & PermissionsCopyright © 2018 by American College of Physicians. All Rights Reserved.PDF downloadLoading ...